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Marketable Securities: Storage or Investment?
August 21, 2013
Craig O. Brown*
NUS Business School
National University of Singapore
Abstract
Corporate liquidity demand models view investments in marketable securities as a relatively simple store of excess liquidity (the storage view). However, compared to excess cash, market investment has more in common with general investment and liability-driven investment. For firms with repatriation tax exposure, constrained to a limited payout and permanent foreign capital reinvestment, the average coefficient difference between excess cash and market investment regressions is zero. For all firms, the difference is 12%. The findings suggest that market investment is no longer a passive store of excess liquidity. Rather, market investment is associated with active general investment and liability-driven investment.
Keywords: Market Investment, Liability-Driven Investment, Payout Policy, International Taxation.
JEL Codes: G11 (Portfolios), G31 (Investment), G32 (Risk Management), G35 (Payout Policy)
* Craig O Brown, Department of Finance, NUS Business School, 15 Kent Ridge Drive, BIZ 1, #07-61 Mochtar
Riady Building, Singapore 119245. Phone: +65 6516-6815. Fax: +65 6779-2083. U.S. Phone: (213) 221-3582. Email: bizcb@nus.edu.sg. I am grateful to Turan Bali, Michael Faulkender, Jack Francis, Andra Ghent, Todd Gormley, Gerard Hoberg, Armen Hovakimian, Sheng Huang (NUS RMC discussant), Dirk Jenter, Anzhela Knyazeva, Diana Knyazeva, Ralph Koijen, Albert (Pete) Kyle, Vojislav Maksimovic, Nagpurnanand Prabhala, David Scharfstein, Lemma Senbet, Paolo Sodini, Per Strömberg, Heather Tookes, Bernard Yeung, and seminar participants at Baruch College, National University of Singapore, Nanyang Business School, the Stockholm School of Economics, HEC Lausanne, the University of Maryland (Smith), and the NUS Risk Management Conference for helpful comments.
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1. Introduction
The standard measure of corporate liquidity is heterogeneous1 and includes short-term
investments in marketable securities (or current market investment). Like corporate liquidity,
market investment (current and noncurrent) is substantial.2 In making investments, a growing
number of corporate managers are reaching for yield3 (Rajan, 2010; Becker and Ivashina, 2012)
and modern firms actively trade investment portfolios. For example, Google has its own trading
floor;4 and Apple’s dedicated subsidiary, Braeburn Capital,5 manages Apple’s liquid assets.
Contrary to the recent anecdotal evidence, money-demand research suggests that market
investment is a relatively simple store of excess cash.6 Moreover, this storage view is consistent
with all modern corporate liquidity management models that emphasize the role of managerial
agency costs (Jensen, 1986); the tax motive (Foley et al., 2007; Dharmapala, Foley, and Forbes,
2011); the precautionary motive and the role of financial constraints (Kaplan and Zingales,
1997). Does the modern firm conform to the passive storage view? Or are managers more active
when investing in marketable securities? Is market investment a simple store of excess cash? Or
do managers pursue investment goals when placing funds in marketable securities?
1 The measure consists of three components: physical currency (or cash) and cash equivalents, credit lines (Yun, 2009; Acharya, Almeida, and Campello, 2010; Campello et al., 2011; Lin, Servaes, and Tufano, 2010), and short-term investments in marketable securities. 2 Market investment, consisting of equity and debt securities, can constitute well over 30% of total assets for many nonfinancial corporations (or firms). When including noncurrent corporate market investment in the measure of liquid assets, it is not cash (42%) that constitutes the majority of liquid assets for firms that make market investments; it is corporate market investment (58%). This 58% consists of 28% noncurrent market investment and 30% current market investment. However, we know relatively little about marketable securities beyond our knowledge of overall corporate liquidity (Opler et al., 1999) and noncurrent market investment tied to strategic equity stakes (Allen and Phillips, 2000; Ouimet, 2013). 3Katy Burne, “Google Googles for Yield, Finds Auto Bonds,” The Wall Street Journal, August 7, 2012. 4 Douglas MacMillan, “Google’s Latest Launch: Its Own Trading Floor,” Bloomberg Businessweek, May 27, 2010. 5 Charles Duhigg and David Kocieniewski, “How Apple Sidesteps Billions in Taxes,” The New York Times, April 28, 2012. 6 Money-demand research suggests that corporate market investment is a simple substitute for cash (Selden, 1961; Maddala and Vogel, 1967; Jeffers and Kwon, 1969) or a store of excess cash (Miller and Orr, 1966, 1968). In fact, Miller and Orr (1968) “followed their (Baumol and his followers) precedents in assuming that earning assets are homogenous” and admittedly ignored “the importance that runoffs from the portfolio can have in cash balance management.”
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The storage view has roots in pre-1960 studies of corporate market investment (Chudson,
1945; Frazer, 1958), and should be qualified for modern firms given the change in investment
behavior over time. Prior to 1960, mostly “safe” investments (Krishnamurthy and Vissing-
Jorgensen, 2010; Gorton, Lewellen, and Metrick, 2012) were held by firms; firms held roughly
75% of their marketable securities in US Treasuries with approximately 67% of their marketable
securities maturing in one year or less (Jacobs, 1960). Over time however, managers of firms
have been investing less in short-term US Treasuries, and more in other types of securities
(Jacobs, 1960; Heston, 1962). Given these changes in investment scope, this paper examines the
storage view for the modern firm.
This paper presents two alternatives to the storage view. In doing so, this paper provides
a scientific basis for meaningful economic differences between excess cash and marketable
securities. The first alternative is that managers invest in marketable securities with goals similar
to those of capital investment (general investment). The general investment motive is consistent
with the speculative motive (Keynes, 1936), portfolio choice (Tobin, 1955), tax arbitrage (Scott,
1979), and agency costs7 (Jensen, 1986). The second alternative is that managers invest in
marketable securities to manage future financial commitments and promises. The practice is
commonly described as asset-liability management (ALM) or liability-driven investment8 (LDI)
(Miller and Orr, 1967; van Binsbergen and Brandt, 2009; Ang, Chen, and Sundaresan, 2012).
7 Although the general investment motive is consistent with an agency cost of free cash flow, this paper is the first paper to discuss modern-firm speculation with investments in marketable securities as opposed to speculation with capital investments or acquisitions. 8 Miller and Orr (1968), referring to their research on CFOs, argue that “in practice corporate financial officers may rely heavily on (portfolio) runoffs as a means of replenishing the firm’s cash balance (see Miller and Orr, 1967). The policy becomes oriented toward anticipation of heavy future requirements and the purchase of securities of a maturity to match these requirements in time. To the extent that cash flows are predictable in timing and magnitude, this kind of reliance on runoffs to meet cash needs may be economical.”
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This paper first shows that marketable securities are associated with variables that, given
the alternatives to the storage view, might not explain market investment and cash in the same
manner: variables related to payout policy, interest, and investment9 (PII).
In studying whether market investment is simply a store of excess cash, the appropriate
empirical method is not as straightforward as a single ordinary least squares (OLS) regression.
This paper first estimates excess cash, then uses coefficient differences10 between excess cash
regressions and market investment regressions (for PII variables).
To test the validity of this paper’s method, I use a natural experiment that focuses on
firms that are constrained to conform to the storage view: multinational corporations (MNCs)
that maintain liquidity offshore because of the taxes associated with repatriation. MNCs have the
flexibility to shift profits to low-tax locations (Harris et al., 1993; Hines and Rice, 1994; Desai,
Foley, and Hines, 2006). Moreover, MNC liquid profits can remain offshore and “trapped”
because of the taxes associated with repatriation (Foley et al., 2007). Trapped-liquidity firms are
typically constrained to hold excess cash as market investments in lieu of a payout to
shareholders (Dharmapala, Foley, and Forbes, 2011). Moreover, to avoid a deferred tax liability,
firms must convince auditors and the tax authorities that foreign income will be permanently
reinvested in capital projects11 (Edwards, Kravet, and Wilson, 2012; Blouin, Krull, and
Robinson, 2012). These features limit the scope for market investment as LDI and general
investment. In an environment where general investment and LDI distinguish market investment
9 This paper uses capital expenditure (speculative motive) and the corporate tax rate (tax arbitrage) as variables to address the first alternative to the storage view (general investment). This paper uses long term interest expenses and dividend payout as variables to address the second alternative to the storage view (LDI). 10 For each model (excess cash and market investment), there might be model misspecification. However by using relative analysis, the regression-difference method is more robust to model misspecification when compared to a single-regression method. 11 Victor Fleischer, “Overseas Cash and the Tax Games Multinationals Play,” The New York Times DealBook, October 3, 2012. The accounting exception, FASB Accounting Standards Codification (ASC) 740-30-25-17, states “A parent entity shall have evidence of specific plans for reinvestment of undistributed earnings of a subsidiary which demonstrate that remittance of the earnings will be postponed indefinitely.”
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from excess cash, managers of trapped-liquidity are likely to be constrained to conform to the
storage view.
Consistent with the presence of a limited payout and constrained investment, for trapped-
liquidity firms, coefficients for the PII variables do not differ between excess cash regressions
and market investment regressions. However, for all firms, the average absolute coefficient
difference between excess cash regressions and market investment regressions (for PII variables)
is 12%.12
This paper is primarily related to the literature on the determinants of marketable
securities (Jeffers and Kwon, 1969) and liability-driven investment (van Binsbergen and Brandt,
2009; Ang, Chen, and Sundaresan, 2012). This paper is also related to the literature on money
demand (Barro and Fischer, 1976; Frenkel and Jovanovic, 1980), money assets (Dang, Gorton,
and Holmstrom, 2009; Krishnamurthy and Vissing-Jorgensen, 2012; Stein, 2012; Sunderam,
2012), corporate liquidity (Eppen and Fama, 1968), and financial flexibility (Gamba and
Triantis, 2008; Denis and Sibilkov, 2010; Denis, 2011; Denis and McKeon, 2012). Finally, this
paper is related to the literature on international taxation (Desai, Foley, and Hines, 2006; Foley et
al., 2007; Graham, Hanlon, and Shevlin, 2011; Dharmapala, Foley, and Forbes, 2011; Blouin,
Krull, and Robinson, 2012; Edwards, Kravet, and Wilson, 2012).
This paper is the first to investigate the storage view of market investment for the modern
firm. In doing so, this paper studies the difference between excess cash and marketable securities
by following a large cross-section of US firms over time. The findings suggest that market
investment is no longer a passive store of excess liquidity. Rather, market investment is
associated with active general investment and liability-driven investment.
12 This paper’s findings also suggest that market investment is not a simple substitute for cash; the average absolute coefficient difference between cash regressions and market investment regressions is 24%.
6
2. Corporate Market Investments: Definition and Example
What are corporate market investments? What types of market investments does a modern firm
make?
Corporate market investments are recognized by the Financial Accounting Standards
Board (FASB) in the Statement of Financial Accounting Standards (SFAS) No. 11513 as
“investments in equity securities that have readily determinable fair values” and “all investments
in debt securities.” Market investments do not include unsecuritized loans, futures, forwards,
options, or other derivatives recognized by SFAS No. 133. Moreover, market investments do not
include treasury stock from repurchases or consolidated subsidiaries, but can include mortgage-
backed securities and other securitized loans.
Google is a large public corporation in the internet and technology sector. Google’s
investments provide not only a good example of the diversity in the types of marketable
securities, but diversity in the maturity of marketable securities. Exhibit I shows the liquid-asset
amounts for the annual period ending December 31, 2011, the firm has total assets of
approximately $72.6 billion. The firm’s cash holding excluding cash-equivalent marketable
securities is equal to approximately $4.7 billion. The firm’s total market investment (excluding
cash-equivalent marketable securities) is equal to approximately $34.6 billion. Its market
investment as a percentage of net assets (total assets minus cash minus cash-equivalent securities
minus market investments) is equal to approximately 124%. The largest component of Google’s
market investment consists of US government notes ($11.6 billion), which make up
approximately 41% of net assets. Google’s market investments also include municipal securities
($1.8 billion), corporate debt securities ($6.1 billion), equity securities ($307 million), and
13 SFAS No. 115 supersedes SFAS No. 12. SFAS No. 12 presents a standard for equity security accounting and the conditions under which equity investments should be recorded at cost or at market value.
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agency residential mortgage-backed securities ($6.5 billion). Of the $34.3 billion of non-cash
equivalent debt marketable securities, $13.2 billion worth is due within 1 year (38.6%), $7.5
billion worth is due between 1 year and 10 years (21.8%), and $8.1 billion worth is due after 10
years (23.6%). Google obviously has a flexible investment policy: Google is not limited to
investing a moderate amount of funds in short-term US Treasuries.
3. Aggregate Market Investments: Size and Risk
To understand the change in corporate market investment practices over time, this section
presents evidence of the trend in aggregate market investment size, and the change in the
aggregate portfolio composition over time.
Taking data from the Flow of Funds Accounts, Table I shows the time-series means of
various types of market investment for three separate periods: Period 1 (1945 to 1964), Period 2
(1965 to 1984), and Period 3 (1985 to 2005). Period 1 firms place approximately 84% of their
investible funds in US Treasury securities,14 and on average, market investments are equal to
approximately 8% of tangible assets. The Period 2 aggregate investment portfolio is more
diverse than the Period 1 portfolio; investments in US Treasury securities comprise only 16.2%
of all Period 2 market investments. On average, approximately 57% of all Period 2 market
investments are classified as unidentified miscellaneous financial assets, with total market
investments being equal to approximately 12% of tangible assets. Finally, Period 3 market
investments are equal to approximately 53% of tangible assets, with over 90% of investments
being classified as unidentified miscellaneous financial assets.
Figure I shows the aggregate real amounts of market investments by asset class
(excluding unidentified miscellaneous financial assets) for the years 1945 to 2008. In 1945,
14 Jacobs (1960) uses a survey method to show the various market investment components of a pre-1960 sample of corporations. He states that pre-1960 firms place most of their investible funds in government debt. In addition, he alludes to the progression towards a higher non-Treasury component.
8
private firms invested $200 billion (2005 dollars) in US Treasury securities. Over the years,
firms invested less in US Treasuries and more in other asset classes; in 2008, private firms
invested $200 billion (2005 dollars) in mutual funds. Over the years, the aggregate amount
invested in unidentified miscellaneous financial assets (or “other” financial assets) dwarfs the
amount invested in all identified market investments. In 2008, private firms invested over $6
trillion (2005 dollars) in unidentified miscellaneous financial assets. Figure II shows the extreme
change in the portfolio composition; in 1945, approximately 100% of the aggregate corporate
market investment portfolio consisted of US Treasury securities. In 2008, approximately 100%
of the aggregate corporate market investment portfolio consisted of unidentified miscellaneous
financial assets.
4. Related Literature and Hypothesis
This section discusses the related literature and presents this paper’s hypothesis. This paper’s
hypothesis is informed by models of liquid-asset demand15 (buffer-stock models and inventory
models) and the motives associated with corporate liquidity management. The current literature
on corporate liquidity management describes the associated motives for all liquid assets (Opler et
al., 1999; Bates, Kahle, and Stulz, 2009). However, the literature does not address the treatment
of the two forms of liquid assets (cash and marketable securities). To understand the two forms, I
review an older literature on liquid asset demand (Patinkin, 1956, Miller and Orr, 1966).
Buffer-stock models explain the demand for all liquid assets (Patinkin, 1956). In a buffer-
stock model, the manager determines the optimal amount of liquid assets to maintain, given
various motives: the precautionary motive, the transactions motive, the tax motive, the agency
cost motive and other motives associated with corporate liquidity management.
15 In the liquid-asset demand literature, short-term investments in marketable securities are often described as money assets.
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Inventory models explain the demand for physical currency (or cash) by firms (Baumol,
1952; Tobin, 1956; Miller and Orr, 1966, 1968; Eppen and Fama, 1968; Constantinides, 1976),
given that managers can maintain liquid assets in two forms: cash and money assets. In an
inventory model, the manager recognizes the two forms, but is concerned only with determining
the optimal amount of cash to maintain over the course of the operating period. Inventory models
are silent on the optimal amount of money assets.16
Buffer-stock models and inventory models recognize investments in marketable
securities as a passive dependent (residual) action. The models do not acknowledge the
investment in marketable securities as an active independent managerial decision. For a manager
who is unconcerned about the form of liquid asset, buffer-stock models recognize market
investments as being substitutes for cash.
For a manager who would like to determine the optimal demand for cash given that
deterministic17 and stochastic18 factors can influence the transfer between cash and money assets,
inventory models recognize market investments as money assets: the residual after the manager
takes the primary action (cash allocation). If, within bounds, cash is recognized as expected cash
16 Tobin argues that money assets are those that are “marketable, fixed in money value, and free of default risk.” Other assets such as corporate equity are not applicable in the cash-demand framework. These assets would fall in the category of general investment (Tobin, 1955; Scott, 1979). See Sprenkle (1969) for his assumption that even current market investments are made with the speculative motive in mind. 17 When cash flows are deterministic, Baumol (1952) argues that optimal cash demand comes about as an allocation decision between a cash account and an account of money assets. Tobin (1955) declares that “cash is by no means the only asset in which transactions balances may be held. Many transactors have large enough balances so that holding part of them in earning assets, rather than in cash, is a relevant possibility… these holdings are always for short periods.” Baumol declares that the optimal amount of cash is that which minimizes transaction costs (brokerage costs and savings-yield opportunity costs). Controlling for year effects (or the savings-yield opportunity cost), in a Baumol-Tobin model, it is possible that market investments are viewed as money assets and will only differ from cash based on variables that measure per-unit brokerage costs. Given the economies of scale in brokerage costs, cash should decrease with size (or as per-unit brokerage costs decline). If market investments are money assets, then market investment should increase with size, but should be equivalent to cash otherwise. 18 When cash flows are stochastic, Miller and Orr (1966, 1968) argue that transfers between the cash account and the investment account will be triggered by boundary conditions (upper and lower). In a Miller-Orr model, a variety of factors and motives can affect the optimal demand for cash. In the corporate liquidity management literature, the optimal amount of liquid assets is determined given various managerial motives (Opler et al., 1999; Bates, Kahle, and Stulz, 2009). The Miller-Orr model predicts that upon meeting an upper bound for its cash balance, a firm will distribute cash, retire debt, or transfer excess cash to the investment account.
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(or optimal cash) and if the positive difference between observed cash and expected cash is
recognized as excess cash (or the cash in excess of optimal cash), then market investment should
share the same determinants as excess cash. This behavior occurs because market investment is a
relatively simple store of excess cash.
The minor role that market investment plays in buffer-stock models and inventory models
can be characterized as the storage view. The storage view states that market investment is
simply a store of excess cash. Jeffers and Kwon (1969) study the demand for government
securities by firms and find support for the storage view. The authors argue that investment in
government securities is, by and large, low-risk and a simple store of excess cash. However
given the recent changes in market investment size and market investment composition, this
paper examines the storage view for the modern firm.
The first alternative to the storage view is that managers invest in marketable securities
with goals similar to those of capital investment (general investment). In contrast to the storage
view, the first alternative views market investment as the primary action—one that is made with
an objective similar to general investment through speculation (Keynes, 1936), portfolio choice
(Tobin, 1955), or tax arbitrage (Scott, 1979).
If market investments are used in line with general investment19 (Keynes, 1936; Spenkle,
1969), then relative to cash or excess cash, the use of market investment should be increasing in
capital expenditure.
Scott (1979) argues that the storage view is not compelling because many firms hold
larger and riskier investments than what can be explained by cash-management models. Scott
19 Unlike most of his contemporaries, Sprenkle (1969) recognizes that even short-term investments can be speculative. Sprenkle writes “The rationale for treating observed balances as being essentially transaction balances was usually that the Keynesian speculative and precautionary balances were undoubtedly very low. Few qualms were felt about excluding the possibility of speculative cash balances since it was felt that these balances would be held in short-term assets other than money.”
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contends that, from a benefit-cost standpoint, market investments20 should be viewed in the same
manner as one views capital investments. In particular, market investment should be evaluated
based on its effect on firm value. He argues that market investment could increase value if there
are substantial tax benefits, as in the case of dividend-paying corporate equity. Scott goes on to
state that market investment can increase value only if it meets the following tax condition.
[1] �1 − ����1 − � > �1 − �
For the tax condition, �� is the capital-gains tax rate for the firm’s shareholder, � is the tax rate
on investment income for the firm’s shareholder, and � is the tax rate on investment income for
the firm. � varies with the type of investment and the corporate tax rate. For dividend-paying
corporate equity, � is equal to �1 − �� , where � is equal to the dividend exclusion rate and �
is equal to the corporate tax rate. For all other taxable investments, � is equal to � . For tax-
exempt investments, � is equal to zero.
If market investments are used for general investment through tax arbitrage, then relative
to excess cash, the use of market investment should be decreasing in the corporate tax rate.
The second alternative to the storage view is that managers invest in marketable
securities to manage future financial commitments and promises. Given the recent changes in the
portfolio composition of market investments and the finding that corporations can use tools other
than derivatives to hedge cash-flow risk (Faulkender, 2005), it could be the case that market
investment is used as a risk management tool.21 In studying risk management, one might not be
20 Scott (1979) argues that because corporations have a tax advantage with respect to dividends, investment in tax-exempt securities should reduce value, whereas investment in dividend-paying corporate equity should increase value. In this paper, I attempt to understand the determinants of the amount of market investments (relative to the determinants of cash and excess cash) more so than the determinants of the composition of market investments. 21 The immediate goal of risk management is to reduce the variability of income, but risk management might have implications for firm value (Smith and Stulz, 1985). Reduced variability of income can increase value for firms with a high current tax liability and firms with a high cost of financial distress (Haugen and Senbet, 1978; Shleifer and
12
solely concerned with the motives for risk management, but also concerned with the optimal risk
management tools and with the types of funds that are being managed. When faced with long-
term financial commitments, a manager can practice liability-driven investment22 (LDI) to
reduce the variability of funds used to satisfy these long-term financial commitments (Wallas,
1959; Miller and Orr, 1967; Hoevenaars et al., 2008; Ang, Chen, and Sundaresan, 2012).23
Miller and Orr (1967, 1968) present the LDI motive for marketable securities. In Miller
and Orr (1968) the authors argue that “in practice corporate financial officers may rely heavily
on (portfolio) runoffs as a means of replenishing the firm’s cash balance (see Miller and Orr,
1967). The policy becomes oriented toward anticipation of heavy future requirements and the
purchase of securities of a maturity to match these requirements in time. To the extent that cash
flows are predictable in timing and magnitude, this kind of reliance on runoffs to meet cash
needs may be economical.” In this regard, market investments might be more useful than cash
because market investment returns can be tailored to match returns associated with long-term
financial commitments.
Jagannathan, Stephens, and Weisbach (2000) and Brav et al. (2005) argue that a firm’s
dividend payout behaves like an ongoing commitment and tends to be associated with
sustainable cash flows. Lintner (1956) shows that managers are hesitant to cut dividends and are
exposed to a sharp decline in the stock price when they cut dividends. Hence managers could be
particularly risk averse when it comes to the variability of funds used to satisfy dividends.
Vishny, 1992; Asquith, Gertner, and Scharfstein, 1994). Alternatively, shareholders might not benefit from reduced variability when managers are risk averse. 22 A popular related literature is the dynamic portfolio choice literature (Campbell and Viceira, 2002). 23 Liability-driven investment (LDI) has long been used by financial intermediaries as a way to manage interest rate risk (Grove, 1974; Flannery 1981). Moreover, firms with pension liabilities find it useful to structure an asset mix that maximizes profits given these liabilities (Rauh, 2009; van Binsbergen and Brandt, 2009; Ang, Chen, and Sundaresan, 2012).
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If market investments are used for LDI, then relative to cash or excess cash, the use of
market investment should be increasing in long-term interest expenses and dividends.
5. Empirical Method
This paper examines the storage view by testing the hypothesis that the determinants of market
investment are the same as the determinants of cash or excess cash. To test coefficient
differences between market investment and cash, this paper uses a generalized Hausman test for
differences in coefficients between market investment and cash, for all variables. For excess
cash, this paper uses a novel two-stage method that first partitions variables and estimates excess
cash, then uses a generalized Hausman test for differences in coefficients between market
investment and excess cash, for PII variables only. To get a representative estimate for
coefficient differences, statistically significant coefficient differences are averaged based on the
percentage correlation-ratio weights for cash (or excess cash).
Excess Cash Estimation
To compare the determinants of market investment to the determinants of excess cash,
this paper uses an estimate of excess cash, which is defined as observed cash in excess of
expected cash. Following Opler et al. (1999), this paper uses a Fama-Macbeth regression
procedure to estimate the coefficients for expected cash. The Fama-Macbeth procedure uses
yearly regressions of cash on industry dummies �� and core variables �� that should determine
expected cash for immediate needs (size, leverage, cash flow, new financing, market-to-book
ratio, and R & D expenses).24 The expected-cash coefficients are obtained by averaging yearly
coefficients, � and ��.
[2] �����ℎ� = ���̅ + �̅�
24 The specification for the core variables is informed by Opler et al. (1999) and Faulkender and Wang (2006).
14
[3] ��� �� = �� ����ℎ�� − �����ℎ�, 0
Here i=1,…,M is an index for firms, j=1,…,J for industries, and t=1,…,T for time (years).
The non-negative fitted residuals of the Fama-Macbeth regression ��� �� are used as the estimates
for excess cash.
Variable Partitioning: Core Variables and PII Variables
While the core variables are likely to have an effect on excess cash and market
investments, the use of an excess-cash estimate derived from the core variables could introduce a
bias towards finding differences for the coefficients of the core variables. Therefore to test
whether the determinants of excess cash are the same as the determinants of market investment,
this paper focuses on variables #��, outside of the core variable set, which could have a stronger
association with market investment when compared to the corresponding association with excess
cash. These variables for payout, interest, and investment (PII) are those related to liability-
driven investment (dividend payout and interest expense) and general investment (capital
expenditures and the marginal tax rate).
Generalized Hausman Test for Equality of Coefficients
If market investment is a simple substitute for cash, then it should share a common data-
generating process with cash; if market investment is a simple store of excess liquid assets, then
it should share a common data-generating process with excess cash. In order to test whether two
models share the same data-generating process, this paper estimates the simultaneous covariance
matrix of the two estimator vectors for cash (or excess cash) and market investments. A
seemingly unrelated estimation method is used to estimate a simultaneous covariance matrix that
is robust to heteroscedasticity. This seemingly unrelated estimation method is an application of
the general sandwich estimator with clusters (White, 1982).
15
Consider the following common data-generating process for a common dependent
variable $�� under the null hypothesis. Here i=1,…,M is an index for firms, j=1,…,J for
industries, and t=1,…,T for time (years). %�� is a mean zero noise term. �� and �� are year and
industry effects. Here &�� includes both core variables ��� and PII variables #��.
[4] $�� = &��' +�� + �� + %��
Given [4], consider N different models—with N estimators—for the same data. Here
k=1,…,N is an index for the different models.
[5] $(�� = &��')( +�� + �� + %(��, * = 1,… ,,
As an example, consider the case where $�� represents excess liquid assets; the split between the
two components of excess liquid assets—excess cash and market investments—is random under
the null hypothesis.25 In this example, there are two models. A common cross-estimator
hypothesis is as follows.
[6] -.:plim')4 = plim')5
The hypothesis can be tested using a generalized Hausman test when one estimates a
simultaneous covariance matrix. The generalized Hausman test has a number of advantages over
the traditional Hausman test (Hausman, 1978). For instance, if the data are clustered, the
traditional Hausman test is not defined. In comparing market investments to excess cash, this
paper presents the results of a generalized Hausman test for the equality of coefficients.
Effect-Size-Weighted Average of Absolute Coefficient Differences
Given the generalized Hausman test, rejection can be determined by looking at a set of
coefficient differences. However for a representative estimate of the set, the coefficient
differences can be reduced to an average of absolute coefficient differences. To determine the
25 Alternatively if $�� represents the buffer stock, then the split between the two components of the buffer stock—cash and market investments—is random under the null hypothesis.
16
average coefficient difference between two models, this paper uses a weighted average of
absolute coefficient differences. In the case of cash, I average over all variables; in the case of
excess cash, I average over PII variables only (the variables that are proposed to be related to
market investment for uses other than cash management).
While an equal-weighted average of statistically significant differences seems reasonable,
equal weights lack one important feature. A coefficient difference for a weak determinant should
not be given the same weight as a coefficient difference for a strong determinant. Hence this
paper uses effect-size weights to determine the average absolute coefficient difference.
Using an effect-size-weighted average is more appropriate than using an equal-weighted
average, but there is more than one set of weights: excess-cash weights and market-investment
weights. One can average coefficients based on market-investment weights or excess-cash
weights. Under the null hypothesis, both sets of weights would be the same. However under the
alternative, the weights are different. Given that the hypothesis test carries the burden of
rejection, I report the weighted average coefficient difference based on weights for the given
cash model. For example, in the case of excess cash, the weight for each difference is the
percentage 65 (or correlation ratio) for the PII variables in the excess-cash model normalized by
the sum of all percentage 65 for the PII variables.
6. Data
Aggregate data for private nonfarm nonfinancial corporations are taken from the Flow of Funds
Accounts maintained by the Federal Reserve Board of Governors. Firm-level data are initially
extracted from the Compustat/CRSP merged database for the years 1970 to 2009. I exclude
financial firms (SIC codes between 6000 and 6999), utilities (SIC codes between 4900 and
4999), and foreign firms. I exclude firm-year observations where data are missing or negative for
17
market value of equity (CSHPRI * PRCC_F). I exclude fiscal years that could have been
influenced by the Global Financial Crisis: 2007 to 2009. Finally, I exclude firm-year
observations where data are missing for all of the following items: investments and advances
using the equity method (IVAEQ), investments and advances using the market method (IVAO),
and short-term investments (IVST).
All data are converted to 2006 dollars using a consumer price index (CPI). CPI data are
extracted from the Federal Reserve Economic Data maintained by the Federal Reserve Bank of
St. Louis. The market investments variable is equal to short-term investments plus noncurrent
investments using the equity and market methods. Cash is cash plus short-term investments
(CHE) minus short-term investments. Liquid assets is equal to the market investments variable
plus the cash variable.
Capital expenditure is equal to the capital expenditures of the firm (CAPX). The size
variable is equal to the market value of equity. The cash flow variable is equal to earnings before
interest, taxes, depreciation, and amortization (or EBITDA) minus interest, minus taxes minus
common dividends paid (OIBDP – XINT – TXT – DVC). Leverage is equal to the market debt
ratio, calculated as total debt (DLTT + DLC) divided by the sum of total debt and the market
value of equity. New financing is equal to total equity issuance (SSTK) minus repurchases
(PRSTKC) plus debt issuance (DLTIS) minus debt redemption (DLTR). Short-term debt ratio is
equal to current liabilities (DLC) divided by total debt. Interest expense is equal to the interest
payments of the firm (XINT). The dividend payout is equal to common dividends paid (DVC).
Pension expense is equal to the pension expense of the firm (XPR). The LDI index variable is the
first principal component factor of the dividend payout and pension expense variables. The
repurchase variable is equal to the purchase of the firm’s own common stock and preferred stock
18
minus the redemption of preferred stock (PRSTKC – PSTKRV). R & D expense is equal to
research and development expenditures (XRD) divided by sales (SALE). The market-to-book
ratio is equal to net assets (AT – CHE – IVAEQ – IVAO) minus book equity (CEQ) plus the
market value of equity, all divided by net assets.
The marginal tax rate is a trichotomous variable (Shevlin, 1990; Graham, 1996). The
firm-year marginal tax rate variable is constructed based on taxable income, the top statutory tax
rate, and the net operating loss (NOL) carry-forward (TLCF). Following Graham and Kim
(2009), taxable income is defined as operating income after depreciation plus non-operating
income minus interest expense minus deferred taxes from the income statement (divided by the
top statutory tax rate) plus extraordinary items and discontinued operations (divided by one
minus the top statutory tax rate) plus special items (OIADP + NOPI – XINT – (TXDI/top tax
rate) + (XIDO/(1 – top tax rate)) + SPI). The marginal tax rate is equal to the top statutory tax
rate if taxable income is positive and there is no NOL carry-forward (TLCF is zero or missing).
The marginal tax rate is equal to half of the top statutory tax rate if either the taxable income is
positive or there exists an NOL carry-forward (without both conditions being satisfied). The
marginal tax rate is equal to zero in all other cases. The repatriation tax variable is equal to the
tax costs of repatriating earnings. Following Foley et al. (2007), this variable is computed by
subtracting foreign taxes paid (TXFO) from the product of the firm’s marginal tax rate and the
firm’s pretax income (PIFO).
To explore heterogeneity based on toehold investments in future merger or acquisition
firms, I use a toehold variable (in year t) equal to one if the company completes a merger or
acquisition in fiscal year t + 1, and zero otherwise. Merger and acquisition data are taken from
SDC Platinum for the years 1969 to 2006. To identify firms with multiple segments, I collect
19
segment data from the Compustat annual business segment files. The multiple segment variable
is equal to one if the firm has more than one business segment, and zero otherwise.
All variables other than size, R & D expense, leverage, short-term debt ratio, market-to-
book ratio, the E index, toehold, multiple segment, the LDI index, and the marginal tax rate are
normalized by net assets. All variables are winsorized at the 1% tails to lessen the effect of
extreme values. I also eliminate firm-year observations for which net assets or dividend payout
values are negative. The final sample consists of 108,864 observations for the years 1971 to
2006. The sample summary statistics are presented in Table II.
7. Sample Statistics and Empirical Analysis
Table II presents definitions (in the legend) and lists the summary statistics for variables used in
this study. Market investments, cash, capital expenditures, cash flow, new financing,
repurchases, interest expense, and dividend payout are all normalized by net assets (total assets
minus cash minus market investments).
The market investment distribution is positively skewed with a mean of 21.30%. When
investigating the raw market investment variable, the average amount for market investments is
approximately $156 million in 2006 dollars. For perspective, the average total net assets for a
mutual fund is approximately $300 million (Chen et al., 2004), whereas the average size for a
hedge fund is approximately $80 million (Getmansky, 2004).
The cash distribution is positively skewed with a mean of 19.2%. The mean for capital
expenditures is 9.60% and is similar to the 9% found in Opler et al. (1999). The median for
capital expenditures is 6.20%. The median equity value for firms in the sample is roughly $82.3
million. The median values for cash flow, the marginal tax rate, and the market-to-book ratio are
20
6.80%, 35%, and 1.317. The mean for leverage is 29.50%, which is comparable with the findings
by Opler et al.
Table III presents the estimates of the determinants of cash,26 the determinants of excess
cash, and the determinants of market investments. For ease of exposition, the independent
variables in all regressions are standardized. All specifications include year effects and industry
effects.27 Column (1) uses a specification that includes core variables and PII variables and finds
that for core variables, cash decreases with firm size28 and leverage, but increases with new
financing, the market-to-book ratio, and R & D expenses.
Estimating Excess Cash
To estimate excess cash, the specification in column (2) is limited to core variables only.
In column (2), the Fama-Macbeth coefficients are mostly consistent with the coefficients for the
cash regression in column (1); expected cash (or transactions cash) decreases with firm size and
leverage, but increases with new financing, and the market-to-book ratio. The non-negative fitted
residuals from the Fama-Macbeth regression are used as estimates of excess cash. In column (3),
these residuals are regressed on the core variables and the PII variables. For the PII variables,
excess cash increases with long-term interest expenses and capital expenditure, but decreases
with the corporate tax rate.
26 Research finds that new financing (McLean, 2011), corporate diversification (Duchin, 2010), bank power (Sprenkle, 1969; Pinkowitz and Williamson, 2001), corporate governance (Dittmar, Mahrt-Smith, and Servaes, 2003; Harford et al., 2008), and financial constraints (Almeida, Campello, and Weisbach, 2004) are all important factors associated with corporate liquidity. 27 Maddala and Vogel (1967) argue that panel-data regressions are better than pure cross-sectional regressions for identifying the determinants of money and the determinants of government security balances. 28 Firm size can also be viewed as a measure of financial constraints (Hadlock and Pierce, 2010). Hadlock and Pierce argue that firm size and firm age are better measures of financial constraints when compared to the KZ index (Kaplan and Zingales, 1997).
21
The Determinants of Market Investments
Columns (5) and (6) investigate the determinants of market investments under two
separate models: a Tobit model and an OLS model. The Tobit model is appropriate under the
assumption that investments at zero are censored; managers would like to make negative
investments but are constrained. The OLS model is appropriate under the assumption that a zero
investment is intentional. Both models give similar results.
In column (6), market investment increases with firm size, new financing, the market-to-
book ratio, and R & D expense, but decreases with leverage and cash flow. Firm size is strongly
associated with market investment; a standard-deviation increase in firm size is associated with
an increase of approximately 1.09 in market investments.
For the PII variables, market investment increases with long-term interest expenses,
dividends, and capital expenditure, but decreases with the corporate tax rate. A standard-
deviation increase in dividend payout is associated with an increase of approximately 25.3% in
market investments. A standard-deviation increase in long-term interest expenses is associated
with an increase of approximately 38% in market investments. A standard-deviation increase in
the corporate tax rate is associated with a decrease of approximately 17% in market investments.
Finally, a standard-deviation increase in capital expenditure is associated with an increase of
approximately 12.8% in market investments.
Market Investment as a Percentage of Liquid Assets
To estimate the difference between excess cash and market investment, this paper
compares the coefficients of an excess-cash regression to coefficients of a market-investment
regression. However, in general, firms that invest heavily in marketable securities might also
maintain large cash balances. Moreover, firms might maintain a fixed ratio of market
22
investments to liquid assets. One concern, with respect to the main results, is that there is a
relation between an independent variable and market investment in the cross-section because of
the type of firm that makes market investments. However when observing one firm, there is no
effect on market investment as a percentage of the firm’s liquid assets (cash plus market
investments). Hence Table III, in addition to the basic regressions, presents regression results
where the dependent variable is market investment as a percentage of liquid assets.
Column (4) of Table III investigates the determinants of market investments as a
percentage of liquid assets. In column (4), market investment increases with firm size and R & D
expense, but decreases with leverage and cash flow. For the PII variables, market investment
increases with long-term interest expenses, dividends, and capital expenditure, but decreases
with the corporate tax rate. For the PII variables, the coefficients are statistically significant at
the 1% level.
Are Market Investments and Cash Perfect Substitutes?
In a buffer-stock model, cash and market investment are perfect substitutes and are
therefore statistically equivalent. To test the prediction of the buffer-stock model, Table IV
column (4) uses a generalized Hausman test and compares determinants of market investments to
the determinants of cash by using the base specification with year effects and industry effects.
When comparing coefficients, one goal is to uncover the ways in which market investments are
similar to, or different from cash based on observable variables. If market investments are
equivalent to cash, then the difference in corresponding coefficients should be statistically and
economically indistinguishable from zero (a generalized Hausman test for coefficient equality).
Cash decreases with size, but market investments exhibit the opposite behavior. The
absolute coefficient difference (or elasticity difference) is approximately 1.26 and is statistically
23
significant at the 1% level. These results are partly consistent with a transactions-cost motive for
holding cash, where market investments serve as the money asset account in an inventory model
of cash demand. For cash flow, the coefficient difference is -15.20% and is statistically
significant at the 1% level. Statistically significant coefficient differences are present for 9 of the
remaining 11 variables thus rejecting the hypothesis that the coefficients are statistically
equivalent. For all variables, the cash 65-weighted average difference in absolute coefficients is
24.2%.
For the PII variables, there are substantial coefficient differences between cash
regressions and market investment regressions. The coefficient differences for long-term interest
expenses, dividend payout, the corporate tax rate, and capital expenditures are all significant at
the 1% level. Compared to the corresponding effect for the cash regression (or the cash effect), a
standard-deviation increase in dividend payout is associated with an increase of approximately
26.4% in market investments. Compared to the cash effect, a standard-deviation increase in long-
term interest expenses is associated with an increase of approximately 13.4% in market
investments. Compared to the cash effect, a standard-deviation increase in the corporate tax rate
is associated with a decrease of approximately 11.8% in market investments. Furthermore,
compared to the cash effect, a standard-deviation increase in capital expenditure is associated
with an increase of approximately 7.9% in market investments. For these PII variables, the cash
65-weighted average difference in absolute coefficients is 8.1%.
These findings reject the idea that market investment is equivalent to cash. These findings
also reject the idea that cash and market investment differ based on firm size only. Furthermore,
while Table IV presents evidence that market investments are different from cash based on
24
common observable variables, Table III columns (5) and (6) show that cash is not a statistically
significant determinant of market investments through common unobservables.
To examine the storage view, this paper continues by comparing the determinants of
market investments to the determinants of excess cash.
Are Market Investments a Simple Store of Excess Cash?
In a Miller-Orr inventory model, the decision to transfer funds from the cash account to
the investment account is influenced by shocks to cash that engender excess cash. In this model,
market investment is a simple store of excess cash. To test the prediction of the Miller-Orr
model, Table IV column (5) uses a generalized Hausman test and compares determinants of
market investments to the determinants of excess cash by using the base specification with year
effects and industry effects. If market investments are equivalent to excess cash, then the
difference in corresponding coefficients should be statistically and economically
indistinguishable from zero.
Given that excess cash is derived from a regression of cash on the core variables, I focus
on coefficient differences for PII variables only. The coefficient differences for long-term
interest expenses, dividend payout, the corporate tax rate, and capital expenditures are all
significant at the 1% level. Compared to the corresponding effect for the excess-cash regression
(or the excess-cash effect), a standard-deviation increase in dividend payout is associated with an
increase of approximately 25.3% in market investments. Compared to the excess-cash effect, a
standard-deviation increase in long-term interest expenses is associated with an increase of
approximately 20.1% in market investments. Compared to the excess-cash effect, a standard-
deviation increase in the corporate tax rate is associated with a decrease of approximately 13.3%
in market investments. Furthermore, compared to the excess-cash effect, a standard-deviation
25
increase in capital expenditure is associated with an increase of approximately 8.1% in market
investments. For these PII variables, the excess-cash 65-weighted average difference in absolute
coefficients is approximately 12%. These findings reject the idea that market investment is
equivalent to excess cash for the PII variables.
8. A Natural Experiment: Repatriation Taxes
Table IV presents findings that reject the predictions of the storage view. However, this paper
presents two assumptions for the validity of the test. First, this paper assumes that the PII
variables proposed to test the storage view, taken together, represent general investment and LDI
concerns. The alternative is that the PII variables do not represent the real economic concerns
which I argue to be the drivers that distinguish market investments from excess cash. Second, the
method used to examine the Miller-Orr version of the storage view, given that excess cash is not
directly observable, requires a two-stage estimation process. This paper assumes that the
estimation model is well specified. The alternative is that there is model misspecification. In
particular, there might be misspecification that results in estimation error for excess cash, and
this estimation error might result in coefficient differences that do not reflect real economic
differences.
To validate the two assumptions, which when violated might bias coefficient differences,
Table V uses a natural experiment where there should be no significant coefficient differences
under the two assumptions. The natural experiment focuses on firms with “trapped” liquidity
(firms that would incur taxes on repatriated foreign earnings). These trapped-liquidity firms
accumulate liquid assets (Foley et al., 2007). Moreover, trapped-liquidity firms are limited in
their payout policy (Dharmapala, Foley, and Forbes, 2011) and constrained to capital investment
as general investment because of the requirement to permanently reinvest foreign earnings in
26
capital projects (Blouin, Krull, and Robinson, 2012; Edwards, Kravet, and Wilson, 2012).
Therefore, under the two assumptions, market investment should not be different from excess
cash for trapped-liquidity firms.
Column (4) of Table V shows the market-investment regression results for trapped-
liquidity firms. For these firms, three coefficients are statistically significant at the 5% level or
less: size, the market-to-book ratio, and R & D expenses, where the latter two are associated with
the precautionary motive (Opler et al., 1999). For trapped-liquidity firms, PII variables are not
significantly related to the use of market investments at the 5% level or less.
Column (6) shows coefficient differences for trapped-liquidity firms. Even though there
is some evidence of excess-cash estimation error for trapped-liquidity firms in column (2) where
PII variables are significantly correlated with excess cash, the error does not engender significant
coefficient differences for trapped-liquidity firms in column (6). In column (6), none of the
coefficient differences for PII variables are significant at the 10% level or less. For these PII
variables, the excess-cash 65-weighted average difference in absolute coefficients is zero.
Moreover, column (6) improves on column (4) in detecting the constraint for trapped-liquidity
firms; two coefficients are significant at the 10% level for PII variables in the market investment
regression, but none of the coefficient differences are statistically significant at the 10% level or
less.
Taken together, these findings suggest that this paper’s empirical method is valid even
when model misspecification might be present. That is, in cases where market investment is not
different from excess cash for economic reasons, there are no statistically significant coefficient
differences for PII variables, and the excess-cash 65-weighted average difference in absolute
coefficients is zero.
27
9. Investments in Marketable Securities and Acquisitions
Firms that acquire other firms as a growth strategy often make toehold investments before
acquisition completion. Therefore an alternative test for storage versus investment is one that
studies whether differences between market investment and excess cash are related to future
acquisitions. To implement the alternative test, in Table VI I investigate coefficient differences
by toehold status; the toehold dummy variable (in year t) is equal to one if the firm merges or
acquires another firm in year t +1.
The average coefficient difference for acquirers is less than the average coefficient
difference for no-merger firms. However the greater average coefficient difference for no-merger
firms is largely due to coefficient differences for long-term interest expense and dividend payout;
acquirers do not exhibit significant coefficient differences for long-term interest expense and
dividend payout.
While the average coefficient difference for no-merger firms is greater than the average
coefficient difference for acquirers, the absolute coefficient differences for the general
investment variables (corporate tax rate and capital expenditure) are greater for acquirers when
compared to no-merger firms. For no-merger firms, the corporate-tax coefficient difference is
approximately -12%; for acquirers, the corporate-tax coefficient difference is approximately
-19%. For no-merger firms, the capital-expenditure coefficient difference is approximately 7%;
for acquirers, the capital-expenditure coefficient difference is approximately 17%.
For no-merger firms, the excess-cash 65-weighted average difference in absolute
coefficients is approximately 12%. For acquirers, the excess-cash 65-weighted average
difference in absolute coefficients is approximately 8%. Hence the results suggest that the
28
difference in the sensitivity to investment (between market investments and excess cash)
increases with future acquisitions.
10. Robustness
This paper finds that the determinants of market investments are different from the determinants
of excess cash. This section explores the robustness of the finding. In particular, are the findings
in Table IV robust when matching on firm size?
Firm Size
Table IV shows that firm size is a particularly important determinant of market
investments. Therefore one concern is that differences between market investment and excess
cash are driven by large firms. To address this concern, Table VII investigates coefficient
differences by firm size.
The average coefficient difference for small firms is less than the average coefficient
difference for large firms. For large and small firms, coefficient differences exist for long-term
interest expenses, the corporate tax rate, capital expenditure, and dividend payout. For large
firms, the excess-cash 65-weighted average difference in absolute coefficients is approximately
16%. For small firms, the excess-cash 65-weighted average difference in absolute coefficients is
approximately 14%. Hence the results are robust to heterogeneity based on firm size.
11. The Interaction of Liability-Driven Investment with General Investment
This paper argues that market investments differ from cash and excess cash based on PII
variables and differences could be driven by liability-driven investment (LDI) and concerns for
general investment. However, firms might not all place the same weight on both concerns. For
instance, firms that make market investments for LDI purposes (risk management) could be less
likely to make market investments as general investment through speculation. In addition, it is
29
unclear whether the average coefficient difference is related to LDI and general investment. To
address these concerns, Table VIII investigates coefficient differences by a firm’s propensity for
promised commitments and dividends and by capital expenditure.
To investigate the heterogeneity in coefficient differences based on a firm’s propensity
for promised commitments and dividends, I construct an LDI index equal to the first principal
component of dividend payout and pension expenses. Firm-year observations are split based on
the median cutoff of the LDI index. Table VIII compares coefficient differences for low-LDI
observations and high-LDI observations. Given the sample split, the associated specification
excludes the short-term debt ratio, interest expense, and dividend payout.
The average coefficient difference for low-LDI observations is less than the average
coefficient difference for high-LDI observations. For high-LDI observations, the excess-cash 65-
weighted average difference in absolute coefficients is approximately 21%. For low-LDI
observations, the excess-cash 65-weighted average difference in absolute coefficients is
approximately 17%. This finding is consistent with the idea that the difference between excess
cash and market investments increases with LDI concerns.
For both low-LDI observations and high-LDI observations, coefficient differences exist
for the corporate tax rate and capital expenditure. However the correlation between the
corporate-tax coefficient difference and the capital-expenditure coefficient difference is negative;
for the corporate-tax coefficient difference, high-LDI observations are associated with a larger
absolute coefficient difference when compared to low-LDI observations; for the capital-
expenditure coefficient difference, high-LDI observations are associated with a smaller absolute
coefficient difference when compared to low-LDI observations. These findings suggest that
firms that make market investments for LDI purposes are more likely to make market
30
investments for tax arbitrage. The findings also suggest that firms that make market investments
for LDI purposes are less likely to speculate.
To investigate the heterogeneity in coefficient differences based on a firm’s propensity
for general investment through speculation, firm-year observations are split based on the median
cutoff of capital expenditure. Table VIII compares coefficient differences for low-investment
observations and high-investment observations. Given the sample split, the associated
specification excludes capital expenditure.
The average coefficient difference for low-investment observations is less than the
average coefficient difference for high-investment observations. For high-investment
observations, the excess-cash 65-weighted average difference in absolute coefficients is
approximately 17%. For low-investment observations, the excess-cash 65-weighted average
difference in absolute coefficients is approximately 13%. This finding is consistent with the idea
that the difference between excess cash and market investments increases with concerns for
general investment through speculation.
For both low-investment observations and high-investment observations, coefficient
differences exist for the corporate tax rate, long-term interest expenses, and dividend payout.
While the long-term interest-expense coefficient difference for low-investment observations is
similar to the corresponding coefficient difference for high-investment observations, the
correlation between the corporate-tax coefficient difference and the dividend-payout coefficient
difference is negative. For the corporate-tax coefficient difference, high-investment observations
are associated with a larger absolute coefficient difference when compared to low-investment
observations; for the dividend-payout coefficient difference, high-investment observations are
associated with a smaller absolute coefficient difference when compared to low-investment
31
observations. These findings suggest that firms that speculate are more likely to make market
investments for tax arbitrage. The findings also suggest that firms that make market investments
as general investment through speculation are less likely to make market investments for LDI
purposes.
Taken together, the results of Table VIII suggest the difference between excess cash and
market investment increases with LDI concerns and concerns for general investment. Moreover,
the findings suggest that the firms that make market investments for LDI (risk management) are
less likely to make market investments as general investment through speculation.
12. Conclusion
Today’s marketable securities are different from the marketable securities of 1960. Market
investment—on average—continues to grow, and previously moderate investment in US
Treasuries has given way to larger29 and more diverse market investment portfolios.
Market investment is not a simple substitute for cash nor is it a store of excess cash. The
average coefficient difference between cash and market investment regressions for all firms (and
all variables) is 24%. Using a natural experiment as a benchmark, this paper shows that for
variables related to payout policy, interest, and investment (PII), market investment does not
differ from excess cash for trapped-liquidity firms that are limited in their payout policy and
constrained to capital investment as general investment. However for all firms, the average
absolute coefficient difference between excess cash and market investment regressions for PII
variables is 12%. Compared to excess cash, market investment has more in common with LDI
and general investment.30
29 Currently, “assets under management” for corporations ($156 million) compare well with average figures for mutual funds ($300 million) and hedge funds ($80 million). 30 Moreover, the results presented in this paper show that the capital-expenditure coefficient difference increases with future acquisitions.
32
Market investment could in some ways be a compromise choice that occupies a space in
between capital investment and cash. Like cash, market investments provide the firm with
flexibility31 (Denis, 2011). Like capital investment, market investment is not perfectly
transparent; it is associated with a decision where the financial manager has more information
about the investment than the firm’s shareholder does about the investment.
Rather than study market investments in a liquidity-demand model, researchers might
find it more useful to study market investments in a model of investment decision-making
(Keynes, 1936; Tobin, 1955; Scott, 1979; Stein, 2003). It could even be the case that for market
investments, investment decision-making by corporations is just as important a research topic as
investment decision-making by households and financial intermediaries.
To understand the specialness of market investments, researchers might find it useful to
study market investments in a model of liability-driven investment.32 As a tool used to maintain
stable funds for financial commitments and dividends, market investments could be superior to
cash. This paper’s findings support the use of market investment (relative to excess cash) to
manage future long-term financial commitments and payout policy. Compared to excess cash,
market investment is strongly correlated with future financial commitments and dividends.33
The evidence presented in this paper has implications for financial managers and
regulators. With regard to financial managers, researchers might want to explore the idea of
optimal market investment. The issue of managerial market-timing could also be important for
31 Gamba and Triantis (2008) argue that flexibility provides a reason for maintaining debt and liquidity. The evidence suggests that liquidity might serve a purpose other than financial flexibility. This paper finds that, compared to cash and excess cash, market investment might be used for speculation and LDI. 32 Bolton, Chen, and Wang (2011a, 2011b) provide a useful framework for understanding a variety of corporate policies in relation to risk management in addition to speculative investment and financial flexibility. 33 Moreover, this paper’s findings suggest market investment could be one mechanism through which firms—in aggregate—can increase dividends without increasing repurchases (the dividend puzzle). If so, then market investment can provide an explanation for the dividend puzzle (Jagannathan, Stephens, and Weisbach, 2000). This idea and the motivating findings from this paper deserve further study.
33
market investments.34 Regulators might want to take an economic approach to the classification
of investment companies and the regulation of market investments.
In general, efforts to determine the composition of a firm’s market investments from
publicly available information bear little fruit. Greater transparency could improve upon
financial market efficiency and financial system health. Currently, if a firm holds more than 40%
of its total assets in market investments (excluding US Treasuries and cash equivalents), it can
attract the attention of the Securities and Exchange Commission (SEC), and might have to
register as an investment company.35 Instead of focusing on an arbitrary asset-based cutoff—
which might no longer be relevant—regulators might want to consider focusing on a general
benefit-cost analysis of market investments.
Although not directly investigated in this paper, the incentives to avoid regulatory
scrutiny could result in increased market investment risk. If firms are motivated to maintain a
low level of perceived market investment risk,36 they might tend to rely more on credit ratings
when compared to financial intermediaries with a higher investment risk tolerance. The global
financial crisis provides a painful lesson that highly rated securities can in fact be very risky
(Coval, Jurek, and Stafford, 2009). Investors, formerly lured by the promise of high yields and
low risk, now have to explain why seemingly prudent investment decision-making was met with
huge losses in 2008. Financial intermediaries have been particularly susceptible to this problem,
but a nonfinancial corporation could also be susceptible given its focus on credit ratings. This
and other issues surrounding marketable securities are worth exploring in future research.
34 See Faulkender (2005) for an example of managerial discretion with respect to the liability timing. 35 See the Appendix for a case study of National Presto Industries. 36 To avoid being regulated as an investment company (Investment Company Act of 1940), nonfinancial corporations face limits on risky marketable security investment.
34
References
Allen, Jeffrey W. and Gordon M. Phillips. 2009. Corporate Equity Ownership, Strategic Alliances, and Product Market Relationships. The Journal of Finance 55, 2791-2815.
Acharya, Viral; Heitor Almeida and Murillo Campello. 2010. Aggregate Risk and the Choice between Cash and Lines of Credit. Unpublished Working Paper.
Almeida, Heitor; Murillo Campello and Michael S Weisbach. 2004. The Cash Flow Sensitivity of Cash. The Journal of Finance 59, 1777-1804.
Ang, Andrew; Bingxu Chen and Suresh Sundaresan. 2012. Liability Driven Investment with Downside Risk. Unpublished Working Paper.
Asquith, Paul; Robert Gertner and David Scharfstein. 1994. Anatomy of Financial Distress: An Examination of Junk Bond Issuers. Quarterly Journal of Economics 109, 625-658.
Barro, Robert J. and Stanley Fischer. 1976. Recent Developments in Monetary Theory. Journal of Monetary Economics 2, 133-167.
Bates, Thomas W.; Kathleen M. Kahle and Rene M. Stulz. 2009. Why Do U.S. Firms Hold So Much More Cash than They Used To? The Journal of Finance 64, 1985-2021.
Baumol, William J., 1952. The Transactions Demand for Cash: An Inventory Theoretic Approach. Quarterly Journal of Economics 66, 545–556.
Becker, Bo and Victoria Ivashina. 2012. Reaching for Yield in the Bond Market. Unpublished Working Paper.
Blouin, Jennifer; Linda Krull and Leslie Robinson. 2012. Where in the World Are “Permanently Reinvested” Foreign Earnings? Unpublished Working Paper.
Bierwag, G. O. and Chulsoon Khang. 1979. An Immunization Strategy is a Minimax Strategy. The Journal of Finance 34, 389-399.
van Binsbergen, J. H. and Michael W. Brandt. 2009. Optimal Asset Allocation in Asset Liability Management. Unpublished Working Paper.
Bolton, Patrick; Hui Chen and Neng Wang. 2011a. A Unified Theory of Tobin’s q, Corporate Investment, Financing, and Risk Management. The Journal of Finance 66, 1545-1578.
Bolton, Patrick; Hui Chen and Neng Wang. 2011b. Market Timing, Investment, and Risk Management. Unpublished Working Paper.
Brav, Alon; John R. Graham, Campbell R. Harvey and Roni Michaely. 2005. Payout Policy in the 21st Century. J. Financ. Econ. 77, 483-527.
Campbell, John Y. and Luis M. Viceira. 2002. Strategic Asset Allocation: Portfolio Choice for Long-Term Investors. Oxford University Press: New York, NY
Campello, Murillo; Erasmo Giambona, John R. Graham and Campbell R. Harvey. 2011. Liquidity Management and Corporate Investment During a Financial Crisis. Review of Financial Studies 24, 1944-1979.
Chen, Joseph; Harrison Hong, Ming Huang, and Jeffrey D. Kubik. 2004. Does Fund Size Erode Mutual Fund Performance? The Role of Liquidity and Organization. Am. Econ. Rev. 94, 1276–1302.
Chudson, Walter. 1945. The Pattern of Corporate Financial Structure. National Bureau of Economic Research: New York, NY.
Constantinides, George M., 1976. Stochastic Cash Management with Fixed and Proportional Transaction Costs. Management Science 22, 1320–1331.
Coval, Joshua D.; Jakub W. Jurek and Erik Stafford. 2009. Economic Catastrophe Bonds. Am. Econ. Rev. 99, 628-666.
35
Dang, Tri Vi; Gary Gorton and Bengt Holmstrom. 2009. Opacity and the Optimality of Debt for Liquidity Provision. Unpublished Working Paper.
Denis, David J. 2011. Financial Flexibility and Corporate Liquidity. Journal of Corporate Finance 17, 667-674.
Denis, David J. and Stephen B. McKeon. 2012. Debt Financing and Financial Flexibility Evidence from Proactive Leverage Increases. Review of Financial Studies 25, 1897-1929.
Denis, David J. and Valeriy Sibilkov. 2010. Financial Constraints, Investment, and the Value of Cash Holdings. Review of Financial Studies 23, 247-269.
Desai, Mihir A.; C. Fritz Foley and James R. Hines Jr. 2006. The Demand for Tax Havens. Journal of Public Economics 90, 513-531.
Dharmapala, Dhammika; C. Fritz Foley and Kristin J. Forbes. 2011. Watch What I Do, Not What I Say: The Unintended Consequences of the Homeland Investment Act. The Journal of Finance 66, 753-787.
Dittmar, Amy; Jan Mahrt-Smith and Henri Servaes. 2003. International Corporate Governance and Corporate Cash Holdings. Journal of Financial and Quantitative Analysis 38, 111-133.
Duchin, Ran. 2010. Cash Holdings and Corporate Diversification. The Journal of Finance 65, 955-992.
Edwards, Alexander; Todd Kravet and Ryan Wilson. 2012. Permanently Reinvested Earnings and the Profitability of Cash Acquisitions. Unpublished Working Paper.
Eppen, Gary D. and Eugene F. Fama. 1968. Solutions for Cash-Balance and Simple Dynamic Portfolio Problems. The Journal of Business 41, 94-112.
Faulkender, Michael. 2005. Hedging Or Market Timing? Selecting the Interest Rate Exposure of Corporate Debt. The Journal of Finance 60, 931-962.
Faulkender, Michael and Rong Wang. 2006. Corporate Financial Policy and the Value of Cash. The Journal of Finance 61, 1957-1990.
Flannery, Mark J. 1981. Market Interest Rates and Commercial Bank Profitability: An Empirical Investigation. The Journal of Finance 36, 1085-1101.
Foley, C. Fritz; Jay C. Hartzell, Sheridan Titman and Garry Twite. 2007. Why Do Firms Hold So Much Cash: A Tax-Based Explanation. J. Financ. Econ. 86, 579-607.
Frazer, William J., Jr. 1958. Large Manufacturing Corporations as Suppliers of Funds to the United States Government Securities Market. The Journal of Finance 13, 499-509.
Frenkel, Jacob A. and Boyan Jovanovic. 1980. On Transactions and Precautionary Demand for Money. Quarterly Journal of Economics 95, 25–43.
Gamba, Andrea and Alexander Triantis. 2008. The Value of Financial Flexibility. The Journal of Finance 63, 2263-2296.
Getmansky, Mila. 2004. The Life Cycle of Hedge Funds: Fund Flows, Size, and Performance. Unpublished Working Paper.
Gorton, Gary B.; Stefan Lewellen and Andrew Metrick. 2012. The Safe Asset Share. Unpublished Working Paper.
Graham, John R. 1996. Proxies for the Corporate Marginal Tax Rate. J. Financ. Econ. 42, 187-221.
Graham, John R.; Michelle Hanlon and Terry Shevlin. 2011. Real Effects of Accounting Rules: Evidence from Multinational Firms’ Investment Location and Profit Repatriation Decisions. Journal of Accounting Research 49, 137-185.
36
Graham, John R. and Hyunseob Kim. 2009. The Effects of the Length of the Tax-Loss Carryback Period on Tax Receipts and Corporate Marginal Tax Rates. Unpublished Working Paper.
Grove, M. A. 1974. On “Duration” and the Optimal Maturity Structure of the Balance Sheet. The Bell Journal of Economics and Management Science 5, 696-709.
Hadlock Charles J. and Joshua R. Pierce. 2010. New Evidence on Measuring Financial Constraints: Moving Beyond the KZ Index. Review of Financial Studies 23, 1909-1940.
Harford, Jarrad; Sattar A. Mansi and William F. Maxwell. 2008. Corporate Governance and Firm Cash Holdings in the U.S.. J. Financ. Econ. 87, 535-555.
Harris, David; Randall Morck, Joel Slemrod and Bernard Yeung. 1993. Income Shifting in U.S. Multinational Corporations. In: Giovanni, A., Hubbard, R. G., Slemrod, J. (Eds). Studies in International Taxation, 277-307. The University of Chicago Press, Chicago.
Haugen, Robert and Lemma Senbet. 1978. The Insignificance of Bankruptcy Costs to the Theory of Optimal Capital Structure. The Journal of Finance 23, 383-393.
Hausman, J. 1978. Specification Tests in Econometrics. Econometrica 46, 1251-1271. Heston, Alan W. 1962. An Empirical Study of Cash, Securities and Other Current Accounts of
Large Corporations,” Yale Economic Essay, II, 117-159. Hines Jr., James H. and Eric M. Rice, 1994. Fiscal Paradise: Foreign Tax Havens and American
Business. Quarterly Journal of Economics 109, 149–182. Hoevenaars, Roy; Roderick Molenaar, Peter Schotman and Tom Steenkamp. 2008. Strategic
Asset Allocation with Liabilities: Beyond Stocks and Bonds. Journal of Economic Dynamics and Control 32, 2939-2970.
Jacobs, Donald P. 1960. The Marketable Security Portfolios of Non-Financial Corporations, Investment Practices and Trends. The Journal of Finance 15, 341-352.
Jagannathan, Murali, Clifford P Stephens, and Michael S Weisbach. 2000. Financial Flexibility and the Choice Between Dividends and Stock Repurchases. J. Financ. Econ. 57, 355–384.
Jeffers, James R. and Jene Kwon. 1969. A Portfolio Approach to Corporate Demands for Government Securities. The Journal of Finance 24, 905-919.
Jensen, Michael C. 1986, Agency Costs of the Free Cash Flow, Corporate Finance and Takeovers. American Economic Review 76, 323–329.
Kaplan, Steven N., and Luigi Zingales. 1997. Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financial Constraints? Quarterly Journal of Economics 112, 169–215.
Keynes, John M. 1936. The General Theory of Employment, Interest and Money. Macmillan: New York, NY.
Krishnamurthy, Arvind and Annette Vissing-Jorgensen. 2010. The Aggregate Demand for Treasury Debt. Unpublished Working Paper.
Krishnamurthy, Arvind and Annette Vissing-Jorgensen. 2012. Short-Term Debt and Financial Crises: What We Can Learn from US Treasury Supply. Unpublished Working Paper.
Lins, Karl V., Henri Servaes, and Peter Tufano. 2010. What Drives Corporate Liquidity? An International Survey of Cash Holdings and Lines of Credit. J. Financ. Econ. 98, 160-176.
Lintner, J. 1956. Distribution of Incomes of Corporations among Dividends, Retained Earnings, and Taxes. American Economic Review 46, 97-113.
Lucas, Robert E. 1978. Asset Prices in an Exchange Economy. Econometrica 46, 1429-1445. Maddala, G. S. and Robert C. Vogel. 1967. Cross-Section Estimates of Liquid asset Demand by
Manufacturing Corporations. The Journal of Finance 22, 557-575. McLean, David T. 2011. Share Issuance and Cash Savings. J. Financ. Econ. 99, 693-715.
37
Miller, Merton H., and Daniel Orr, 1966. A Model of the Demand for Money by Firms. Quarterly Journal of Economics 80, 413–435.
Miller, Merton H., and Daniel Orr, 1967. An Application of Control Limit Models to the Management of Corporate Cash Balances. In: Robichek, A. A. (Ed). Financial Research and Management Decisions, 277-307. John Wiley and Sons, New York.
Miller, Merton H., and Daniel Orr, 1968. The Demand for Money by Firms: Extensions of Analytic Results. The Journal of Finance 23, 735-759.
Modigliani, F., and Merton Miller. 1958. The Cost of Capital, Corporation Finance, and the Theory of Investment. American Economic Review 48, 261−297.
Opler, Tim; Lee Pinkowitz; René Stulz and Rohan Williamson. 1999. The Determinants and Implications of Corporate Cash Holdings. J. Financ. Econ. 52, 3-46.
Ouimet, Paige Parker. 2013. What Motivates Minority Acquisitions? The Trade-Offs between a Partial Equity Stake and Complete Integration. Review of Financial Studies 26, 1021-1047.
Patinkin, Don. 1956. Money, Interest, and Prices. Row Peterson, Evanston. Pinkowitz Lee and Rohan Williamson. 2001. Bank Power and Cash Holdings: Evidence from
Japan. Review of Financial Studies 14, 1059-1082. Rajan, Raghuram G. 2010. Fault Lines. Princeton University Press: Princeton, NJ. Rauh, Joshua D. 2009. Risk Shifting versus Risk Management: Investment Policy in Corporate
Pension Plans. Review of Financial Studies 22, 2687-2733. Rosen, Dan and Stavros A. Zenios. 2006. Enterprise-Wide Asset and Liability Management:
Issues, Institutions, and Models. In: Zenios, S. A., Ziemba, W. T. (Eds.). Handbook of Asset and Liability Management 1, 1-24, Elsevier. Holland.
Scott, James H., Jr. 1979. The Tax Effects of Investment in Marketable Securities on Firm Valuation. The Journal of Finance 34, 307-324.
Selden, Richard T. 1961. The Postwar Rise in the Velocity of Money a Sectoral Analysis. The Journal of Finance 16, 483-545.
Shevlin, Terry. 1990. Estimating Corporate Marginal Tax Rates with Asymmetric Tax Treatment of Gains and Losses. The Journal of the American Taxation Association 11, 51-67.
Shleifer, Andrei and Robert Vishny. 1992. Liquidation Values and Debt Capacity: A Market Equilibrium Approach. The Journal of Finance 47, 1343-1366.
Smith, Clifford W. and Rene M. Stulz. 1985. The Determinants of Firms' Hedging Policies. The Journal of Financial and Quantitative Analysis 20, 391-405.
Sprenkle, Case M. 1969. The Uselessness of Transactions Demand Models. The Journal of Finance 24, 835-847.
Stein, Jeremy. 2003. Agency, Information, and Corporate Investment. In: Constantinides, G. M., Harris, M., Stulz, R. (Eds.). Handbook of Economics and Finance 1, 111-165, Elsevier.
Stein, Jeremy C. 2012. Monetary Policy as Financial-Stability Regulation. Quarterly Journal of Economics 127, 57-95.
Sunderam, Adi. 2012. Money Creation and the Shadow Banking System. Unpublished Working Paper.
Tobin, James. 1955. A Dynamic Aggregative Model. Journal of Political Economy 63, 103-115. Tobin, James. 1956. The Interest Elasticity of the Transactions Demand for Cash. The Review of
Economics and Statistics 38, 241-247. Tobin, James. 1958. Liquidity Preference as Behavior Towards Risk. The Review of Economic
Studies 25, 65−86.
38
Tobin, James. 1969. A General Equilibrium Approach to Monetary Theory. Journal of Money, Credit and Banking 1, 15−29.
Wallas, G. E. 1959. Immunization. Journal of the Institute of Actuaries Students’ Society 15, 345-357.
White, H. 1982. Maximum-Likelihood Estimation of Misspecified Models. Econometrica 50, 1-25.
Yun, Hayong. 2009. The Choice of Corporate Liquidity and Corporate Governance. Review of Financial Studies 22, 1447-1475.
39
Table I. Aggregate Cash and Corporate Market Investments by Asset Class:
Period Means The table provides time-series means of aggregate balance sheet items (cash, financial assets, and tangible assets) for nonfarm nonfinancial corporations in the US economy. The full period is 1945 to 2005 (Federal Reserve Board of Governors) and is divided into three sub-periods: Period 1 (1945 to 1964), Period 2 (1965 to 1984), and Period 3 (1985 to 2005). All nominal balance sheet items are converted to 2005 dollars using the Consumer Price Index. Foreign deposits are deposits, including negotiable certificates of deposit, held in foreign financial institutions. Checkable deposits consist of demand deposits, negotiable order of withdrawal (NOW) accounts and automatic transfer service (ATS) accounts. Currency is US currency and coin. Time and savings deposits are deposits that depositors may withdraw after giving prior notice. Money market mutual funds are open-end investment companies that invest in short-term, liquid assets, including short-term municipal securities. A security repurchase agreement is an agreement to sell an asset, in many cases a federal government security, accompanied simultaneously by an agreement that the seller will repurchase the asset at a later date at a higher price. Commercial paper consists of short-term unsecured promissory notes issued by financial and nonfinancial borrowers. US Treasury securities are marketable and securities issued by the Department of the Treasury. US Govt. agency securities are issued by various federal agencies, other than the Treasury. Municipal securities and loans are obligations issued primarily by state and local governments. Mortgages are loans that are secured in whole or in part by real property. Mutual fund shares are obligations issued by mutual funds; the category excludes money market mutual fund shares. Equity in government-sponsored enterprises (GSE) is equity ownership in Fannie Mae, the Farm Credit System, and the Federal Home Loan Banks. Unidentified miscellaneous claims are obtained directly as the total amount reported by original sources as ‘‘other’’ financial assets. Consumer credit consists of short-term and intermediate-term loans to individuals. Trade credits are accounts receivable arising from the sale of business-related goods and services. Foreign direct investment is the acquisition of equity in, and the provision of loans to, US affiliates of foreign firms by the purchase of tangible or financial assets of US firms or the direct ownership of their equity shares; the 10 percent threshold that distinguishes direct investment from portfolio investment. Insurance receivables are deferred and unpaid life insurance premiums. Investment in finance company (FC) subsidiaries is the acquisition of equity ownership in the subsidiary companies. Among these subsidiaries companies are the subsidiaries of motor vehicle manufacturers and the credit subsidiaries of major retailers.
Period 1: 1945 - 1964 Period 2: 1965 - 1984 Period 3: 1985 - 2005
Time-Series Means Time-Series Means Time-Series Means
Amount % of % of Amount % of % of Amount % of % of
(in $BN,
2005) TANA MINV (in $BN,
2005) TANA MINV (in $BN,
2005) TANA MINV
Cash and cash equivalents 215.439 11.388 150.347 313.734 7.351 101.794 622.362 9.044 17.555
Foreign deposits 1.463 0.062 0.996 15.034 0.335 3.365 30.481 0.454 0.934
Checkable deposits and currency 199.971 10.681 139.678 198.228 4.744 73.831 238.026 3.646 7.796
Time and savings deposits 13.908 0.642 9.612 83.067 1.887 20.577 211.936 3.028 5.684
Money market funds 0.000 0.000 0.000 7.863 0.163 0.755 136.151 1.830 2.961
Security repurchase agreement 0.097 0.003 0.061 9.542 0.223 3.267 5.769 0.086 0.180
Market investments (MINV) 145.712 7.804 100.000 563.529 12.324 100.000 3689.712 53.040 100.000
Commercial paper 3.138 0.136 2.174 33.279 0.789 12.498 44.203 0.622 1.129
US Treasury securities 122.241 6.790 83.972 45.351 1.093 16.207 51.072 0.811 1.849
US Govt. agency securities 3.152 0.125 2.143 7.935 0.187 2.571 15.165 0.225 0.450
Municipal securities and loans 9.941 0.452 6.822 20.377 0.480 6.734 42.946 0.668 1.463
Mortgages 0.270 0.013 0.190 30.887 0.653 3.579 75.553 1.179 2.618
Mutual funds 0.199 0.007 0.132 4.154 0.095 1.258 73.707 1.021 1.774
Equity in GSE 0.183 0.007 0.125 0.210 0.006 0.156 0.000 0.000 0.000
Unidentified misc. investments 6.587 0.274 4.440 421.335 9.021 56.997 3387.067 48.514 90.717
Other identified financial assets 628.988 30.657 435.359 1823.302 42.312 563.670 3167.489 46.776 93.551
Consumer credit 57.595 2.902 39.944 77.486 1.857 28.662 89.702 1.383 2.981
Trade credit 406.469 19.887 281.456 1061.831 24.772 342.180 1637.159 24.434 49.815
Foreign direct investment 145.623 6.975 100.587 599.828 13.771 170.714 1193.288 17.257 33.156
Insurance receivables 193.019 0.893 13.373 75.988 1.739 21.204 218.306 3.273 6.724
Investment in FC subsidiaries 0.000 0.000 0.000 8.169 0.172 0.910 29.034 0.429 0.875
Tangible assets (TANA) 1996.542 100.000 1386.685 4271.995 100.000 1394.026 6687.987 100.000 204.772
Total assets 2986.682 149.850 2072.392 6972.560 161.986 2159.489 14200.000 208.860 415.878
Figure I. Real Amount of Market Investments by Asset Class The figure presents the amounts of aggregate market investments for nonfarm nonfinancial corporations in the US economy (Federal Reserve Board of Governors). All nominal items are converted to 2005 dollars using the Consumer Price Index. Commercial paper consists of short-term unsecured promissory notes issued by financial and nonfinancial borrowers. US Treasury securities are marketable and securities issued by the Department of the Treasury. US Govt. agency securities are issued by various federal agencies, other than the Treasury. Municipal securities and loans (Munis) are obligations issued primarily by state and local governments. Mortgages are loans that are secured in whole or in part by real property. Mutual fund shares are obligations issued by mutual funds; the category excludes money market mutual fund shares. Equity in government-sponsored enterprises (GSE) is equity ownership in Fannie Mae, the Farm Credit System, and the Federal Home Loan Banks.
050
100
150
200
Amount in Billions of 2005 US Dollars
1945 1955 1965 1975 1985 1995 2005Year
US Treasury Commercial Paper
Munis Govt Agency
Mortgages Mutual Funds & GSE Equity
Market Investments by Asset Class
42
Figure II. Market Investment Portfolio Composition The figure presents the classes of aggregate market investments for nonfarm nonfinancial corporations in the US economy as a percentage of total aggregate market investments (Federal Reserve Board of Governors). All nominal items are converted to 2005 dollars using the Consumer Price Index. Commercial paper consists of short-term unsecured promissory notes issued by financial and nonfinancial borrowers. US Treasury securities are marketable and securities issued by the Department of the Treasury. US Govt. agency securities are issued by various federal agencies, other than the Treasury. Municipal securities and loans (Munis) are obligations issued primarily by state and local governments. Mortgages are loans that are secured in whole or in part by real property. Mutual fund shares are obligations issued by mutual funds; the category excludes money market mutual fund shares. Equity in government-sponsored enterprises (GSE) is equity ownership in Fannie Mae, the Farm Credit System, and the Federal Home Loan Banks. Unidentified miscellaneous claims (other investments) are obtained directly as the total amount reported by original sources as ‘‘other’’ financial assets.
020
40
60
80
100
% of Total Market Investm
ents
1945 1955 1965 1975 1985 1995 2005Year
US Treasury Other Investments
Commercial Paper Munis
Govt Agency Mortgages
Mutual Funds & GSE Equity
Market Investments by Asset Class
43
Exhibit I. An Example: Google The exhibit presents Note 3 from the 10-K filing for Google Inc for the annual period ended December 31, 2011. It presents amounts for the firm’s various liquid assets. These amounts are from the December 2010 and December 2011 fiscal years (in millions of US dollars). Cash consists of demand deposits, physical currency and coin. US government agencies are securities issued by various federal agencies, other than the Treasury. Time deposits are deposits that depositors may withdraw after giving prior notice. Money market mutual funds are open-end investment companies that invest in short-term, liquid assets, including short-term municipal securities. US government notes are marketable securities issued by the Department of the Treasury. Foreign government bonds are obligations issued by foreign governments. Municipal securities are obligations issued primarily by state and local governments. Corporate debt securities are obligations issued by corporations. Agency residential mortgage-backed securities are claims on cash flows from residential mortgages. Marketable equity securities consist of equity or stock investments.
As of December 31,
2010
2011
Cash and cash equivalents: Cash $ 4,652 $ 4,712 Cash equivalents:
Time deposits
973
534 Money market and other funds 7,547 4,462 U.S. government agencies
0
275
U.S. government notes 300 0 Foreign government bonds
150
0
Corporate debt securities 8 0
Total cash and cash equivalents
13,630
9,983
Marketable securities: Time deposits
307
495
U.S. government agencies 1,857 6,226 U.S. government notes
3,930
11,579
Foreign government bonds 1,172 1,629 Municipal securities
2,503
1,794
Corporate debt securities 5,742 6,112 Agency residential mortgage-backed securities
5,673
6,501
Marketable equity securities 161 307
Total marketable securities
21,345
34,643
Total cash, cash equivalents, and marketable securities $ 34,975 $ 44,626
44
Table II. Corporate Market Investments: Definitions and Summary Statistics The table provides summary statistics for observations in the sample. The sample period is 1971 to 2006. All nominal balance sheet items are converted to 2006 dollars using the Consumer Price Index. Market investments is short-term investments plus noncurrent investments using the equity and market methods. Cash is cash holdings. Liquid assets is the sum of Cash and Market investments. Capital expenditure is capital investments. Cash flow is EBITDA minus interest minus taxes minus common dividends. New financing is equal to total equity issuance minus repurchases plus debt issuance minus debt redemption. Repurchases is the net repurchase of common shares and preferred stock. Interest expense is the interest expense of the firm. Short-term debt ratio is current liabilities divided by the sum of current liabilities and long-term debt. Dividend payout is equal to common dividend paid. Market-to-book ratio is total assets minus cash minus current market investments minus noncurrent investments using the equity and market methods minus book value of equity plus the market value of equity, all normalized. Repatriation tax is the tax costs of repatriating earnings (Foley et al., 2007). Pension expense is the pension expense of the firm. In Table A.II, all aforementioned variables are normalized by total assets minus the book value of equity plus the market value of equity minus cash minus current market investments minus noncurrent investments using the equity and market methods. In other tables, all aforementioned variables are normalized by total assets minus cash minus current market investments minus noncurrent investments using the equity and market methods. Size is the market value of equity. Leverage is market leverage. R & D expense is the research and development expenditures of the firm divided by sales. Marginal tax rate is the trichotomous variable for corporate tax rate (Graham, 1996). Toehold is equal to one if the firm acquires or merges with another firm in year t+1, and zero otherwise. Multiple segment is equal to one if the firm has more than one segment, and zero otherwise. LDI Index is the first principal component factor of Dividend payout and Pension expense.
Variable Name Mean sd. N Q50
Market investments 0.213 0.797 108864 0.016
Cash 0.192 0.582 108864 0.043
Capital expenditure 0.096 0.104 108864 0.062
Size 839.341 2851.850 108864 82.288
Cash flow -0.062 0.594 108864 0.068
Leverage 0.295 0.248 108864 0.237
New financing 0.190 0.792 108864 0.008
Market-to-book ratio 2.485 4.466 108864 1.317
R & D expense 0.120 0.607 108864 0.000
Marginal tax rate 33.522 11.308 108864 35.000
Repurchases -0.018 0.133 108864 0.000
Short-term debt ratio 0.320 0.319 108864 0.197
Interest expense 0.033 0.038 108864 0.024
Dividend payout 0.009 0.020 108864 0.000
45
Table III. Cash and Corporate Market Investments
The table presents regression results for the sample where the dependent variables are the logarithm of Cash in columns (1) and (2), the excess logarithm of Cash in column (3), the ratio of Market investments to Liquid assets in column (4), and the logarithm of Market investments in columns (5) and (6). Variable definitions are presented in Table II.
Log(Cash)
Fama-
Macbeth
Log(Cash)
Excess
Log(Cash)
Market
Investments/
L. Assets
Tobit
Log(Market
Investments)
Log(Market
Investments)
Log (Size) -0.177 -0.208 -0.012 0.084 1.735 1.086
(12.306)** (16.736)** (1.763)+ (25.861)** (26.103)** (25.245)**
Cash flow 0.005 -0.014 -0.027 -0.017 -0.238 -0.138
(0.229) (0.272) (2.211)* (5.412)** (3.063)** (2.558)*
Leverage -0.547 -0.535 -0.024 0.003 -0.351 -0.256
(41.630)** (11.916)** (3.990)** (0.962) (5.723)** (6.835)**
New financing 0.354 0.302 0.006 -0.005 0.248 0.205
(29.560)** (13.660)** (0.903) (2.578)** (4.899)** (5.598)**
Market-to-book ratio 0.249 0.290 -0.040 -0.001 0.133 0.153
(17.263)** (16.907)** (5.312)** (0.393) (2.050)* (3.272)**
R & D expense 0.110 -0.105 0.144 0.014 0.397 0.298
(8.633)** (1.655) (17.913)** (5.767)** (7.190)** (7.500)**
Cash 0.094 0.071
(1.350) (1.428) Payout, Interest and
Investment (PII)
Repurchases -0.016 -0.007 0.001 0.036 0.027
(1.639) (1.303) (0.446) (0.781) (0.955)
Short-term debt ratio 0.030 0.040 0.003 0.131 0.100
(2.481)* (6.992)** (1.185) (2.324)* (2.855)** Short-term debt
ratio* -0.203 -0.118 0.002 -0.246 -0.166
Interest expense (12.835)** (13.508)** (0.809) (3.725)** (3.915)**
Interest expense 0.249 0.182 0.020 0.508 0.380
(15.502)** (18.328)** (6.544)** (7.578)** (8.362)**
Marginal tax rate -0.052 -0.037 -0.008 -0.262 -0.170
(4.670)** (7.159)** (3.369)** (4.924)** (5.134)**
Capital expenditure 0.049 0.047 0.007 0.176 0.128
(4.780)** (10.239)** (3.737)** (4.021)** (4.483)**
Dividend payout -0.011 0.000 0.025 0.332 0.253
(0.701) (0.021) (8.733)** (5.930)** (6.543)**
Number of obs. 108864 124718 108864 108307 108864 108864
Model p-value 0.000 0.000 0.000 0.000 0.000 0.000 The sample period is 1971 to 2006. The coefficients are estimated using OLS in columns (1), (3), (4) and (6); Fama-Macbeth in column (2); a Tobit model in column (5). All regressions other than column (2) use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses. The Model p-value shows the result for a test that all of the listed coefficients are jointly zero. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
46
Table IV. Comparing Cash to Corporate Market Investments The table presents regression results for the sample where the dependent variables are the logarithm of Cash in column (1) the excess logarithm of Cash in column (2) and the logarithm of Market investments in column (3). Variable definitions are presented in Table II.
(1) (2) (3) (3) - (1) (3) - (2)
Log(Cash)
Excess
Log(Cash)
Log(Market
Investments) Cash
Comparison
E. Cash
Comparison
Log (Size) -0.177 -0.012 1.085 1.262 1.097
(12.306)** (1.763)+ (25.206)** [0.000]** [0.000]**
Cash flow 0.005 -0.027 -0.147 -0.152 -0.120
(0.229) (2.211)* (2.724)** [0.004]** [0.019]*
Leverage -0.547 -0.024 -0.260 0.287 -0.236
(41.630)** (3.990)** (6.974)** [0.000]** [0.000]**
New financing 0.354 0.006 0.234 -0.120 0.228
(29.560)** (0.903) (7.238)** [0.000]** [0.000]**
Market-to-book ratio 0.249 -0.040 0.163 -0.086 0.203
(17.263)** (5.312)** (3.538)** [0.068]+ [0.000]**
R & D expense 0.110 0.144 0.300 0.190 0.156
(8.633)** (17.913)** (7.542)** [0.000]** [0.000]** Payout, Interest and
Investment (PII)
Repurchases -0.016 -0.007 0.029 0.045 0.036
(1.639) (1.303) (1.004) [0.108] [0.194]
Short-term debt ratio 0.030 0.040 0.101 0.071 0.061
(2.481)* (6.992)** (2.895)** [0.041]* [0.071]+
Short-term debt ratio* -0.203 -0.118 -0.168 0.035 -0.050
Interest expense (12.835)** (13.508)** (3.963)** [0.420] [0.222]
Interest expense 0.249 0.182 0.383 0.134 0.201
(15.502)** (18.328)** (8.407)** [0.003]** [0.000]**
Marginal tax rate -0.052 -0.037 -0.170 -0.118 -0.133
(4.670)** (7.159)** (5.121)** [0.000]** [0.000]**
Capital expenditure 0.049 0.047 0.128 0.079 0.081
(4.780)** (10.239)** (4.473)** [0.006]** [0.004]**
Dividend payout -0.011 0.000 0.253 0.264 0.253
(0.701) (0.021) (6.548)** [0.000]** [0.000]**
Avg. diff: cash eta-sq 0.242 0.118
Number of obs. 108864 108864 108864
Adj. R-squared 0.214 0.104 0.135 The sample period is 1971 to 2006. Column (4) presents the difference in coefficients between columns (3) and (1); column (5) presents the difference in coefficients between columns (3) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2) and (3). The p-values for a generalized Hausman test are reported in brackets in columns (4) and (5); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for all variables (column 5) or the PII variables (column 6) is calculated using eta-squared weights for the respective cash regressions. The Model p-value shows the result for a test that all of the listed coefficients are jointly zero. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
47
Table V. A Natural Experiment: Repatriation The table presents regression results by Repatriation tax (median cut) for the sample where the dependent variables are the excess logarithm of Cash in columns (1) and (2) and the logarithm of Market investments in columns (3) and (4). Variable definitions are presented in Table II.
(1) (2) (3) (4) (3) - (1) (4) - (2) No Tax
Excess
Log(Cash)
Tax
Excess
Log(Cash)
No Tax
Log(Market
Investments)
Tax
Log(Market
Investments) No Tax
Comparison
Tax
Comparison
Log (Size) -0.019 0.014 1.045 1.439 1.064 1.425
(2.601)** (0.714) (23.212)** (11.627)** [0.000]** [0.000]**
Cash flow -0.037 0.209 -0.146 -0.151 -0.109 -0.360
(2.907)** (1.862)+ (2.584)** (0.369) [0.042]* [0.313]
Leverage -0.022 -0.110 -0.278 -0.053 -0.256 0.057
(3.401)** (4.162)** (7.053)** (0.364) [0.000]** [0.682]
New financing 0.005 -0.020 0.245 0.122 0.240 0.142
(0.681) (0.290) (7.301)** (0.462) [0.000]** [0.557]
Market-to-book ratio -0.050 0.159 0.128 0.976 0.178 0.817
(6.313)** (4.102)** (2.687)** (4.891)** [0.002]** [0.000]**
R & D expense 0.136 0.383 0.283 0.922 0.147 0.539
(16.657)** (3.572)** (7.024)** (2.522)* [0.002]** [0.090]+ Payout, Interest and
Investment (PII)
Repurchases -0.006 -0.018 0.036 -0.084 0.042 -0.066
(1.023) (0.690) (1.205) (0.694) [0.149] [0.562]
Short-term debt ratio 0.035 0.058 0.079 0.224 0.044 0.166
(5.716)** (3.245)** (2.137)* (1.935)+ [0.221] [0.147]
Short-term debt ratio* -0.113 -0.089 -0.160 -0.069 -0.047 0.020
Interest expense (12.046)** (2.223)* (3.592)** (0.361) [0.274] [0.912]
Interest expense 0.176 0.262 0.358 0.318 0.182 0.056
(16.585)** (5.766)** (7.380)** (1.724)+ [0.001]** [0.741]
Marginal tax rate -0.039 -0.073 -0.167 -0.154 -0.128 -0.081
(6.941)** (3.963)** (4.707)** (1.339) [0.000]** [0.472]
Capital expenditure 0.049 0.070 0.145 0.131 0.096 0.061
(10.004)** (3.046)** (4.835)** (0.930) [0.001]** [0.662]
Dividend payout 0.003 -0.011 0.273 0.148 0.270 0.159
(0.343) (0.451) (6.447)** (1.257) [0.000]** [0.169]
Avg. diff: cash eta-sq 0.109 0.000
Number of obs. 89147 7239 89147 7239
Adj. R-squared 0.109 0.146 0.135 0.143 The sample period is 1971 to 2006. Column (5) presents the difference in coefficients between columns (3) and (1); column (6) presents the difference in coefficients between columns (4) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2), (3) and (4). The p-values for a generalized Hausman test are reported in brackets in columns (5) and (6); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for the PII variables is calculated using eta-squared weights for the respective cash regressions. The adjusted R-squared measures the fit. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
48
Table VI. Corporate Market Investments and Acquisitions The table presents regression results by Toehold status for the sample where the dependent variables are the excess logarithm of Cash in columns (1) and (2) and the logarithm of Market investments in columns (3) and (4). Variable definitions are presented in Table II.
(1) (2) (3) (4) (3) - (1) (4) - (2) No Merger
Excess
Log(Cash)
Acquirers
Excess
Log(Cash)
No Merger
Log(Market
Investments)
Acquirers
Log(Market
Investments) No Merger
Comparison
Acquirers
Comparison
Log (Size) -0.009 -0.034 0.991 1.336 1.000 1.370
(1.272) (2.804)** (22.077)** (19.320)** [0.000]** [0.000]**
Cash flow -0.049 0.048 -0.158 -0.352 -0.109 -0.400
(3.868)** (1.736)+ (2.804)** (2.761)** [0.041]* [0.001]**
Leverage -0.010 -0.124 -0.300 -0.073 -0.290 0.051
(1.614) (8.328)** (7.771)** (0.949) [0.000]** [0.496]
New financing -0.003 0.041 0.202 0.288 0.205 0.247
(0.448) (2.331)* (5.650)** (3.857)** [0.000]** [0.000]**
Market-to-book ratio -0.055 -0.003 0.116 0.340 0.171 0.343
(6.771)** (0.217) (2.285)* (4.278)** [0.001]** [0.000]**
R & D expense 0.141 0.171 0.292 0.450 0.151 0.279
(17.053)** (8.933)** (6.993)** (5.439)** [0.000]** [0.000]** Payout, Interest and
Investment (PII)
Repurchases -0.007 -0.016 0.019 0.081 0.026 0.097
(1.265) (1.327) (0.637) (1.426) [0.371] [0.073]+
Short-term debt ratio 0.028 0.086 0.032 0.367 0.004 0.281
(4.737)** (7.489)** (0.863) (5.583)** [0.920] [0.000]**
Short-term debt ratio* -0.104 -0.219 -0.136 -0.277 -0.032 -0.058
Interest expense (11.711)** (8.739)** (3.084)** (2.586)** [0.451] [0.567]
Interest expense 0.166 0.282 0.378 0.346 0.212 0.064
(16.034)** (12.110)** (7.816)** (3.932)** [0.000]** [0.457]
Marginal tax rate -0.036 -0.041 -0.158 -0.235 -0.122 -0.194
(6.774)** (3.814)** (4.576)** (3.665)** [0.000]** [0.002]**
Capital expenditure 0.043 0.074 0.113 0.243 0.070 0.169
(9.102)** (6.655)** (3.853)** (3.712)** [0.016]* [0.007]**
Dividend payout 0.004 -0.010 0.293 0.096 0.289 0.106
(0.495) (0.870) (7.195)** (1.561) [0.000]** [0.084]+
Avg. diff: cash eta-sq 0.121 0.077
Number of obs. 88624 20240 88624 20240
Adj. R-squared 0.109 0.117 0.133 0.162 The sample period is 1971 to 2006. Column (5) presents the difference in coefficients between columns (3) and (1); column (6) presents the difference in coefficients between columns (4) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2), (3) and (4). The p-values for a generalized Hausman test are reported in brackets in columns (5) and (6); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for the PII variables is calculated using eta-squared weights for the respective cash regressions. The adjusted R-squared measures the fit. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
49
Table VII. The Role of Firm Size The table presents regression results by Size (median cut) for the sample where the dependent variables are the excess logarithm of Cash in columns (1) and (2) and the logarithm of Market investments in columns (3) and (4). Variable definitions are presented in Table II.
(1) (2) (3) (4) (3) - (1) (4) - (2) Small
Excess
Log(Cash)
Large
Excess
Log(Cash)
Small
Log(Market
Investments)
Large
Log(Market
Investments) Small
Comparison
Large
Comparison
Log (Size) 0.033 -0.073 0.589 1.397 0.556 1.470
(2.507)* (6.074)** (6.956)** (18.463)** [0.000]** [0.004]**
Cash flow -0.137 0.115 -0.341 -0.125 -0.204 -0.240
(9.249)** (5.587)** (5.359)** (1.412) [0.001]** [0.005]**
Leverage -0.015 -0.048 -0.429 -0.221 -0.414 -0.173
(2.234)* (4.196)** (9.629)** (3.476)** [0.000]** [0.000]**
New financing -0.002 0.004 0.143 0.265 0.145 0.261
(0.169) (0.404) (3.064)** (6.168)** [0.002]** [0.000]**
Market-to-book ratio -0.146 0.003 -0.287 0.298 -0.141 0.295
(12.044)** (0.275) (3.716)** (5.657)** [0.066]+ [0.000]**
R & D expense 0.117 0.186 0.145 0.509 0.028 0.323
(12.523)** (16.217)** (2.951)** (10.584)** [0.561] [0.000]** Payout, Interest and
Investment (PII)
Repurchases -0.017 -0.011 0.038 -0.054 0.055 -0.043
(2.886)** (1.073) (1.206) (1.122) [0.076]+ [0.346]
Short-term debt ratio 0.012 0.065 -0.049 0.205 -0.061 0.140
(1.661)+ (7.730)** (1.103) (4.008)** [0.161] [0.005]**
Short-term debt ratio* -0.094 -0.082 -0.128 -0.123 -0.034 -0.041
Interest expense (9.919)** (3.576)** (2.638)** (1.436) [0.483] [0.613]
Interest expense 0.146 0.225 0.389 0.423 0.243 0.198
(12.597)** (14.186)** (7.132)** (5.730)** [0.000]** [0.004]**
Marginal tax rate -0.023 -0.060 -0.121 -0.238 -0.098 -0.178
(3.854)** (6.922)** (3.044)** (4.603)** [0.013]* [0.000]**
Capital expenditure 0.035 0.057 0.113 0.151 0.078 0.094
(6.799)** (7.210)** (3.432)** (3.247)** [0.017]* [0.036]*
Dividend payout 0.034 -0.005 0.394 0.181 0.360 0.186
(2.899)** (0.635) (6.445)** (3.910)** [0.000]** [0.000]**
Avg. diff: cash eta-sq 0.140 0.164
Number of obs. 57731 51133 57731 51133
Adj. R-squared 0.129 0.129 0.139 0.139 The sample period is 1971 to 2006. Column (5) presents the difference in coefficients between columns (3) and (1); column (6) presents the difference in coefficients between columns (4) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2), (3) and (4). The p-values for a generalized Hausman test are reported in brackets in columns (5) and (6); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for the PII variables is calculated using eta-squared weights for the respective cash regressions. The adjusted R-squared measures the fit. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
50
Table VIII. Corporate Market Investments: LDI and General Investment The table presents coefficient differences by LDI index (median cut) and Capital expenditure (median cut) for the sample where the dependent variables are the excess logarithm of Cash in and the logarithm of Market investments. Variable definitions are presented in Table II.
Low LDI
Comparison
High LDI
Comparison
Low
Investment
Comparison
High
Investment
Comparison
Log (Size) 0.954 1.161 1.038 1.127
[0.000]** [0.000]** [0.000]** [0.000]**
Cash flow -0.173 -0.091 -0.302 0.017
[0.017]* [0.338] [0.001]** [0.784]
Leverage -0.365 -0.630 -0.314 -0.154
[0.000]** [0.000]** [0.000]** [0.001]**
New financing 0.159 0.129 0.130 0.265
[0.001]** [0.045]* [0.050]* [0.000]**
Market-to-book ratio 0.399 0.339 0.003 0.263
[0.000]** [0.000]** [0.962] [0.000]**
R & D expense 0.106 0.238 0.088 0.188
[0.052]+ [0.003]** [0.148] [0.000]**
Payout, Interest and Investment (PII)
Repurchases 0.122 0.031 0.040 0.021
[0.002]** [0.588] [0.262] [0.552]
Short-term debt ratio -0.020 0.151
[0.663] [0.001]**
Short-term debt ratio* -0.002 -0.102
Interest expense [0.978] [0.075]+
Interest expense 0.204 0.198
[0.000]** [0.000]**
Marginal tax rate -0.102 -0.246 -0.102 -0.182
[0.030]* [0.001]** [0.011]* [0.000]**
Capital expenditure 0.183 0.156
[0.000]** [0.012]*
Dividend payout 0.277 0.235
[0.000]** [0.000]**
Avg. diff: cash eta-sq 0.166 0.205 0.128 0.166
Number of obs. 41624 42030 54755 54109 The sample period is 1971 to 2006. All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. The p-values for a generalized Hausman test are reported in brackets; the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for the PII variables is calculated using eta-squared weights for the respective cash regressions. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
51
Appendix
13. Aggregate Market Investments and Aggregate Cash
Taking data from the Flow of Funds Accounts, Figure A.I shows that aggregate cash (as a
percentage of tangible assets) decreases with time for the years 1945 to 1974, then increases with
time for the years 1975 to 2008. In contrast to the evidence for cash, the evidence presented in
Figure A.II shows that aggregate market investment (as a percentage of tangible assets) is
roughly constant for the years 1945 to 1974, and then increases substantially from 1975 to 2008.
14. Further Robustness
This paper finds that the determinants of market investments are different from the determinants
of excess cash. This section explores the robustness of the finding. In particular, are the findings
in Table IV robust when matching on firm multiple-segment status? Are the results robust when
using an alternative normalization variable?
Multiple Business Segments
Firms with multiple segments often use internal capital markets as a matter of business
strategy. Moreover, some multiple-segment firms maintain finance-company segments to
facilitate consumer purchases. Therefore, one concern is that differences between market
investment and excess cash are driven by multiple-segment firms. To address this concern, Table
A.I investigates coefficient differences by multiple-segment status.
The average coefficient difference for single-segment firms is substantially less than the
average coefficient difference for multiple-segment firms. For multiple-segment firms,
coefficient differences exist for long-term interest expenses, the corporate tax rate, capital
expenditure, and dividend payout. However for single-segment firms, coefficient differences
exist for long-term interest expenses, capital expenditure, and dividend payout. For multiple-
52
segment firms, the excess-cash 65-weighted average difference in absolute coefficients is
approximately 24%. For single-segment firms, the excess-cash 65-weighted average difference
in absolute coefficients is approximately 14%. Hence the results are robust to heterogeneity
based on multiple business segments.
An Alternative Normalization Variable
For this paper’s main tests, the market investment variable is normalized by lagged net
assets (at book value). However market investments can be recorded at market value. This
difference in accounting might introduce an upward bias in the market investment variable
simply because of a firm’s accounting practices. As a robustness check, Table A.II investigates
the difference between excess cash and market investment using an alternative normalization
variable: the market value of net assets. The main results remain robust when using this
alternative normalization variable. In comparison to columns (4) and (5) of Table IV, the average
coefficient differences are greater in Table A.II, columns (4) and (5). When using the market
value of net assets as a normalization variable, the cash 65-weighted average difference in
absolute coefficients is approximately 26%; the excess-cash 65-weighted average difference in
absolute coefficients is approximately 41%.
15. A Case Study: The Regulation of Investments in Marketable Securities
Given existing regulation, can a firm make excessive market investments? What is the profile of
a firm that makes excessive market investments? To shed light on these questions, I present a
brief case study of National Presto Industries, a firm that was recently sued by the Securities and
Exchange Commission (SEC) for excessive market investments.
National Presto is a public corporation that sells small consumer appliances, adult
diapers, and ammunition. Its primary NAICS code corresponds to broad-woven fabric mills. For
53
the quarterly period ended April, 5, 2009 (unaudited), the firm has total assets of approximately
$343 million. The firm’s cash holding including cash equivalent securities is equal to
approximately $19.4 million. The firm’s total market investment (excluding cash equivalent
securities) is equal to approximately $130 million. Market investment as a percentage of net
assets is equal to approximately 61%. The firm’s market investment consists wholly of tax-
exempt securities.
National Presto found itself with a large amount of cash after a series of divestitures in
the 1970s and 1980s. The managers of the firm stated that they were seeking investment
opportunities and needed the cash to invest. Market investments made up 86% of total assets in
1994 and 92% of total assets in 1998. In 2002, the SEC filed a lawsuit against National Presto
declaring that the firm was an investment company as defined in Section 3(a)(1)(C) of the
Investment Company Act of 1940. Section 3(a)(1)(C) states that “the title, ‘investment
company,’ means any issuer which is engaged or proposes to engage in the business of investing,
reinvesting, owning, holding, or trading in securities, and owns or proposes to acquire
investment securities having a value exceeding 40 percentum of the value of such issuer’s total
assets (exclusive of Government securities and cash items) on an unconsolidated basis.”
In November, 2005, Judge Charles R. Norgle of the U.S. District Court for the Northern
District of Illinois ruled in the SEC’s favor. In the draft injunction, the SEC allowed for National
Presto to apply for an exemption, which other firms – such as Microsoft – had done. The judge
refused the draft; National Presto responded by registering as an investment company and
replaced enough of its existing portfolio with government securities to bring its market
investments below the 40% limit. Subsequent to the 2005 ruling, Presto fell out of compliance
54
with SEC reporting rules, which prompted the New York Stock Exchange (NYSE) to warn the
firm that it could be delisted from the exchange within a year.
In May 2007, the U.S. Court of Appeals for the Seventh Circuit reversed the 2005
decision. In doing so, the Seventh Circuit relied less on the asset-based test and more on the
judgment that investors were not misled by the firm’s behavior. National Presto’s CEO Maryjo
Cohen said in a statement, “…The court’s opinion is logical and well-reasoned and is a valuable
legal precedent which will no doubt be cited in future cases.”
55
Figure A.I. Aggregate Cash The figure presents aggregate cash holdings for nonfarm nonfinancial corporations in the US economy as a percentage of book value of tangible assets and the market value of tangible assets (Federal Reserve Board of Governors). All nominal items are converted to 2005 dollars using the Consumer Price Index.
05
10
15
20
Cash (% of Tangible Assets)
1945 1955 1965 1975 1985 1995 2005Year
Book Value Market Value
Aggregate Cash
56
Figure A.II. Aggregate Market Investments The figure presents aggregate market investments for nonfarm nonfinancial corporations in the US economy as a percentage of book value of tangible assets and the market value of tangible assets (Federal Reserve Board of Governors). All nominal items are converted to 2005 dollars using the Consumer Price Index. S & P 500 index is the index value at the close of the trading day.
0500
1000
1500
S & P 500 Index
020
40
60
80
Market Investm
ents (% of Tangible Assets)
1945 1955 1965 1975 1985 1995 2005Year
Book Value Market Value
S & P 500 index
Aggregate Market Investments
57
Table A.I. Multiple Business Segments The table presents regression results by Multiple segment status for the sample where the dependent variables are the excess logarithm of Cash in columns (1) and (2) and the logarithm of Market investments in columns (3) and (4). Variable definitions are presented in Table II.
(1) (2) (3) (4) (3) - (1) (4) - (2) Single
Excess
Log(Cash)
Multiple
Excess
Log(Cash)
Single
Log(Market
Investments)
Multiple
Log(Market
Investments) Single
Comparison
Multiple
Comparison
Log (Size) 0.006 -0.014 0.829 1.156 0.823 1.170
(0.623) (1.323) (13.666)** (16.826)** [0.000]** [0.000]**
Cash flow -0.021 0.003 -0.025 -0.381 -0.004 -0.384
(1.846)+ (0.098) (0.420) (2.628)** [0.944] [0.005]**
Leverage -0.097 -0.021 -0.373 -0.226 -0.276 -0.205
(12.293)** (1.760)+ (7.764)** (3.246)** [0.000]** [0.003]**
New financing -0.000 0.021 0.269 0.067 0.269 0.046
(0.042) (0.911) (7.633)** (0.601) [0.000]** [0.674]
Market-to-book ratio -0.074 -0.003 0.222 0.171 0.296 0.174
(9.425)** (0.134) (4.352)** (1.532) [0.000]** [0.123]
R & D expense 0.132 0.205 0.299 0.379 0.167 0.174
(17.062)** (4.835)** (7.101)** (2.917)** [0.000]** [0.147] Payout, Interest and
Investment (PII)
Repurchases -0.005 -0.026 0.062 0.035 0.067 0.061
(0.822) (1.918)+ (1.940)+ (0.580) [0.034]* [0.296]
Short-term debt ratio 0.030 0.054 0.177 0.237 0.147 0.183
(4.266)** (4.592)** (4.051)** (3.409)** [0.001]** [0.007]**
Short-term debt ratio* -0.106 -0.144 -0.230 -0.150 -0.124 -0.006
Interest expense (11.090)** (8.133)** (4.538)** (1.869)+ [0.012]* [0.947]
Interest expense 0.167 0.235 0.332 0.643 0.165 0.408
(15.367)** (11.005)** (5.967)** (7.518)** [0.002]** [0.000]**
Marginal tax rate -0.031 -0.035 -0.098 -0.177 -0.067 -0.142
(4.496)** (3.742)** (2.256)* (2.907)** [0.116] [0.018]*
Capital expenditure 0.054 0.027 0.181 0.177 0.127 0.150
(9.718)** (2.884)** (5.417)** (2.971)** [0.000]** [0.011]*
Dividend payout 0.009 0.006 0.147 0.310 0.138 0.304
(0.931) (0.534) (2.883)** (4.631)** [0.005]** [0.000]**
Avg. diff: cash eta-sq 0.140 0.241
Number of obs. 58207 29280 58207 29280
Adj. R-squared 0.124 0.090 0.116 0.149 The sample period is 1971 to 2006. Column (5) presents the difference in coefficients between columns (3) and (1); column (6) presents the difference in coefficients between columns (4) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2), (3) and (4). The p-values for a generalized Hausman test are reported in brackets in columns (5) and (6); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for the PII variables is calculated using eta-squared weights for the respective cash regressions. The adjusted R-squared measures the fit. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
58
Table A.II. Alternative Normalization: Market Value of N. Assets The table presents regression results for the sample where the dependent variables are the logarithm of Cash in column (1) the excess logarithm of Cash in column (2) and the logarithm of Market investments in column (3). Variable definitions are presented in Table II.
(1) (2) (3) (3) - (1) (3) - (2)
Log(Cash)
Excess
Log(Cash)
Log(Market
Investments) Cash
Comparison
E. Cash
Comparison
Log (Size) -0.253 -0.015 1.101 1.354 1.116
(17.810)** (2.285)* (26.663)** [0.000]** [0.000]**
Cash flow -0.019 -0.070 -0.369 -0.350 -0.299
(1.725)+ (11.010)** (12.491)** [0.000]** [0.000]**
Leverage -0.558 -0.130 -0.572 -0.014 -0.442
(33.911)** (15.972)** (12.956)** [0.743] [0.000]**
New financing 0.132 0.013 -0.004 -0.136 -0.017
(17.404)** (3.143)** (0.178) [0.000]** [0.400]
Market-to-book ratio -0.175 0.132 0.093 0.268 -0.039
(13.161)** (16.242)** (2.643)** [0.000]** [0.279]
R & D expense 0.139 0.115 0.246 0.107 0.131
(12.707)** (17.861)** (7.974)** [0.001]** [0.000]** Payout, Interest and
Investment (PII)
Repurchases -0.021 -0.007 -0.060 -0.039 -0.053
(2.350)* (1.455) (2.293)* [0.132] [0.037]*
Short-term debt ratio -0.006 0.009 0.049 0.055 0.040
(0.495) (1.712)+ (1.497) [0.093]+ [0.215]
Short-term debt ratio* -0.164 -0.086 -0.161 0.003 -0.075
Interest expense (10.953)** (11.202)** (4.169)** [0.928] [0.048]*
Interest expense 0.441 0.259 0.823 0.382 0.564
(24.695)** (25.650)** (17.223)** [0.000]** [0.000]**
Marginal tax rate 0.001 -0.005 -0.108 -0.109 -0.103
(0.119) (0.992) (3.388)** [0.001]** [0.001]**
Capital expenditure 0.137 0.087 0.302 0.165 0.215
(13.331)** (17.594)** (10.995)** [0.000]** [0.000]**
Dividend payout 0.048 0.021 0.350 0.302 0.329
(3.571)** (3.645)** (9.544)** [0.000]** [0.000]**
Avg. diff: cash eta-sq 0.264 0.406
Number of obs. 108452 108452 108452
Adj. R-squared 0.099 0.129 0.139 The sample period is 1971 to 2006. Column (4) presents the difference in coefficients between columns (3) and (1); column (5) presents the difference in coefficients between columns (3) and (2). All regressions use year and industry effects. Heteroscedasticity-robust standards errors are estimated and corrected for clustering at the firm level. Absolute t-statistics are reported in parentheses in columns (1), (2) and (3). The p-values for a generalized Hausman test are reported in brackets in columns (4) and (5); the null hypothesis is that the difference in the coefficients is zero. The average difference in significant (10% or less) coefficients for all variables (column 4) or the PII variables (column 5) is calculated using eta-squared weights for the respective cash regressions. The adjusted R-squared measures the fit. +, *, ** denote statistical significance at the 10%, 5% and 1% levels.
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