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Resolving the Price Volatility Puzzle The Role of Earningslowast
Gil Sadkadagger
First version November 23 2003
This version January 26 2005
Abstract
In an efficient market prices should vary only if investors change their expectations about
cash flows discount factors or both Previous research showed that the dividend yield varies
mostly due to variation in expected returns and contains little information about cash flows
This literature uses dividend growth variation as its measure of cash-flow information However
according to Miller and Modigliani (1961) with no taxes given earnings dividends are strictly a
financing decision and should not affect prices Consistent with the dividend-policy irrelevance
hypothesis this paper shows that variation in expected profitability growth explains as much
as 70 of the variation in the dividend yield Thus the dividend yield contains information
about cash flows in terms of earnings not dividends In addition this paper finds evidence
consistent with a permanent downward shift in the dividend yield in the 1990s Controlling
for this permanent shift the results indicate that the dividend yield has not lost its ability to
predict returns
Keywords accounting valuation expected-return variation profitability equity premium variance
decomposition
lowastI would like to thank Ray Ball Philip Berger John Cochrane Richard Leftwich Efraim Sadka Ronnie Sadka
Wendy Rothschild Douglas Skinner Kendrew Witt and the workshop participants at the University of Chicago for
comments and suggestions Any errors are my own I gratefully acknowledge financial support from the University
of Chicago Graduate School of BusinessdaggerUniversity of Chicago Graduate School of Business 5807 S Woodlawn Ave Chicago Illinois 60637 e-mail
gsadkaChicagoGSBedu
1 Introduction
In general prices are expected discounted cash flows Thus there are two factors that may af-
fect prices the expectations regarding discount factors and expectations regarding future cash
flows Research on stock price volatility has found that variation in expected returns explains
most of the variation in aggregate stock returns (the market portfolio) and the dividend yield (eg
Campbell and Shiller (1988a 1988b) Campbell (1991) and Campbell and Ammer (1993))1 On
the other hand variation in expected dividends does not explain much of the variation in prices
Consistent with this analysis on stock price volatility the finance literature has found that re-
turns are predictable and dividends are not (see eg Fama and French (1988 1989) Keim and
Stambaugh (1986) Lettau and Ludvigson (2001) Kothari and Shanken (1997) Lamont (1998)
and Cochrane (2001)) Exceptions are Ribeiro (2002) and Lettau and Ludvigson (2004) who find
that the labor-income-to-dividend and the consumption-to-wealth ratios identify some predictable
dividend variation While these recent studies find evidence of dividend predictability it remains
the case that dividends do not seem to affect the dividend-price ratio (dividend yield)
These results are somewhat disturbing Prices are simply expected discounted cash flows Thus
one would expect that both cash flow and return variation would generate price variation Since
the dividend yield is stationary and varies it must predict either returns or cash flows or both
The evidence described above suggests that only expected returns variation affects the aggregate
dividend yield For instance as Cochrane (2001) points out It is nonetheless an uncomfortable
fact that almost all variation in pricedividend ratios is due to variation in expected excess returns
How nice it would be if high prices reflected expectations of higher future cash flows
This literature focuses on dividends as cash flow information However dividends are not
expected to have an effect on prices According to Miller and Modigliani (1961) given earnings and
ignoring taxes dividend policy is irrelevant and should not affect prices Dividends are irrelevant
because earnings measure the potential cash flow that the asset generates and dividends are only
an endogenous financing decision made by the firm and its stock holders (when the dividend is
1When the analysis is applied in the cross-section (eg Vuolteenaho (2002) Callen and Segal (2004) Easton (2004)
and Cohen Polk and Vuolteenaho (2003)) the results suggest that variation in expected profitability can explain
much of the variation in the firm-level book-to-market returns and earnings-price ratios The difference between the
aggregate and firm-level results has been attributed in part to the relative strength of the idiosyncratic components
of cash flow variation versus the systematic components of expected returns
2
distributed) Earnings on the other hand are not an endogenous decision they are a result of the
firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends
The difference between dividends and earnings approximates the difference between actual cash
flow and free cash flow Investors are not interested in expected short-term dividends They are
interested in the expected ability to pay out cash ie free cash flow Therefore the relevant
variable to predict or in other words the variable that should be reflected in prices is profitability
growth and not dividend growth
The primary advantage of using accounting income in this setting as opposed to dividends
stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given
earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends
do not matter In the long-run investors are concerned with discounted cash flows (dividends) that
the asset produces However this paper suggests that on the aggregate level short-run dividend
variations do not affect prices On the other hand investors will be sensitive to earnings variations
because they provide information about the long-run dividend flow Accounting income must be
received in cash or assets in the future which will eventually be distributed as dividends In
contrast dividends do not necessarily reflect future cash flows they are distributed from past and
current earnings
The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in
the 1990s There are many firms trading with a positive price that do not pay dividends and
are not expected to pay dividends in the short-run Even though these firms may not distribute
dividends or are not expected to in the short-term it does not mean their prices do not vary due
to changes in expected cash flows The price of the stock reflects the long-run dividend stream
which is a function of current and expected earnings - dividends follow earnings The firm invests
it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash
to finance its operations it distributes it as dividends In sum in the long-run it does not matter
if we choose dividends or earnings because they are the same but earnings are more appropriate
in short-horizon tests of stock price volatility
This role of accounting information has been studied extensively in the literature For example
Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo
performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal
3
the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive
cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and
the cash flows itrsquos entitled to one must include accounts receivables in the performance measure
Therefore cash measures alone would not be appropriate as performance measures
Earnings have several advantages over dividends in addition to the fact that dividends are a
result of financing decisions The legal status of earnings makes it the most appropriate measure of
future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the
firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders
While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and
Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from
accrued earnings They cannot legally exceed the book value of retained earnings
Previous research provides an additional reason for using earnings as a proxy for future cash
flows Previous literature found that prices contain information about expected earnings For
instance empirical evidence suggests that prices predict earnings better than conventional time
series models and that current price changes reflect future expected earnings shocks (see eg Beaver
Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn
(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in
early research such as Ball and Brown (1968) The accounting literature on prices and earnings
implies that the slope on the dividend yield with respect to earnings growth is expected to be
negative That is higher prices reflect expectations for higher future profitability Therefore
higher expected earnings push prices up and the dividend yield down
The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price
volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the
dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice
that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth
The above implies that earnings and the earning-dividend ratio are good candidates to test for
(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability
In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to
expected profitability (Return on Equity - ROE)
4
the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and
Brown (1967)) that is priced
Based on the discussion above this paper contributes to the study of price volatility and pre-
dictability of earnings and returns by studying the information contained in the aggregate dividend
yield with regard to cash flows Specifically this paper investigates whether the dividend yield
contains information about future cash flows in terms of accounting income The results show that
expected profitability is a major source of dividend yield variation During the sample period (1952
- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield
Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield
This finding is consistent with a large body of research that studies the role of accounting income
in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball
Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings
and accruals are more strongly associated with stock prices than are dividends and cash flows
In the short-term the dividend yield is informative about earnings not dividends In the long-
term over the life of the firm earnings and dividends are the same But in the short-term such as
the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate
measure of cash flows because earnings are more timely In fact the results suggest that the
dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to
expected dividend smoothing when expected earnings are high the expected dividend-earnings
ratio is low and vice versaUsing these results this paper shows that the dividend yield would
only be able to predict dividends in the very long-term Higher expected earnings are not expected
to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope
coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-
term earnings rather than dividends is the more appropriate and more useful measure of cash
flows
As discussed above this paper finds that the dividend yield predicts both expected returns and
expected earnings growth Since the dividend yield predicts both returns and profitability it is
clear that the two are not independent In fact the results indicate a negative contemporaneous
correlation between returns and earnings growth However returns are positively correlated (021)
5See also Ribeiro (2002) and Pastor and Veronesi (2003)
5
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
1 Introduction
In general prices are expected discounted cash flows Thus there are two factors that may af-
fect prices the expectations regarding discount factors and expectations regarding future cash
flows Research on stock price volatility has found that variation in expected returns explains
most of the variation in aggregate stock returns (the market portfolio) and the dividend yield (eg
Campbell and Shiller (1988a 1988b) Campbell (1991) and Campbell and Ammer (1993))1 On
the other hand variation in expected dividends does not explain much of the variation in prices
Consistent with this analysis on stock price volatility the finance literature has found that re-
turns are predictable and dividends are not (see eg Fama and French (1988 1989) Keim and
Stambaugh (1986) Lettau and Ludvigson (2001) Kothari and Shanken (1997) Lamont (1998)
and Cochrane (2001)) Exceptions are Ribeiro (2002) and Lettau and Ludvigson (2004) who find
that the labor-income-to-dividend and the consumption-to-wealth ratios identify some predictable
dividend variation While these recent studies find evidence of dividend predictability it remains
the case that dividends do not seem to affect the dividend-price ratio (dividend yield)
These results are somewhat disturbing Prices are simply expected discounted cash flows Thus
one would expect that both cash flow and return variation would generate price variation Since
the dividend yield is stationary and varies it must predict either returns or cash flows or both
The evidence described above suggests that only expected returns variation affects the aggregate
dividend yield For instance as Cochrane (2001) points out It is nonetheless an uncomfortable
fact that almost all variation in pricedividend ratios is due to variation in expected excess returns
How nice it would be if high prices reflected expectations of higher future cash flows
This literature focuses on dividends as cash flow information However dividends are not
expected to have an effect on prices According to Miller and Modigliani (1961) given earnings and
ignoring taxes dividend policy is irrelevant and should not affect prices Dividends are irrelevant
because earnings measure the potential cash flow that the asset generates and dividends are only
an endogenous financing decision made by the firm and its stock holders (when the dividend is
1When the analysis is applied in the cross-section (eg Vuolteenaho (2002) Callen and Segal (2004) Easton (2004)
and Cohen Polk and Vuolteenaho (2003)) the results suggest that variation in expected profitability can explain
much of the variation in the firm-level book-to-market returns and earnings-price ratios The difference between the
aggregate and firm-level results has been attributed in part to the relative strength of the idiosyncratic components
of cash flow variation versus the systematic components of expected returns
2
distributed) Earnings on the other hand are not an endogenous decision they are a result of the
firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends
The difference between dividends and earnings approximates the difference between actual cash
flow and free cash flow Investors are not interested in expected short-term dividends They are
interested in the expected ability to pay out cash ie free cash flow Therefore the relevant
variable to predict or in other words the variable that should be reflected in prices is profitability
growth and not dividend growth
The primary advantage of using accounting income in this setting as opposed to dividends
stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given
earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends
do not matter In the long-run investors are concerned with discounted cash flows (dividends) that
the asset produces However this paper suggests that on the aggregate level short-run dividend
variations do not affect prices On the other hand investors will be sensitive to earnings variations
because they provide information about the long-run dividend flow Accounting income must be
received in cash or assets in the future which will eventually be distributed as dividends In
contrast dividends do not necessarily reflect future cash flows they are distributed from past and
current earnings
The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in
the 1990s There are many firms trading with a positive price that do not pay dividends and
are not expected to pay dividends in the short-run Even though these firms may not distribute
dividends or are not expected to in the short-term it does not mean their prices do not vary due
to changes in expected cash flows The price of the stock reflects the long-run dividend stream
which is a function of current and expected earnings - dividends follow earnings The firm invests
it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash
to finance its operations it distributes it as dividends In sum in the long-run it does not matter
if we choose dividends or earnings because they are the same but earnings are more appropriate
in short-horizon tests of stock price volatility
This role of accounting information has been studied extensively in the literature For example
Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo
performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal
3
the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive
cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and
the cash flows itrsquos entitled to one must include accounts receivables in the performance measure
Therefore cash measures alone would not be appropriate as performance measures
Earnings have several advantages over dividends in addition to the fact that dividends are a
result of financing decisions The legal status of earnings makes it the most appropriate measure of
future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the
firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders
While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and
Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from
accrued earnings They cannot legally exceed the book value of retained earnings
Previous research provides an additional reason for using earnings as a proxy for future cash
flows Previous literature found that prices contain information about expected earnings For
instance empirical evidence suggests that prices predict earnings better than conventional time
series models and that current price changes reflect future expected earnings shocks (see eg Beaver
Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn
(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in
early research such as Ball and Brown (1968) The accounting literature on prices and earnings
implies that the slope on the dividend yield with respect to earnings growth is expected to be
negative That is higher prices reflect expectations for higher future profitability Therefore
higher expected earnings push prices up and the dividend yield down
The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price
volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the
dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice
that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth
The above implies that earnings and the earning-dividend ratio are good candidates to test for
(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability
In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to
expected profitability (Return on Equity - ROE)
4
the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and
Brown (1967)) that is priced
Based on the discussion above this paper contributes to the study of price volatility and pre-
dictability of earnings and returns by studying the information contained in the aggregate dividend
yield with regard to cash flows Specifically this paper investigates whether the dividend yield
contains information about future cash flows in terms of accounting income The results show that
expected profitability is a major source of dividend yield variation During the sample period (1952
- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield
Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield
This finding is consistent with a large body of research that studies the role of accounting income
in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball
Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings
and accruals are more strongly associated with stock prices than are dividends and cash flows
In the short-term the dividend yield is informative about earnings not dividends In the long-
term over the life of the firm earnings and dividends are the same But in the short-term such as
the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate
measure of cash flows because earnings are more timely In fact the results suggest that the
dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to
expected dividend smoothing when expected earnings are high the expected dividend-earnings
ratio is low and vice versaUsing these results this paper shows that the dividend yield would
only be able to predict dividends in the very long-term Higher expected earnings are not expected
to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope
coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-
term earnings rather than dividends is the more appropriate and more useful measure of cash
flows
As discussed above this paper finds that the dividend yield predicts both expected returns and
expected earnings growth Since the dividend yield predicts both returns and profitability it is
clear that the two are not independent In fact the results indicate a negative contemporaneous
correlation between returns and earnings growth However returns are positively correlated (021)
5See also Ribeiro (2002) and Pastor and Veronesi (2003)
5
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
distributed) Earnings on the other hand are not an endogenous decision they are a result of the
firmsrsquo operations and investments and thus represent the ability of firms to distribute dividends
The difference between dividends and earnings approximates the difference between actual cash
flow and free cash flow Investors are not interested in expected short-term dividends They are
interested in the expected ability to pay out cash ie free cash flow Therefore the relevant
variable to predict or in other words the variable that should be reflected in prices is profitability
growth and not dividend growth
The primary advantage of using accounting income in this setting as opposed to dividends
stems from the theory developed by Miller and Modigliani (1961) The theory suggests that given
earnings and ignoring taxes dividend policy is irrelevant This paper does not claim that dividends
do not matter In the long-run investors are concerned with discounted cash flows (dividends) that
the asset produces However this paper suggests that on the aggregate level short-run dividend
variations do not affect prices On the other hand investors will be sensitive to earnings variations
because they provide information about the long-run dividend flow Accounting income must be
received in cash or assets in the future which will eventually be distributed as dividends In
contrast dividends do not necessarily reflect future cash flows they are distributed from past and
current earnings
The hypothesis of short-term dividend irrelevance is apparent in stock prices particularly in
the 1990s There are many firms trading with a positive price that do not pay dividends and
are not expected to pay dividends in the short-run Even though these firms may not distribute
dividends or are not expected to in the short-term it does not mean their prices do not vary due
to changes in expected cash flows The price of the stock reflects the long-run dividend stream
which is a function of current and expected earnings - dividends follow earnings The firm invests
it accrues earnings the earnings turn into cash flows and when the firm no longer requires the cash
to finance its operations it distributes it as dividends In sum in the long-run it does not matter
if we choose dividends or earnings because they are the same but earnings are more appropriate
in short-horizon tests of stock price volatility
This role of accounting information has been studied extensively in the literature For example
Dechow (1994) illustrates that accounting earnings and accruals are better measures of firmsrsquo
performance than cash flows2 A common example is accounts receivables Assume that some of2See also Basu (1997) Ball Kothari and Robin (2000) Dechow Kothari and Watts (1998) and Callen and Segal
3
the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive
cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and
the cash flows itrsquos entitled to one must include accounts receivables in the performance measure
Therefore cash measures alone would not be appropriate as performance measures
Earnings have several advantages over dividends in addition to the fact that dividends are a
result of financing decisions The legal status of earnings makes it the most appropriate measure of
future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the
firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders
While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and
Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from
accrued earnings They cannot legally exceed the book value of retained earnings
Previous research provides an additional reason for using earnings as a proxy for future cash
flows Previous literature found that prices contain information about expected earnings For
instance empirical evidence suggests that prices predict earnings better than conventional time
series models and that current price changes reflect future expected earnings shocks (see eg Beaver
Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn
(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in
early research such as Ball and Brown (1968) The accounting literature on prices and earnings
implies that the slope on the dividend yield with respect to earnings growth is expected to be
negative That is higher prices reflect expectations for higher future profitability Therefore
higher expected earnings push prices up and the dividend yield down
The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price
volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the
dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice
that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth
The above implies that earnings and the earning-dividend ratio are good candidates to test for
(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability
In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to
expected profitability (Return on Equity - ROE)
4
the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and
Brown (1967)) that is priced
Based on the discussion above this paper contributes to the study of price volatility and pre-
dictability of earnings and returns by studying the information contained in the aggregate dividend
yield with regard to cash flows Specifically this paper investigates whether the dividend yield
contains information about future cash flows in terms of accounting income The results show that
expected profitability is a major source of dividend yield variation During the sample period (1952
- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield
Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield
This finding is consistent with a large body of research that studies the role of accounting income
in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball
Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings
and accruals are more strongly associated with stock prices than are dividends and cash flows
In the short-term the dividend yield is informative about earnings not dividends In the long-
term over the life of the firm earnings and dividends are the same But in the short-term such as
the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate
measure of cash flows because earnings are more timely In fact the results suggest that the
dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to
expected dividend smoothing when expected earnings are high the expected dividend-earnings
ratio is low and vice versaUsing these results this paper shows that the dividend yield would
only be able to predict dividends in the very long-term Higher expected earnings are not expected
to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope
coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-
term earnings rather than dividends is the more appropriate and more useful measure of cash
flows
As discussed above this paper finds that the dividend yield predicts both expected returns and
expected earnings growth Since the dividend yield predicts both returns and profitability it is
clear that the two are not independent In fact the results indicate a negative contemporaneous
correlation between returns and earnings growth However returns are positively correlated (021)
5See also Ribeiro (2002) and Pastor and Veronesi (2003)
5
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77
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Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37
Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340
Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28
Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560
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dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of
Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of
prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of
Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal
of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on
equity capital The Accounting Review 79 (1) 73-95
21
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
the firmrsquos sales are made on account In this case the firm and its assets generate the right to receive
cash flows Because the cash is not yet received then in order to measure the firmrsquos performance and
the cash flows itrsquos entitled to one must include accounts receivables in the performance measure
Therefore cash measures alone would not be appropriate as performance measures
Earnings have several advantages over dividends in addition to the fact that dividends are a
result of financing decisions The legal status of earnings makes it the most appropriate measure of
future cash flows Firms distribute dividends from accrued earnings Legally earnings represent the
firmrsquos verifiable cash flows generated by its investments and assets that belong to its stock holders
While dividends might provide a signal for future profitability (eg Watts (1973) and Healy and
Palepu (1988) and Nissim and Ziv (2001))3 it remains the case that dividends are distributed from
accrued earnings They cannot legally exceed the book value of retained earnings
Previous research provides an additional reason for using earnings as a proxy for future cash
flows Previous literature found that prices contain information about expected earnings For
instance empirical evidence suggests that prices predict earnings better than conventional time
series models and that current price changes reflect future expected earnings shocks (see eg Beaver
Clarke and Wright (1979) Beaver Lambert and Morse (1980) Collins Kothari and Rayburn
(1987) Collins and Kothari (1989) and Kothari and Sloan (1992)) This result is also apparent in
early research such as Ball and Brown (1968) The accounting literature on prices and earnings
implies that the slope on the dividend yield with respect to earnings growth is expected to be
negative That is higher prices reflect expectations for higher future profitability Therefore
higher expected earnings push prices up and the dividend yield down
The third reason for using the aggregate earnings and earnings-dividend ratio in tests of price
volatility is the evidence concerning their predictability For instance Lamont (1998) finds that the
dividend-earnings ratio co-integrates with the dividend-price ratio and predicts returns4 Notice
that earnings growth multiplied by the dividend-earnings ratio growth is equal to dividend growth
The above implies that earnings and the earning-dividend ratio are good candidates to test for
(2004)3 In contrast DeAngelo DeAngelo and Skinner (1996) find that dividends are not a reliable signal for profitability
In addition Watts (1973) finds only weak evidence of the predictive power of dividends with respect to earnings4Vuolteenaho (2000) finds that as much as 40 of the variation in the aggregate book-to-market ratio is due to
expected profitability (Return on Equity - ROE)
4
the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and
Brown (1967)) that is priced
Based on the discussion above this paper contributes to the study of price volatility and pre-
dictability of earnings and returns by studying the information contained in the aggregate dividend
yield with regard to cash flows Specifically this paper investigates whether the dividend yield
contains information about future cash flows in terms of accounting income The results show that
expected profitability is a major source of dividend yield variation During the sample period (1952
- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield
Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield
This finding is consistent with a large body of research that studies the role of accounting income
in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball
Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings
and accruals are more strongly associated with stock prices than are dividends and cash flows
In the short-term the dividend yield is informative about earnings not dividends In the long-
term over the life of the firm earnings and dividends are the same But in the short-term such as
the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate
measure of cash flows because earnings are more timely In fact the results suggest that the
dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to
expected dividend smoothing when expected earnings are high the expected dividend-earnings
ratio is low and vice versaUsing these results this paper shows that the dividend yield would
only be able to predict dividends in the very long-term Higher expected earnings are not expected
to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope
coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-
term earnings rather than dividends is the more appropriate and more useful measure of cash
flows
As discussed above this paper finds that the dividend yield predicts both expected returns and
expected earnings growth Since the dividend yield predicts both returns and profitability it is
clear that the two are not independent In fact the results indicate a negative contemporaneous
correlation between returns and earnings growth However returns are positively correlated (021)
5See also Ribeiro (2002) and Pastor and Veronesi (2003)
5
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
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Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
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when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
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56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
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22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
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-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
the predictability of cash flows5 or systematic undiversifiable profitability variation (eg Ball and
Brown (1967)) that is priced
Based on the discussion above this paper contributes to the study of price volatility and pre-
dictability of earnings and returns by studying the information contained in the aggregate dividend
yield with regard to cash flows Specifically this paper investigates whether the dividend yield
contains information about future cash flows in terms of accounting income The results show that
expected profitability is a major source of dividend yield variation During the sample period (1952
- 2001) earnings growth explains as much as 70 of the variation in the aggregate dividend yield
Thus expected earnings growth is one of the factors that determine the equilibrium dividend yield
This finding is consistent with a large body of research that studies the role of accounting income
in the economy and asset prices (eg Dechow (1994) Basu (1997) Callen and Segal (2004) Ball
Kothari and Robin (2000) and Penman and Yehuda (2004)) These studies document that earnings
and accruals are more strongly associated with stock prices than are dividends and cash flows
In the short-term the dividend yield is informative about earnings not dividends In the long-
term over the life of the firm earnings and dividends are the same But in the short-term such as
the ten to 15-year-ahead horizon commonly used in the literature earnings are a more appropriate
measure of cash flows because earnings are more timely In fact the results suggest that the
dividend yield predicts both earnings growth and changes in the dividend-earnings ratio Due to
expected dividend smoothing when expected earnings are high the expected dividend-earnings
ratio is low and vice versaUsing these results this paper shows that the dividend yield would
only be able to predict dividends in the very long-term Higher expected earnings are not expected
to contemporaneously translate into higher dividends The implied 40-year-ahead horizon slope
coefficient of log dividend growth on the log dividend-price ratio is only -019 Thus in the short-
term earnings rather than dividends is the more appropriate and more useful measure of cash
flows
As discussed above this paper finds that the dividend yield predicts both expected returns and
expected earnings growth Since the dividend yield predicts both returns and profitability it is
clear that the two are not independent In fact the results indicate a negative contemporaneous
correlation between returns and earnings growth However returns are positively correlated (021)
5See also Ribeiro (2002) and Pastor and Veronesi (2003)
5
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
with the one-year ahead earnings growth (this result is not tabulated in the paper) Since lower
dividend yield predicts both low expected returns and high earnings growth the contemporaneous
correlation between earnings growth and returns is expected to be negative A sharp price increase
(high contemporaneous returns) would result in a decline in the dividend-price ratio and hence
should be positively correlated with long-term earnings growth Consequently variations in the
dividend yield due to variations in expected returns can be attributable in part to variations in
expected earnings
In addition to the lack of dividend predictability some recent studies (eg Lettau and Ludvigson
(2004)) find that the dividend yield has declined and lost its ability to predict returns This
paper finds evidence consistent with a permanent downward shift in the 1990s Controlling for the
permanent change the results suggest that the dividend yield is a good predictor of future excess
returns and future earnings growth In fact the R2 of the regression of one-year-ahead horizon
returns on the dividend yield is 10 Moreover the coefficients are very similar to the ones reported
in Cochrane (2001) using a sample period ending at 1996 consistent with a permanent shift in the
dividend yield
The remainder of this paper is organized as follows Section 2 provides a short description of
the data and their sources Section 3 tests whether the dividend yield contains information about
cash flows through expected accounting earnings growth Section 4 includes some additional tests
including tests aimed at determining whether the equilibrium dividend yield has declined Section
5 concludes
2 Data
The sample contains all firm-year data in the CRSP monthly and COMPUSTAT annual databases
for the period 1952-2001 for firms with fiscal-year ends in December The December fiscal year end
requirement avoids temporal misspecifications due to different reporting and different cumulation
periods of annual earnings The returns dividends and price data are extracted from the CRSP
monthly data set The earnings item used is the earnings before extraordinary items in COMPU-
STAT The annual financial variables are measured from April of year t until March of year t+ 1
Table 1 reports summary statistics for the data used in this paper The table reports the time
series averages medians and standard deviations of the variables used in the paper The annual
6
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
returns are the annual value-weighted returns in excess of the risk-free rate6 The risk free rate is
extracted from the Fama and French three factor model data in the WRDS database
The earnings growth measure is defined as growth in the sum of annual earnings for the sample
firms This paper deviates from past literature (eg Vuolteenaho (2002) uses return on equity)
in its measure of profitability for two reasons First accounting conservatism7 requires timely
recognition of expected declines in cash flows and at the same time does not allow firms to recognize
unverifiable expected increases in cash flows This asymmetry in recognition of economic income
results in a skewed earnings distribution (with relatively large negative values) This skewness is
likely to affect profitability measures such as average profitability growth and average return on
equity The summary statistics in Table 1 for earnings growth are consistent with a symmetric
distribution Second earnings growth is very similar in essence to dividend growth commonly used
in the literature (eg Cochrane (2001)) and the sum of earnings is a good approximation for the
profitability of the market portfolio which is the variable of interest
3 The Dividend Yield and the Predictability of Earnings Divi-
dends and Returns
Previous studies suggest that the dividend yield varies mainly due to variations in expected returns
As noted above the stationarity of the dividend yield implies that it must predict either returns
or cash flows or both The evidence suggests that the dividend-price ratio contains very little
information regarding future dividend growth
Table 2 reports the estimation of the regression models
Rtminusrarrt+i = δ0 + δ1 middotDPt + ηt+i (1)
and
Dt+iDt = δ0 + δ1 middotDPt + ηt+i (2)
The table provides a short summary of previously recorded results in the literature (eg Fama and
6Tables 4-7 use raw returns7See eg Basu (1997) Ball (2001) and Ball Kothari and Robin (2000)
7
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
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Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
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22
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of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
French (1988 1989)) The dividend yield predicts returns Its predictive power increases over the
long term The adjusted R2 for the 10-year horizon returns is increasing to 55 This result is very
similar to the results reported in Fama and French (1988) The coefficient on the dividend-price
ratio increases with horizon as well
The relation between short and long-term predictability can be interpreted by the following two
assumptions
Rt+1 = a middotDPt + ε1t+1 (3)
and
DPt+1 = ρ middotDPt + ε2t+1 (4)
Cochrane (2001) shows that these assumptions (where ρ asymp 1) imply both the increase in the
coefficient and the increase in R2 over longer horizons The coefficients on the dividend yield are
all positive implying that low prices are associated with high expected returns
While the dividend-price ratio predicts returns it does not predict future dividend growth The
coefficients on the dividend yield are statistically insignificant for all horizons and their sign changes
for different horizons Moreover the adjusted R2 for all horizons is negative
31 Predictability of Earnings
To summarize up to this point the dividend yield predicts returns but not dividend growth This
lack of dividend predictability led the finance literature to conclude that expected returns are the
main cause for aggregate price movements Although the dividend-price ratio does not predict
dividend growth it may contain information about expected cash flow through other measures
such as accounting earnings In fact as discussed above investors should be more interested in
measures of free cash flow or their portfoliorsquos ability to distribute dividends than actual dividends
which represent financing decisions
To test whether the dividend yield predicts earnings growth the following two regression models
were estimated for 1-10 year horizons
8
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Et+iEt = δ0 + δ1 middotDPt + ηt+1 (5)
and
EtDt
Et+iDt+i= δ0 + δ1 middotDPt + ηt+1 (6)
Table 3 reports the results of OLS estimation of the above two equations8 Notice that (Et+iEt) middot
[(EtDt) (Et+iDt+1)] = Dt+iDt Thus the information about dividend growth can be expressed
as information about expected earnings growth and information about the expected earnings-
dividend ratio9 This decomposition is not specific for accounting earnings Dividend growth
can be expressed as Dt+iDt = (Xt+iXt) middot [(XtDt) (Xt+iDt+1)] for any X However the use
of accounting earnings is not arbitrary Earnings is the most appropriate measure and predictor of
cash flows
The results reported in Table 3 appear to confirm the hypothesis that the dividend yield contains
information about cash flows in terms of earnings The dividend yield seems to be predicting long-
term earnings growth especially at the 6-year horizon and longer This result is consistent with the
conservative nature of accounting Economic gains are not recorded in a timely fashion Economic
growth at period t would result in earnings increases as much as ten years later The patterns of
predictability are similar to those of the returns predictability reported in Table 2 The coefficient
on the dividend yield increases in absolute value with the horizon as does the R2
The results in Table 3 for the estimation of Equation (6) are consistent with expected dividend
smoothing While the dividend yield predicts future earnings growth it also predicts changes in
the earnings-dividend ratio The change in earnings-dividend ratio is also predictable in the long-
term and it offsets the effects of expected earnings growth The results suggest that an increase in
expected profitability is associated with an expected decline in the dividend-earnings ratio In other
words dividends do not vary as strongly as earnings and an expected earnings increase does not
8Equation 5 was also estimated using real earnings growth (deflated by GDP deflator) The results do not change
qualitatively9 It is also possible to include profitability using the Clean Surplus Relation (eg Ohlson (1995) Feltham and
Ohlson (1995) and Vuolteenaho (2000)) However as Lo and Lys (1999) points out accounting rules violate the clean
surplus relation and this relation is not necessarily related to accounting Lo and Lys state that either the book value
or earnings can be chosen arbitrarily and still satisfy the Clean Surplus Relation
9
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
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Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
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56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
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Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
imply an equivalent expectation for a dividend increase Since (Et+iEt)middot [(EtDt) (Et+iDt+i)] =
Dt+iDt this result is consistent with the inability of the dividend yield to predict future dividend
growth Hence the market anticipates dividend smoothing
32 Understanding the Lack of Dividend Predictability
The results in Figure 1 summarize and illustrate the relation between earnings growth expected
dividend-earnings ratio and the expectations for future dividend growth The figure plots the
expected earnings growth and expected dividend-earnings ratio from estimating
ln (Et+iEt) = δ0 + δ1 middot ln (DPt) + ηt+1 (7)
and
ln (Et+iDtEtDt+i) = δ0 + δ1 middot ln (DPt) + ηt+1 (8)
The implied expected log dividend growth is the sum of the predicted values from the above
regression model Since E (xy) 6= E (x)E (y) Figure 1 uses logs to make use of the property of
expectations E (x+ y) = E (x) +E (y) to calculate the implied log dividend growth rate
Notice that while there is an increase in expected earnings growth the expected dividend-
earnings ratio declines The resulting implied dividend growth is very weak There are two different
interpretations for this result First it is possible that the dividend yield predicts dividend growth
in the very long-horizon Second it is possible that the dividend smoothness is endogenous
- implying that dividend growth might be unpredictable10 Since some recent studies find some
evidence of dividend predictability the first interpretation ie dividend yield predicts dividends
only in the very long horizon is more likely The results show that firms are expected to keep
reserves when earnings are high and use them when earnings are low resulting in smooth dividends
To understand the lack of dividend predictability consider the following equations
∆10et+10 = a middot dpt + t+10 (9)
∆10(dminus e)t+10 = b middot dpt + ςt+10 (10)
10Apart from exogenous shocks such as recessions (see Section 41)
10
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
dpt+1 = ρ middot dpt + ψt+1 (11)
where ∆ixt+i = xt+i minus xt for all x i et = ln(Et) (d minus e)t = ln (EtDt+iEt+iDt) and dpt =
ln (DPt)
Since Figure 1 shows that the implied dividend growth appears only over the long term the
analysis begins with long-term predictability of earnings growth (ten years) Equation (11) implies
that
dpt+10 = ρ10 middot dpt + error (12)
and for the log dividend growth ∆10dt+10 Equations (9) and (10) imply that
∆10dt+10 = (a+ b) middot dpt + error (13)
Using Equations (12) and (13) the implied long-term dividend growth is given by
∆10middotidt+10middoti =h(a+ b) + ρ10 (a+ b) + + ρ10middot(iminus1) (a+ b)
imiddot dpt + error (14)
for all i The results for Equations (9) and (10) not reported are a = minus084 b = 076 and
ρ = 096 Therefore a + b = minus008 Note that the implied dividend growth is very low The
following table reports the implied dividend growth given these results
i Implied Dividend Growth Coefficient
1 -008
2 -013
3 -017
4 -019
The table above represents the lack of dividend predictability Since earnings growth is only
predictable in the long-term about five years ahead horizon and longer dividends are unpredictable
in longer horizons In fact the table shows that the implied 40-year-ahead horizon dividend growth
coefficient is only -019 The table implies that to find dividend predictability using the dividend
yield one must use very long-term tests Such a test is not feasible with the available data and
11
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
long horizon tests might be unreliable In sum earnings are more timely than dividends and they
provide a better measure for cash flows than dividends
33 A Variance Decomposition Approach
The variance decomposition approach follows the work of Campbell and Shiller (1988a)11 who
decompose the variance of the dividend-price ratio to two major components expected returns and
expected dividend growth12 This approach contributes by estimating how variation in expected
profitability affects the dividend yield (economic significance) In other words the method tests
how much of the variation in the dividend-price ratio is attributable to information about expected
profitability For brevity this paper provides only the key steps Note
Rt+1 = (Pt+1 +Dt+1) Pt (15)
Equation (15) can be rewritten so that the price-dividend ratio can be written as
PtDt
= Rminus1t+1
micro1 +
Pt+1Dt+1
paraDt+1
Dt(16)
Taking natural logs yields
pt minus dt = minusrt+1 +∆dt+1 + lnsup31 + ept+1minusdt+1
acute(17)
The lowercase letter denotes the natural log and ∆dt+1 = dt+1 minus dt Taking a Taylor expansion of
the last term yields
pt minus dt = minusrt+1 +∆dt+1 + const+ ρ (pt+1 minus dt+1) (18)
where ρ = 1 (1 +DP ) asymp 096 Notice in Table 1 Panel B that the average dividend-price ratio is
approximately 4 Iterating forward and assuming that limjrarrinfin ρj (pt+j minus dt+j) = 0 results in the
following expression
dt minus pt = const+EinfinXj=1
ρjminus1 (rt+j minus∆dt+j) (19)
11For a similar but different approach see Cochrane (1991)12See also Cochrane (2001)
12
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Equation (18) implies that the variance of the dividend yield can be decomposed into two parts
predictability of returns and dividend predictability
var (dt minus pt) = cov
⎛⎝dt minus ptinfinXj=1
ρjminus1rt+j
⎞⎠minus cov
⎛⎝dt minus ptinfinXj=1
ρjminus1∆dt+j
⎞⎠ (20)
Table 4 reports the results for the estimation of Equation (20) Most of the variation in the
dividend-price ratio is due to variation in expected returns (about 122)13 On the other hand
dividend growth variation does not generate variation in the dividend-price ratio These results are
consistent with previous findings (eg Campbell and Shiller (1988a) and Cochrane (2001)) and the
results in Table 2 When cash flow information is restricted to dividend growth this result suggests
that the dividend yield does not contain much information about cash flows
Equation (19) can be modified slightly to include other sources of information about cash flow
Notice as before that ∆dt+j = ∆xt+jminus∆ (xt+j minus dt+j) for any x This paper focuses on one source
of cash flow information accounting earnings (denoted by E and e = ln (E)) Equation (19) can
be written as
dt minus pt = const+Et
infinXj=1
ρjminus1 [rt+j minus (∆et+j minus∆ (et+j minus dt+j))] (21)
The corresponding variance decomposition can be decomposed into three factors returns pre-
dictability earnings predictability and earnings-dividend ratio predictability The sum of the last
two parts is the dividend growth The variance decomposition is then decomposed further into the
same three factors and with additional decomposition for different horizons one through five and
six through ten periods ahead14
The GMM estimator is the covariance13Expected returns variation explains 132 of the variation when using excess returns14The decomposition into 1-5 and 6-10 year horizons is due to the results in Table 6 The long run (6 years and
longer) earnings growth seems more predictable than the shorter horizon
13
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
var (dt minus pt) = cov
⎛⎝dt minus pt5X
j=1
ρjminus1rt+j
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1rt+j
⎞⎠ (22)
minuscov
⎛⎝dt minus pt5X
j=1
ρjminus1∆et+j
⎞⎠minus cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆et+j
⎞⎠+cov
⎛⎝dt minus pt5X
j=1
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ cov
⎛⎝dt minus pt10Xj=6
ρjminus1∆ (et+j minus dt+j)
⎞⎠+ρ10cov (dt minus pt dt+11 minus pt+11)
Table 4 reports the results from estimating Equation (22) The results are consistent with the
results reported in Table 3 The dividend yield reflects expectations for earnings and earnings-
dividend ratio As much as 70 of the dividend yield variation is due to earnings growth variation
In the infinite horizon equation Equation (19) we can replace dividends with earnings because
they are the same Also the infinite horizon dividend earnings ratio is equal to 1 Therefore in
long horizon tests it does not matter whether we use dividends or earnings However the results
in Table 4 indicates that in short horizon tests profitability is a more timely measure of cash flows
and changes in expected profitability are priced On the other hand short-term dividend variation
is not reflected in prices
34 The Determinants of the Dividend Yield
The analysis below provides additional inferences on whether dividends or earnings determine
the equilibrium dividend yield To simplify the analysis denote Rlowastt equivP10
j=1 ρjminus1rt+j Elowastt equivP10
j=1 ρjminus1∆et+j EDlowastt equiv
P10j=1 ρ
jminus1∆(e minus d)t+j and Dlowastt equivP10
j=1 ρjminus1∆dt+j Table 5 reports the
correlations between these variables The dividend yield is highly correlated with both expected
profitability growth (-07) and expected returns (085) On the other hand expected dividend
growth does seem to be correlated with the dividend yield
The apparent strong correlation between earnings growth and returns is not surprising First
investorsrsquo preferences of holding risk varies with business conditions Second expected profitability
is expected to vary with business conditions For example expected returns are high in recessions
On the other hand expected profitability is low in recessions Note that this result does not contra-
dict previous findings that unexpected earnings are positively associated with positive unexpected
14
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
returns (eg Ball and Brown (1968))
An additional method of testing different determinants of the dividend yield is a simple regres-
sion analysis15 In particular Table 6 uses the following regression model
dt minus pt = δ0 + δ1Rlowastt + δ2E
lowastt + δ3D
lowastt + δ4ρ
10(dminus p)t+11 + ζt (23)
The results in Table 6 are consistent with the hypothesis that the dividend yield is determined by
expected earnings growth and not dividend growth The coefficient on expected profitability growth
is negative and statistically significant for all model specifications The coefficient on dividend
growth is not statistically significant in any of the specifications Moreover the adjusted R2 for
the regression including earnings alone is 05 compared to -002 for dividends In sum the results
in Table 6 are consistent with the hypothesis that expected earnings growth and expected returns
determine the equilibrium aggregate dividend-price ratio
The results in Tables 2 3 and 5 point to the strong relation between expected returns and
expected earnings Since the same variable (the dividend yield) predicts both earnings and returns
(Tables 2 and 3) the two are not independent and in fact they are highly correlated (Table 5)
Expected returns include a large cash flow component as reflected by earnings (notice that Rlowastt is
highly correlated with Elowastt ) These results suggest that variations in expected returns are due in
part to variations in expected earnings growth
Given the results in Tables 2 3 and 5 the determinants of the dividend yield were decomposed
into two orthogonal factors of expected returns and expected cash flows for both earnings and
dividends Since expected returns include both a cash flow component and an expected returns
component the expected returns determinant was decomposed into returns orthogonal to cash
flows as follows
Rlowastt = ϕ0 + ϕ1Dlowastt + υDt (24)
was estimated for dividends and
Rlowastt = ϕ0 + ϕ1Elowastt + υEt (25)
15Kothari and Shanken (1992) use a similar regression analysis using dividends
15
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
References
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dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
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Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
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Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
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of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
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equity capital The Accounting Review 79 (1) 73-95
21
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of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
for earnings
Consider the following linear model of the dividend yield
dt minus pt = bX0 + bX1 Xlowastt + bX2 υ
Xt + ζXt (26)
for X = E and D The variance of the dividend yield can then be decomposed into
V ar (dt minus pt) =iexclbX1cent2V ar (Xlowast
t ) +iexclbX2cent2V ar
iexclυXtcent+ V ar
iexclζXtcent
(27)
Table 7 reports estimation results for Equations (26) and (27) The results support the hypoth-
esis that the equilibrium dividend yield is determined in part by cash flow information as reflected
by earnings However the dividend yield does not seem to be affected by expectations of future
dividend growth Moreover the results indicate that expected returns themselves contain informa-
tion about future cash flows The adjusted R2 is similar when using dividends and earnings That
is the expectations of returns contain information about expectations of cash flows16 as reflected
by earnings For instance Table 5 shows a very high correlation between long term returns and
long term earnings17 Table 7 also shows that expected earnings growth explains as much as 50
of the variation in the dividend yield compared to only 1 that dividends explain
4 Additional Considerations
This section provides some additional tests and results related to the dividend yield The evidence
explored in this section is consistent with a permanent decline in the dividend yield during the
1990s Controlling for this shift restores the predictive power of the dividend yield with respect
to expected returns This section also explores some additional related issues such as raw returns
versus excess returns and the information content of dividend growth with respect to earnings and
returns16See Menzly et al (2004)17See Easton Harris and Ohlson (1992)
16
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
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nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
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of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
41 The Dividend Yield in the 1990s
Previous studies (eg Lettau and Ludvigson (2004)) find that the dividend yield lost its predictive
power with respect to returns in the 1990s and is lower than its past mean This finding suggests
that one of the following is true First it is possible that the dividend yield is not as informative
about expected returns as suggested by prior research Second it is possible that the dividend
yield will increase to its past mean due to either higher dividends andor lower returns Finally
it is possible that the dividend yield has declined to a new lower equilibrium stationary level The
following test supports the latter interpretation of the results Controlling for a permanent shift
in the dividend yield it seems that the dividend yield is highly informative about expected excess
returns (including the 1990s) and it did not lose its predictive power
To control for a permanent shift in the dividend yield the following regression model was used
DPt = δ0 + δ1 middotDUM90s+ τ t (28)
where DUM90s is an indicator variable that receives the value of 1 if the year is greater than or
equal to 1990 and zero otherwise The results (not reported) suggest that the dividend yield shifted
in the 1990s δ1 = minus0016 and is statistically significant To test whether the dividend yield has
maintained its ability to predict excess returns and earnings growth Table 8 reports results for the
following regression models
Rtminusrarrt+i = δ0 + δ1 middot τ t + ηt+1 (29)
and
Et+iEt = δ0 + δ1 middot τ t + ηt+1 (30)
The results are consistent with a permanent shift in the dividend yield The results suggest that
the dividend yield did not loose its ability to predict excess returns and earnings growth in the
1990s The results are also stronger compared to Tables 2 and 3 For example the adjusted R2 for
the one-year-ahead horizon predicting regression (for expected excess returns) is around 1018
18Notice that Tables 4-7 are not affected by the permanent shift Since the tests use 10 year horizon returns and
earnings the dividend yields during the 1990s are mostly excluded
17
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
References
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Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77
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Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37
Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340
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Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560
Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance
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dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of
Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
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prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of
Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal
of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on
equity capital The Accounting Review 79 (1) 73-95
21
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
411 Why Has the Dividend Yield Declined
The dividend yield seems to have declined during the 1990s This result is consistent with Fama and
French (2001) Fama and French find that fewer firms pay cash dividends The main reason for the
decline in dividends is the change in the firmsrsquo characteristics The number of small firms with low
earnings and high growth opportunities has increased significantly in the 1990s Moreover they find
that firms are less likely to pay dividends even when controlling for the change in characteristics
In the 1990s many firms engaged in RampD activities and stock markets were used more extensively
in financing such projects These projects are high growth projects with low short-term cash flows
resulting in a lower dividends and high prices ie a new lower equilibrium market dividend-price
ratio
42 An Impulse Response Function
Another method of illustrating the point presented in Figure 1 is using an impulse response function
In particular using the following set of equations to illustrate the effects of a shock to the dividend
yield until it converges back to its equilibrium level
DPt+1 = ρ middotDPt + ε1t+1 (31)
Rt+1 = a middotDPt + ε2t+1 (32)
Et+iEt = b middotDPt + ε3t+1 (33)
and
EtDt
Et+iDt+i= c middotDPt + ε4t+1 (34)
Unfortunately Table 3 shows that the predictability in the dividendsearnings ratio begins at
the two year horizon The coefficient on the one-year-ahead horizon is negative Therefore it is
necessary to extract a more appropriate estimate for c Since (EtDt) (Et+2Dt+2) = (c+ ρ middot c) middot
DPt + ε4t+2 the figure uses the two-year-horizon regression to extract c
18
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
References
Ball Ray 2001 Infrastructure Requirements for an economically efficient system of public financialreporting and disclosure Brookings - Wharton Papers on Financial Services
Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77
Ball Ray and Philip Brown 1968 An empirical evaluation of accounting income numbers Journal ofAccounting Research 6 159-178
Ball Ray SP Kothari and Ashok Robin 2000 The effect of international institutional factors onproperties of accounting earnings Journal of Accounting and Economics 29 1-51
Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37
Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340
Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28
Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560
Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance
decomposition for long-term asset returns Journal of Finance 48 3-37Campbell John Y and Robert J Shiller 1988a The dividend-price ratio and expectations of future
dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of
Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of
prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of
Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal
of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on
equity capital The Accounting Review 79 (1) 73-95
21
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
The impulse response function is plotted in Figure 2 The pattern in this figure is consistent
with Figure 1 A positive shock to the dividend yield results in higher future returns lower earnings
and higher dividendsearnings ratio Notice that the effect on earnings growth is higher than the
expected effect on the dividendsearnings ratio implying long-term dividend decline
43 The Information Content of Dividend Growth
Previous work such as Healy and Palepu (1988) and Nissim and Ziv (2001) shows that dividends
can provide information about future profitability To test the implications of the predictive power
of dividend increases for future profitability the following model was estimated
Et+iEt = δ0 + δ1 middotDPt + δ2 middotDtDtminus1 + ηt+1 (35)
The model was estimated including and excluding the dividend yield The results (not reported) are
not consistent with dividend growth predicting future profitability growth δ2 is generally negative
and is mostly not statistically significant In other words on the aggregate level dividend growth
does not seem to signal profitability growth This result suggests that the information content of
the dividend yield with respect to earnings is generated mostly from the denominator (ie prices)
44 Raw Returns versus Excess Returns
The results in Tables 2 and 3 are estimated using excess returns (in excess of the risk-free rate)
These tests were replicated using raw returns The results do not vary qualitatively The paper
chose excess returns to show that there are time-varying risk premiums However the variance
decomposition approach requires the use of raw returns When Table 4 is estimated using excess
returns the sum of the decomposition-components does not add up to 100 Therefore Table 4
utilizes the raw returns For the same reason Tables 5-7 use raw returns as well
5 Conclusion
The paper investigates the implications of accounting profitability for the information content of the
dividend-price ratio Previous studies suggest that the dividend yield does not contain information
about cash flows ie the dividend yield does not predict dividend growth However the results
19
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
References
Ball Ray 2001 Infrastructure Requirements for an economically efficient system of public financialreporting and disclosure Brookings - Wharton Papers on Financial Services
Ball Ray and Philip Brown 1967 Some preliminary findings on the association between the earnings ofa firm its industry and the economy Journal of Accounting Research 5 55-77
Ball Ray and Philip Brown 1968 An empirical evaluation of accounting income numbers Journal ofAccounting Research 6 159-178
Ball Ray SP Kothari and Ashok Robin 2000 The effect of international institutional factors onproperties of accounting earnings Journal of Accounting and Economics 29 1-51
Basu S 1997 The conservatism principle and the asymmetric timeliness of earnings Journal of Ac-counting and Economics 24 3-37
Beaver William H Roger Clarke William F Wright 1979 The information content of security pricesJournal of Accounting and Economics 17 316-340
Beaver William H Richard Lambert and Dale Morse 1980The information content of security pricesJournal of Accounting and Economics 2 3-28
Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560
Campbell John Y 1991 A variance decomposition for stock returns Economic Journal 101 157-179Campbell John Y and John Ammer 1993 What moves the stock and bond markets A variance
decomposition for long-term asset returns Journal of Finance 48 3-37Campbell John Y and Robert J Shiller 1988a The dividend-price ratio and expectations of future
dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of
Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of
prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of
Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal
of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on
equity capital The Accounting Review 79 (1) 73-95
21
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
presented in this paper are consistent with predictability of accounting profitability These results
suggest that the cash flow information embedded in the dividend-price ratio shows up in terms
of profitability growth (free cash flow) and not dividend growth Although it is unlikely that
dividend policy is irrelevant as suggested by Miller and Modigliani (1961) it seems that on the
aggregate level investors are more interested in measures of free cash flow than dividends The
dividend growth is much smoother less predictable and much less timely than earnings Thus
especially for short horizons such as ten to 15 years ahead (the horizon commonly used in the
literature) earnings rather than dividends are more appropriate and are likely to provide more
insight on the information embedded in prices
As an approximation over the life of the firm earnings and dividends are the same However
it is unclear how long it takes for a profitability shock to translate into dividends Long-term
dividend growth is affected by many different profitability shocks and might be difficult to predict
For example a $100 profitability shock in any year might translate into a $4 dividend shock for
25 years which would be difficult to detect in the data particularly given other past and future
profitability shocks In fact the paper shows that the implied 40-year ahead horizon dividend
growth as reflected in the dividend yield is relatively weak
This paper also shows that expected returns contain a significant cash flow component Since
the dividend yield predicts both profitability and returns the two cannot be independent This
means that variation in the dividend yield due to expectations of returns also reflects variation in
expected profitability
20
References
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Callen Jeffrey L and Dan Segal 2004 Do accruals drive stock returns a variance decompositionanalysis Journal of Accounting Research 42 527-560
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dividends and discount factors Review of Financial Studies 1 195-227Campbell John Y and Robert J Shiller 1988b Stock prices earnings and expected dividends The
Journal of Finance 43 661-676Cochrane John H 1991 Explaining the variance of price-dividend ratios Review of Financial Studies
5 243-280Cochrane John H 2001 Asset pricing Princeton PressCohen Randolph B Christopher Polk and Tuomo Vuolteenaho 2003 The value spread Journal of
Finance 58 609-641Collins Daniel W SP Kothari 1989 An analysis of intertemporal and cross-sectional determinants of
earnings response coefficients Journal of Accounting and Economics 11 143-181Collins Daniel W SP Kothari and Judy D Rayburn 1987 Firm size and the information content of
prices with respect to earnings Journal of Accounting and Economics 9 111-138DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1992 Dividends and losses Journal of
Finance 47 (5) 1837-1863DeAngelo Harry Linda DeAngelo and Douglas J Skinner 1996 Reversal of fortune dividend signaling
and the disappearance of sustained earnings growth Journal of Financial Economics 40 341-371Dechow Patricia 1994 Accounting earnings and cash flows as measures of firm performance Journal
of Accounting and Economics 18 3-42Dechow Patricia SP Kothari and Ross L Watts 1998 The relation between earnings and cash flows
Journal of Accounting and Economics 25 133-168Easton Peter D 2004 PE ratios PEG ratios and estimating the implied expected rate of return on
equity capital The Accounting Review 79 (1) 73-95
21
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
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23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Easton Peter D Trevor S Harris and James A Ohlson 1992 Aggregate accounting earnings canexplain most of security returns The case of long returns intervals Journal of Accounting andEconomics15 119-143
Ertimur Yonca 2003 Financial information environment of loss firms Working Paper New York Uni-versity
Fama Eugene F and Kenneth R French 1988 Dividend yields and expected stock returns Journal ofFinancial Economics 22 3-25
Fama Eugene F and Kenneth R French 1989 Business conditions and expected returns on stocks andbonds Journal of Financial Economics 25 23-49
Fama Eugene F and Kenneth R French 1993 Common risk factors in the returns on stocks andbonds Journal of Financial Economics 33 3-56
Fama Eugene F and Kenneth R French 2001 Disappearing dividends changing firm characteristicsor lower propensity to pay Journal of Financial Economics 60 3-43
Fama Eugene F and James MacBeth 1973 Risk return and equilibrium empirical tests Journal ofPolitical Economy 81 607-636
Feltham Gerald A and James A Ohlson 1995 Valuation and clean surplus accounting for operatingand financial activities Contemporary Accounting Research 11 689-731
Francis Jennifer J Douglas Hanna and Linda Vincent 1996 Causes and effects of discretionary assetwrite-offs Journal of Accounting Research 34
Healy Paul M and Krishna G Palepu 1988 Earnings information conveyed by dividend initiation andomissions Journal of Financial Economics 21 149-175
Korajczyk Robert A and Amnon Levy 2003 Capital structure choice macroeconomic conditions andfinancial constraints Journal of Financial Economics 68 75-109
Kothari SP and Jay Shanken 1992 Stock return variation and expected dividends Journal of FinancialEconomics 31 177-210
Kothari SP and Jay Shanken 1997 Book-to-market dividend yield and expected market return atime-series analysis Journal of Financial Economics 44 169-203
Kothari SP and Richard G Sloan 1992 Information in prices about future earnings implications forearnings response coefficients Journal of Accounting and Economics 15 143-171
Lamont Owen 1998 Earnings and expected returns Journal of Finance 53 1563-1587Lettau Martin and Sydney C Ludvigson 2001 Resurrecting the (C) CAPM a cross-sectional test
when risk premia are time-varying Journal of Political Economy 109 1238-1287Lettau Martin and Sydney C Ludvigson 2004 Expected returns and expected dividend growth Jour-
nal of Financial Economics forthcomingLo Kin and Thomas Lys 1999 The Ohlson model contribution to valuation theory limitations and
empirical applications Journal of Accounting Auditing amp Finance 337-367Menzly Lior Tano Santos and Pietro Veronesi 2004 Understanding predictability Journal of Political
Economy 112 1-47Miller MH and F Modigliani 1961 Dividend policy growth and the valuation of shares Journal of
Business 34 411-433Nissim Doron and Amir Ziv 2001 Dividend changes and future profitability The Journal of Finance
56 2111-2134Ohlson James A 1995 Earnings book values and dividends in security valuation Contemporary
Accounting Research 11 661-687Paacutestor Lubos and Pietro Veronesi 2003 Stock valuation and learnings about profitability Journal of
Finance 58 1749-1790
22
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Paacutestor Lubos and Pietro Veronesi 2004 Rational IPO wave Forthcoming - Journal of FinancePenman Stephen H and Nir Yehuda 2004 The pricing of earnings and cash flows and an affirmation
of accrual accounting Working Paper - Columbia UniversityRibeiro Ruy M 2002 Predictable dividends and returns Working Paper - University of ChicagoSadka Gil and Ronnie Sadka 2003 The post-earnings-announcement-drift and liquidity risk Working
Paper - University of ChicagoVuolteenaho Tuomo 2000 Understanding the aggregate book-to-market ratio and its implications to
current equity-premium expectations working paper - Harvard UniversityVuolteenaho Tuomo 2002 What drives firm-level stock returns Journal of Finance 57 233-264Watts Ross L 1973 The information content of dividends The Journal of Business 46 191-211
23
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
-2
-15
-1
-05
0
05
1
15
2
25
1 2 3 4 5 6 7 8 9 10
Dividends-Earnings Ratio Earnings Dividends
Figure 1 Expected Earnings Earnings-Dividend ratio and Implied Dividend Growth This figure plots the expected earnings growth the expected change in the dividend-earnings ratio and the implied expected dividend growth The marketrsquos expectation is estimated for a one-standard-deviation decline in the log dividend-price ratio The plot is based on predicted values based on the regressions ln∆Et+i =α+βln(DPt )+εt+i and (ln∆Dt+i- ln∆Et+i )=α+βln(DPt )+εt+i Expected dividend growth is the sum of the expected earnings growth and expected dividend payout i denotes the horizon
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
DP Returns Earnigns Growth Growth in EarningsDividends
Figure 2 Impulse Response Function The figure plots the impulse response function of the following set of equations DPt+1=ρDPt+ε1t Et+1Et=ρDPt+ε2t Rtrarrt+1=ρDPt+ε3t (ED)t+1(ED)t=ρDPt+ε4t The figure plots the response to a one standard deviation increase in the dividend yield
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
DPtMean 0039
Median 0037Standard Deviation 0012
Rtrarrt+1 Rtrarrt+2 Rtrarrt+3 Rtrarrt+4 Rtrarrt+5 Rtrarrt+10Mean 0076 0158 0148 0347 0438 0897
Median 0077 0127 0117 0294 0348 0865Standard Deviation 0156 0218 0229 0369 0449 0838
Dt+1Dt Dt+2Dt Dt+3Dt Dt+4Dt Dt+5Dt Dt+10DtMean 1069 1124 1182 1246 1315 1722
Median 1047 1111 1149 1247 1300 1675Standard Deviation 0166 0176 0191 0193 0218 0349
Et+1Et Et+2Et Et+3Et Et+4Et Et+5Et Et+10EtMean 1102 1202 1313 1445 1586 2472
Median 1121 1229 1277 1438 1628 2465Standard Deviation 0131 0246 0332 0390 0441 0662
(DtEt)(Dt+1Et+1) (DtEt)(Dt+2Et+2) (DtEt)(Dt+3Et+3) (DtEt)(Dt+4Et+4) (DtEt)(Dt+5Et+5) (DtEt)(Dt+10Et+10)Mean 0978 0948 0918 0877 0847 0736
Median 0961 0912 0865 0855 0826 0689Standard Deviation 0165 0212 0228 0203 0206 0252
Value-Weighted Market Index
Table 1Summary Statistics
The table reports the mean median and the standard deviation for selected variables Rtrarrt+i is the cumulative annual excess return from April year t+1till March year t+1+i Dt+iDt is the change in dividends during the period beginning in April year t+1 till March year t+1+i DPt is the dividend-price ratio at time t The table reports summary statistics for value weighted index Eit is measured as the sum of the fiscal year earnings of all firms in thesample The sample includes all firms in the CRSP and COMPUSTAT annual databases for the period 1952 ndash 2001 with fiscal year ending in December
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Rtrarrt+1 -0064 3600 0058-084 191 -
Rtrarrt+2 -0047 5198 0056-032 148 -
Rtrarrt+3 -0107 6378 0076-075 167 -
Rtrarrt+4 -0176 12892 0122-046 149 -
Rtrarrt+5 -0360 19484 0191-071 172 -
Rtrarrt+10 -1691 61140 0552-284 413 -
Dt+1Dt 1136 -1888 -00011298 -088 -
Dt+2Dt 1166 -1072 -00151939 -071 -
Dt+3Dt 1174 0217 -00211314 010 -
Dt+4Dt 1228 0450 -00211228 019 -
Dt+5Dt 1255 1473 -00171211 065 -
Dt+10Dt 1828 -2521 -0019903 -071 -
Table 2Predicting Returns and Dividends with the Dividend-Price Ratio
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Dt+iDt= δ0 + δ1DPt + εt+i and Rtrarrt+i= δ0 + δ1DPt + εt+i Dt+iDt is the cumulative annual change in dividends during the periodApril year t+1 till March year t+1+i DPt is the dividend-price ratio (value-weighted) at time t Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databasesduring the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept DPt R2
Et+1Et 1193 -2344 00262277 -188 -
Et+2Et 1223 -0549 -0020724 -015 -
Et+3Et 1293 0498 -0021468 008 -
Et+4Et 1532 -2194 -0017424 -028 -
Et+5Et 1807 -5495 -0002439 -062 -
Et+6Et 2195 -11226 0037555 -134 -
Et+7Et 2689 -19099 0112706 -233 -
Et+8Et 3265 -28619 0215747 -293 -
Et+9Et 3640 -32743 0250684 -263 -
Et+10Et 4028 -37169 0317667 -265 -
(DtEt)(Dt+1Et+1) 1011 -0840 -00171108 -040 -
(DtEt)(Dt+2Et+2) 0865 2110 -0008921 091 -
(DtEt)(Dt+3Et+3) 0775 3554 0009552 108 -
(DtEt)(Dt+4Et+4) 0641 5811 0075416 154 -
(DtEt)(Dt+5Et+5) 0538 7550 0130324 182 -
(DtEt)(Dt+6Et+6) 0402 10273 0169251 254 -
(DtEt)(Dt+7Et+7) 0279 12547 0203141 244 -
(DtEt)(Dt+8Et+8) 0204 13671 0252087 220 -
(DtEt)(Dt+9Et+9) 0166 13959 0302069 214 -
(DtEt)(Dt+10Et+10) 0183 13063 0266078 205 -
Table 3Predicting Earnings and Earnings-Dividends Ratio with the Dividend-Price Ratio
The table reports results for the following regression models Et+iEt= δ0 + δ1DPt + εt+i and (EtDt ) (Et+iDt+i) = δ0 + δ1DPt + εt+i Et+iEt is the change in earnings from year t to year t+i DPt is the dividend-price ratio (value-weighted) at time t (EtDt ) (Et+iDt+i) denotes the cumulative annual change in the earnings-dividends ratio from year t to year t+i The sample includes all firms in the CRSP and COMPUSTAT annual database during the period 1952 ndash2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Var(d t -p t ) 0053 0053 005310000 10000 10000
Cov(d t -p t sumρ j-1 ∆d t+j ) years 1-10 -0003-658(719)
Cov(d t -p t sumρ j-1 r t+j ) years 1-10 0065 006512371 12371(1866) (1866)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-10 -0037-7062(2134)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-10 00346404(2424)
Cov(d t -p t sumρ j-1 r t+j ) years 1-5 00468708(1140)
Cov(d t -p t sumρ j-1 r t+j ) years 6-10 00193663(1873)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 1-5 -0016-2977(1354)
Cov(d t -p t sumρ j-1 ∆e t+j ) years 6-10 -0022-4085(1193)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 1-5 -00163044(1665)
Cov(d t -p t sumρ j-1 ∆(d-e) t+j ) years 6-10 00183360(1042)
Cov(d t -p t ρ j (d-p) t+j ) years 11- -0009 -0009 -0009-1730 -1730 -1730(1716) (1716) (1716)
Table 4Variance Decomposition for the Dividend-Price Ratio
The table reports the variance decomposition of the dividend-price ratio dt-pt=ln(DPt) where DPt is the value-weighted dividend yield at the end of year t (March year t+1) rt=ln(1+Rt) where Rt is the value-weighted market return for the period beginning at April year t ending at March year t+1 ∆dt+i= ln(Dt+iDt) where Dt denotes the dividends during year t measured from April year t-1 till March year t ∆(d-e)t+i=ln((Et+iDt+i) (EtDt)) where Etdenotes the yearly corporate earnings before extraordinary items during year t (April t-1 till March t) ∆et+i= ln(Et+iEt) ρasymp096 Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
d t -p t R t E
t ED t D
t ρ -11 (d-p) t+11
d t -p t 1
R t 08532 1
(0000)
E t -07055 -06922 1
(0000) (0000)
ED t -05493 -04849 07724 1
(00002) (00013) (0000)
D t -00881 -01707 01346 -05255 1
(0584) (02858) (04016) (00004)
ρ -11 (d-p) t+11 -01788 -04096 02263 -01214 04925 1(02634) (00078) (01548) (04497) (00011)
Table 5Correlation Matrix
The table reports the pairwise correlations for selected variables rt+i is the log annual returns from April year t+i-1till March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i(∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-
d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Dependant Variable Intercept R t E
t ED t D
t ρ -11 (d-p) t+11 adj-R2
d t -p t -313 -018 -002(3481) (-084)
d t -p t -266 -070 050(-2974) (-677)
d t -p t -266 -071 001 047(-2426) (-690) (012)
d t -p t -304 055 -020 004 021 076(-2058) (456) (-228) (030) (248)
d t -p t -303 055 -023 004 021 076(-2058) (456) (-242) (027) (248)
Table 6Regression Analysis
The table reports OLS coefficients and t-statistics below rt+i is the log annual returns for April year t+i-1 untill March year t+i ∆dt+i is the log change in dividends for the period April year t+i-1 untill March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-
1∆et+j Rt=sum1
10ρj-1rt+j Dt=sum1
10ρj-1∆dt+j EDt=sum1
10ρj-1∆(e-d)t+j The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001 with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Dependant Variable Intercept E t (b E
1 ) D t (b D
1 ) υ Et (b E
2 ) υ Dt (b D
2 ) adj-R2
d t -p t -314 -012 060 072(-2917) (-057) (696)
d t -p t -266 -070 048 074(-4222) (-999) (353)
Dependant Variable Total (b E1 ) 2 Var(E
t ) (b D1 ) 2 Var(D
t ) (b E2 ) 2 Var(υ E
t ) (b D2 ) 2 Var(υ D
t ) ErrorVar(d t -p t ) 0054 0000 0039 0015
(100) (1) (72) (27)
Var(d t -p t ) 0054 0027 0014 0013(100) (50) (26) (24)
Table 7Analysis of the Dividend Yield Variance
Panel A OLS results
Panel B Analysis of Variance
The table reports OLS coefficients and t-statistics bellow (Panel A) and an analysis of variance (Panel B) rt+i is the log annual returns from April year t+i-1 till March year t+i ∆dt+i is the log change in dividends from April year t+i-1 to March year t+i ∆et+i (∆(e-d)t+i) is the log change in earnings (earnings-dividends ratio) for the period April year t+i-1 untill March year t+i dt-pt is the log dividend price ratio at time t E
t=sum110ρj-1∆et+j R
t=sum110ρj-1rt+j D
t=sum110ρj-1∆dt+j ED
t=sum110ρj-1∆(e-d)t+j υX
t is estimated for X=E and X=D as follows R
t=φ0+ φ1Xt+ υX
t The sample includes all firms in the CRSP and COMPUSTAT annual database for the period 1952 ndash 2001with fiscal year ending in December Standard errors (Newey-West with 9 lags) for the percentage are reported below in parentheses
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2
Intercept τ t R2
Rtrarrt+1 0079 5188 0096381 285 -
Rtrarrt+2 0160 8705 0142466 249 -
Rtrarrt+3 0145 6469 0059377 146 -
Rtrarrt+4 0332 21780 0330473 387 -
Rtrarrt+5 0413 30316 0445476 423 -
Rtrarrt+10 0860 62809 0619520 507 -
Et+1Et 1103 -3318 00415929 -216 -
Et+2Et 1220 -3694 00073213 -131 -
Et+3Et 1348 -3651 -00062391 -114 -
Et+4Et 1462 -2717 -00171884 -056 -
Et+5Et 1588 -2902 -00171632 -043 -
Et+6Et 1746 -8558 00071674 -114 -
Et+7Et 1921 -16304 00661797 -197 -
Et+8Et 2107 -27129 01801983 -278 -
Et+9Et 2307 -33264 02532118 -286 -
Et+10Et 2505 -40690 03922239 -335 -
Table 8Predicting Returns and Earnings with the Dividend-Price Ratio Adjusted for Changes in the 90s
The table reports regression results for the following regression model Dt+iDt=α0i + δ1DPt + δ2β0t + δ3β1t + εt+i DPtis the dividend price ratio (equally weighted) at time t β0 β1 are the slopes form the following cross-sectional regressions EitPit-1=α0t + α1tDRitRit + β0tRit + β1tDRitRit + εit EitPit-1 notes the earnings per share (excluding extraordinary items) for firm i at time t scaled by the beginning period price Rit denotes the yearly returns measured from March year t till March at year t+1 DRit is a dummy variable which receives the value of 1 where Ritlt0 and 0 otherwise The sample includes all firms in the CRSP and COMPUSTAT annual database during the time period of 1952 - 2002
The table reports results for the following regression models Et+iEt= δ0 + δ1τt + εt+i and Rtrarrt+i= δ0 + δ1 τt + εt+i Et+iEt is the cumulative annual change in earnings during the period April year t+1 till March year t+1+i τtis estimated as follows DPt = δ0 + δ1DUM90s + τt DPt is the dividend-price ratio (value-weighted) at time t DUM90s is an indicator variable equal 1 for the period following 1990 and zero otherwise Rtrarrt+i denotes the cumulative annual excess returns measured from April year t+1 till March at year t+1+i The sample includes all firms in the CRSP and COMPUSTAT annual databases during the period 1952 ndash 2001 with fiscal year ending in December The table reports the coefficients and their corresponding (Newey-West with lag i-1) t-statistic (below) and the adjusted R2