Exploratory analyses of dividend reinvestment plans and some comparisons

International Review of Financial Analysis 14 (2005) 570–586

Exploratory analyses of dividend reinvestment plans

and some comparisons

Kevin Chianga, George M. Frankfurterb,*, Arman Kosedagc

aUniversity of Alaska at Fairbanks, United StatesbEmeritus, Louisiana State University, 60 Sagris Cove, Miramar Beach, FL 32550-3842, United States

cSabanci University, Turkey

Available online 24 November 2004

Abstract

In this paper, we explore salient features of dividend reinvestment plans (DRIPs), analyze their

financial peculiarities and search for the differences between firms that offer DRIPs and those that do

not. As more than 1200 firms currently offer the plan, an understanding of why these plans differ in a

variety of cost/benefit structures and, perhaps more importantly, what separates these firms from No-

DRIP firms is crucial for both investors and adaptors of the plan. Our research suggests that—out of

17 financial and accounting variables—DRIP firms differ from No-DRIP firms in only three

variables. In spite of this, we conclude that there is much to learn about the motivation for DRIPs.

D 2004 Elsevier Inc. All rights reserved.

JEL classification: G30; G32; G35

Keywords: DRIP; Rights offering; Capital structure; Dividend; Growth

1. Introduction

The purpose of this paper and the research it proposes is to expand the corporate,

academic finance literature dealing with the effects of dividend reinvestment plans (DRIPs)

on the dividend policy formulation of firms. In recent years, DRIPs have becomemuchmore

prevalent—both as an investment strategy or tool for the individual investor and as a source

1057-5219/$ -

doi:10.1016/j.i

* Correspon

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see front matter D 2004 Elsevier Inc. All rights reserved.

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ding author. Tel./fax: +1 850 654 5250.

ress: [email protected] (G.M. Frankfurter).

K. Chiang et al. / International Review of Financial Analysis 14 (2005) 570–586 571

of new equity for corporations—since their emergence in the late 1960s and are currently

offered by approximately 1200 firms. According to Baker and Seippel (1981) and others,

firms view these programs as a means of raising equity capital and improving shareholder

goodwill, and investors see them as a means of dollar-cost averaging.

DRIPs are set-up to allow current shareholders to purchase additional shares by buying

directly from the firm and thereby bypass the broker and his associated fees (Carlson,

1992). In addition, approximately 50 companies now allow open enrollment in their

DRIPs. Through these plans, investors can make initial investments and all subsequent

investments without paying broker fees (Burns, 1994). Although the plans appear to be

beneficial to both the shareholders and the firm, there are some problems that could be

considered deterrents. As Schneid (1981) points out, one such problem is that bplanterminations and arbitrage trading may tend to exert a negative impact on market price.Q

Because of the popularity of DRIPs with individual investors and personal investment

analysts, most of the information about DRIPs has been in the laymen finance literature.

These articles focus of course on the relationship of DRIPs to personal finance issues

rather than corporate or academic finance issues and implications. Furthermore, most of

the corporate and academic literature on DRIPs concentrates on their association with

utilities. Consequently, it pays scant attention, if any, to other industries (predominantly the

financial services industry, which now accounts for the largest percentage of DRIPs

offered), much less the entire universe of DRIPs.

Despite their apparent advantages, not all firms offer DRIPs. This seems to suggest that

firm-specific factors might be the driving force for the introduction of such plans, and

perhaps, that firm characteristics may be instrumental in the specifics of the plan offered.

Because of the thinness of the academic literature, there is a void that calls to be filled by

exploring these issues of specificity and characteristics. Accordingly, the analyses of how

firms that offer DRIPs differ from firms that do not is the objective of this paper and our

research. This objective necessarily involves the study of DRIP characteristics as well.

Naturally, our research agenda is exploratory because the lack of well-justified hypotheses

precludes it from being confirmatory.

Section 1 is a brief overview of DRIPs. In Section 2, we review the literature. Section 3

is the statistical part of the paper where we discuss the data, explain the variables of the

study, describe the models we use and the results of our tests. Finally, in Section 4, we

suggest avenues for future research and also offer some brief conclusion.

1.1. DRIPs: an overview

DRIPs are by no means new. Mutual funds and closed-end investment companies have

been providing DRIPs for their shareholders since the early 1940s (Finnerty, 1989). Lehman

Corporation, an investment company, was the first firm to offer market DRIPs.1 DRIPs were

first made available to noninvestment companies through an SEC regulation revision in

1968. Allegheny Power Systems was the first industrial corporation to implement a DRIP.

1 Davey (1976), and Saporoschenko (1996) examine three types of DRIPs: (1) market DRIPs, which are set-up

as a service to shareholders and provide no bnewQ cash to the firm; (2) treasury DRIPs, which are designed to sell

shares from treasury stock; and (3) combination DRIPs (market and treasury).

K. Chiang et al. / International Review of Financial Analysis 14 (2005) 570–586572

Before 1972, all DRIPs were open-market plans. Long Island Lighting offered the first

new-issue DRIP in 1972 (Finnerty, 1989), and AT&T was the first firm to implement a

new-issue DRIP that offered a discount to its investors (Saporoschenko, 1996). As we

discuss in greater detail later in this paper, the majority of DRIPs are offered in the

financial and utility industries.

Cherin and Hanson (1995) identify the following factors that drive the creation of

DRIPs by firms that offer the product:

! Stabilization of the stockholder base. Corporations wishing to avoid excessive

institutional ownership believe that a DRIP will attract and hold small, individual

shareholders, keeping control in the hands of management.

! Greater market price support. Sponsoring firms may believe that price volatility caused

by institutional trading can be moderated through DRIPs, and that quarterly lump sum

purchases to meet plan demand can be beneficial to the firm in that they place upward

pressure on the stock’s market price, providing a degree of price support for the stock.

! New equity capital. By using authorized but previously unissued shares in connection

with the plan, the firm taps a reservoir of new capital, obtaining regular cash infusions,

thereby reducing dependence on other external sources. The boriginal issueQ or bnewcapitalQ DRIP appeals particularly to capital-intensive businesses, like utilities, and the

trend is likely to continue. Modest amounts are raised every year that not only avoid large

periodic offerings and their adverse signaling effects but also allow, as some claim, new

capital to be used more quickly, promoting earnings stability. In addition, by providing

equity inflows, these plans restore balance to debt-burdened capital structures.

! Improved corporate liquidity.

! Lower financing costs. Because investment banker underwriting fees and underpricing

are bypassed and because fewer dividend checks and stock certificates must be

prepared and mailed, the net origination and administrative costs of equity financing are

significantly reduced as the firm uses a bnew-issueQ DRIP. Even rights offering cannot

compete. One estimate of the cost of raising equity capital through a DRIP versus a

normal underwriting is that the plan cost is between 2% and 3%, whereas investment

bankers require a 3% to 5% spread.

! Better shareholder relations. The convenience and other perceived investor benefits of

a DRIP would reap the goodwill of the generally small, individual shareholder.

Presumably, greater shareholder loyalty may reduce the likelihood of an unwanted

takeover. It seems that improved relations with shareholders weigh heavily in planning

the initiation of a DRIP.

! Appeal to shareholders. The plan attracts new stockholders who like DRIPs.

Cherin and Hanson (1995) remark, however, that from the firm’s standpoint, DRIPs

have several disadvantages:

! Dilution. Dilution of earnings per share may be a problem with bnew-issueQ DRIPs.! Wounded investor relations. A DRIP might impair investor relations by causing

shareholders to flirt with the illiquidity of not receiving needed cash dividends. In

addition, a plan may be seen as geared to only those investors with longer term


investment, creating conflict between participants and nonparticipants. Moreover, plans

may invite legal headaches with the SEC and others.2 Injuring shareholder relations

through clerical/record-keeping errors is always a possibility as well.

! Costs. The plan start-up and maintenance costs outweigh the advantages. In addition,

nonparticipants are being discriminated against in the form of expenditures on the plan.

The start-up costs for a DRIP can be high. And there are annual expenses associated

with administering the DRIP. Furthermore, there are costs associated with educating

shareholders when initiating a DRIP.

! Participation. Too few stockholders could enroll to make a DRIP worthwhile. And,

perhaps more problematic, there is little control over the extent of participation while an

boriginal issueQ plan is in force without resorting to plan alterations and/or changes in

dollar dividends declared. In other words, a free cash flow problem may exist or new

equity capital may be insufficient, requiring ongoing plan modification.

! Company ownership. To maintain the firm’s shareholder profile, especially if it is

institutionally dominated, a DRIP could be inappropriate.

Because they allow for dollar-cost averaging and the avoidance of brokers’ fees, DRIPs

are touted as a profitable investment strategy for the individual investor. The potential

investor must carefully evaluate the programs, however, as they may differ on several

features, among them are fees that are charged, discounts offered, optional cash payment

availability, enrollment requirements, availability of safekeeping and management of

the plan.

! Fees charged. Although most firms charge no commissions for purchasing stocks

through their DRIPs, many assess the investor one sort of service fee or another. These

fees are classified as dividend reinvestment, optional cash investment, certificate

issuance, sale of shares or termination of account. The fees for dividend reinvestment

are usually set-up either as a certain percentage of the reinvestment amount or as a fixed

dollar amount. The usual percentage ranges from 3% to 10%. The most common dollar

amount is $3 to $5. The optional cash investment fee ranges from 0.025% per share to

$2.50 per share, plus broker’s commission. The most common range for the fees on

certificate issuance is $5 to $15. The sale fee may be either a broker’s commission or a

fixed amount that can range from $0.03 to $15 per share. Charges for the termination of

an account can range from $2.50 to $25 plus broker’s commission.

! Discounts offered. Some firms may offer discounts to investors. These discounts can be

granted either on dividend reinvestment or on optional cash investments. Although

these discounts can vary from 1% to 10%, the most common discount is 3% to 5%.

Strangely enough, quite a few firms do both: offer discounts and charge some fees.

! Optional cash payment (OCP) availability. The availability of OCPs is one of the major

benefits emphasized in case of a DRIP that offers such possibility. Firms allowing for

OCP either will automatically withdraw a fixed amount of money from the investor’s

checking or savings account to make optional cash investments or will accept check

2 DRIPs involve SEC registration.


payments to the firm. The amounts allowed for an OCP usually range from $10 to

$150,000 per investment period, ranging from weekly to yearly.

! Enrollment requirements. The plan can be set-up to offer shares either to current

investors exclusively or to anyone at all. Some of the firms that allow all investors to

enter their DRIPs include AFLAC, Dial, Exxon, Johnson Controls, Texaco and Mobil.

For these no-load stocks, as they are commonly called, there might be a minimum

investment requirement that can range from $50 to $1000. DRIPs that allow current

investors only may require the investor to hold before enrollment anywhere from 1 to

1000 shares. Whether the firm allows for foreign acceptance simply indicates whether

the firm accepts investments from foreign investors.

! Availability of safekeeping. The safekeeping characteristic signifies whether the firm

accepts certificated shares and holds them in safekeeping for the investors. Sometimes,

the shares are deposited in the account safekeeping for the investor.

! Management of the plan. DRIPs can be administered either by the issuing firm or by an

agent. Only about 12.5% of all firms offering DRIPs administer their own plan. In the rest

of the firms, an agent administers the DRIPs. Some of the most commonly used agents are

The Bank of Boston, First Chicago Trust, RM Trust and The Bank of New York.

Part of our analyses in Section 3 is built on these plan characteristics, which in turn we

translate to observable and quantifiable variables.

2. Literature review

Because of the popularity of DRIPs with individual investors and personal investment

analysts, most of the information published about DRIPs has been in laymen’s finance

literature. Although the popular finance literature on DRIPs is too voluminous to mention,

a few articles merit special notice. Most of these articles are geared of course toward the

individual investor and not toward the firm. Business Week (April 14, 1975) points out that

DRIPs are a method by which firms can try to raise their P/E ratio. Goodman (1993)

advises investors to use DRIPs as a method of bbuilding your assets on autopilot.Q Money

(1994) touts DRIPs as a bsurefire approach to beating the market.Q And according to

Landy (1996), DRIPs provide a simple means of raising capital from existing

shareholders.

Several books pander information on DRIPs. Among them are The moneypaper’s guide

(1996) to dividend reinvestment plans, No-load stocks (Carlson, 1995) and Buying stock

without a broker (Carlson, 1992, 1996).

The academic literature on DRIPs is slight because its thrust, in one way or another, is

to fit the phenomenon into the straight-jacket of one or another cherished or currently in

vogue dividend theory. A recent paper by Bierman (1997), however, lumps DRIPs

together with the bdividend puzzle,Q using the idiom as it was originally intended by Black

(1976).

Most of the DRIPs studies focus on the effects of a DRIPs-related announcement on

shareholder wealth. There is also literature related to DRIPs on equity offerings with

noninsured rights offers being analogous and sometimes offered as a substitute to DRIPs.


A convenient taxonomy of the academic literature puts DRIPs in three categories: (A)

event studies; (B) raising new capital/rights offerings; and (3) agency costs/problems.

(A) Event studies

Although most DRIPs research falls into this category, there are a multitude of

problems associated with these studies. One of the most prevalent problems is the

pinpointing of the exact announcement date for the DRIP. In addition, event studies

are very bfragileQ in the sense that it is not uncommon to find contradictory evidence,

given the model from which babnormal returnsQ are derived. Therefore, their resultsshould not be taken lightly or unheeded. Nevertheless, because these studies

constitute such a large portion of the DRIPs literature, we would be remiss not to

report here about their existence and their findings.

Peterson, Peterson and Moore (1987) examine a 1-day window surrounding SEC

filings for new shares being issued by utilities before May 1981 by utilities after July

1981—which received preferential tax treatment (Internal Revenue Code Section

305(e) created tax deferral for DRIPs of qualifying utilities)—and by nonutilities.

They find that utilities adopting DRIPs before the tax law change experienced a

negative reaction on the day after the plan was registered, and that utilities adopting

DRIPs after July 1981 experienced positive abnormal returns significantly greater

than those without preferential treatment. They find that nonutility DRIPs, however,

realized insignificant average abnormal returns.

(B) Chang and Nichols (1992) also examine the effect of the 1981 tax legislation and

find a positive announcement effect for the qualifying utility firms. In comparing the

pre and posttax deferral periods to the 1982–1985 period in which tax deferral was

in place, Chang and Nichols find that there was an increase in DRIP participation for

qualifying utility firms but no increase for the nonqualifying utilities.

Dubofsky and Bierman (1988) examine a 3-day window around the announce-

ment of discount DRIPs. They find significant positive abnormal returns. Dubofsky

and Bierman (ibid.) argue, bthe positive excess returns are consistent with the

hypotheses that the sample firms are moving toward more optimal (less risky) capital

structures, that the internal financing aspects of a DRIP convey positive information

when announced, and/or that on balance transactions costs and brokerage fees are

reduced for the firm and its owners.Q The Dubofsky and Bierman arguments are in

contrast to the braggadocio of the free cash flow hypothesis, according to which

excess cash should be siphoned away from the firm or else management would

squander it on unnecessary perks. Perumpral, Keown and Pinkerton (1991) study the

announcement month of a DRIP and find results similar to those of Dubofsky and

Bierman. In contrast, Allen (1991) reports negative significant abnormal returns for

industrial firms announcing DRIPs.

(C) Raising new capital/rights offerings

Scholes and Wolfson (1989) examine discount DRIPs and find that discount

DRIPs provide an investment banking function in raising new capital for the firm.

They note that these bdiscount dividend–reinvestment and stock–purchase plans

allow shareholders to capture part of the underwriting fees incurred in new stock

offerings and save sponsoring firms some of the usual underwriting costs.Q Scholes


and Wolfson’s views are supported by Finnerty (1989), who emphasizes the

importance of new-issue DRIPs as a source of equity capital to firms.

Eckbo and Masulis (1992) study a large sample of equity offerings via rights

offerings and standbys. They find that 54% adopted new-issue DRIPs between 1973

and 1981, whereas only 28% of firm commitment issuers used new-issue DRIPs.

Eckbo and Masulis conclude that DRIPs are tantamount to periodic rights issues of

new shares. They also surmise that the wide use of DRIPs by firms that formerly

used rights offering/standbys will lead to the disappearance of equity offerings

through rights offering/standby methods.

(C) Agency costs/problems

Saporoschenko (1996) argues that firms with growth potential are more likely to

use treasury and combination plan DRIPs because of their need for outside funding.

Firms that issue treasury and combination plan DRIPs bypass outside monitoring,

part and parcel of other equity types. With respect to information asymmetries,

Saporoschenko notes that

. . .since treasury and combined DRIP’s are comparable to rights offering, firms

issuing DRIP’s should be confident of high subscription rates (this may be a reason

why some firms offer discounts of shares purchased through DRIP’s) and relative

undervaluation (ibid.).

Saporoschenko’s conjectures are based on the validity of findings by Eckbo and

Masulis (1992) and Smith (1977) that the lower direct flotation costs make rights offerings

a substantially cheaper method of equity issuance than going through an underwriter/

investment banker.

Saporoschenko (1996) also examines the small firm effect. Saporoschenko hypothe-

sizes that smaller firms should benefit more from the alleviation of informational

asymmetries via the use of DRIPs.

Steinbart and Swanson (1998) study the reasons that firms amend their DRIPs to

allow investors to make initial purchases of their stock. Their study attempts to ascertain

whether firms offer bno-loadQ DRIPs for economic or agency purposes. Through

telephone interviews, they asked investor relations’ representatives of firms why they

were selling bno-loadQ DRIPs. The prospectuses of these firms are also studied to learn

about the source of the shares that would be issued through bno-loadQ DRIPs. Their

results show that firms offered bno-loadQ DRIPs to broaden their shareholder base. From

this, Steinbart and Swanson (1998) conclude that their finding is consistent with agency-

related explanations.

3. Data, variables, models and results

As suggested in the introduction, our exploratory analyses of DRIPs focus on detecting

the firm characteristics that may (a) dictate plan features (i.e., a within group analysis of

DRIP firms) and (b) explore differences, if any, between DRIP firms and No-DRIP firms

(i.e., between group analysis).


The DRIP plan features, described in Section 1, can be either qualitative or

quantitative. Qualitative variables are coded as binary, while quantitative variables are

in the appropriate units of measurement. In Table 1, we show the possible plan

features as factors, including their definition and the possible values the factors can

take.

From a sample of 1004 firms offering DRIPs on NetStockDirect, we randomly select

just 206 firms. There are two reasons for reducing the sample size to 206:

(1) for these firms, we could identify for certain one or more of the DRIP factors, and

(2) the reduced size allowed us to be sure that a close to full information dataset was

available for other variables of the firms we could to study.

The sample of 206 firms roughly corresponds to the relative frequencies of the total

population as per the three firm categories: financial, utilities and industrial firms. A

complete list of these firms is not included herein but is available on request from

Table 1

DRIP features

Factor name Definition Measure

Covenants

CASHD Cash dividends Yes=1, No=0

IRA IRA option Yes=1, No=0

OCP Optional cash purchase Yes=1, No=0

ACH Direct debit from bank Yes=1, No=0

DISC Discount Yes=1, No=0

LAH Loans against holding Yes=1, No=0

AF Open to/accept foreigners Yes=1, No=0

ADR American deposit receipt Yes=1, No=0

RSA Requires Special Affiliation Yes=1, No=0

MININSH Minimum initial shares required Quantity

MINOCP Minimum optional cash purchase $/year

MAXOCP Maximum optional cash purchase $/year

Fees

OCP fee OCP fee $ Amount

PUCOM Commission—purchase $/Share

SALESCOM Commission—Sales $/Share

SALESFEE Sales fee $/Share

TERMFEE Termination fee $/Share

ENROLFEE Enrollment fee $ Amount

SK Safekeeping/insurance $/Share

NSF Not sufficient funds $/Share

Additional features

PTYPE Plan can be designed either as a registered

DRIP or direct stock plan (DSP)

Registered DRIP=1;

DSP=0

E Enrollment Current shareholders

only=1; anyone=0

MNG Management type Company=1; agent=0


the authors. Table 2 displays simple statistics relating to the plan feature variables for

the sample firms. Note that not all factors are present for each of the 206 DRIP

firms.

In panel A of the table, the figures for the binary (qualitative) variables are given in

frequency and percent form. The numbers that represent dollars, either total/year or per

share, are presented in panel B with their minimum, maximum, average and standard

deviation.

The data reveal that, for this sample, more than 90% of the DRIP firms

! pay a cash dividend;

! extend the possibility of optional cash purchases of the stock;

! open their plan to foreign investors;

! do not have an IRA;

! do not provide loans against the reinvested dividends;

Table 2

DRIP features—descriptive statistics

(A) Binary variables

Variable Number of Frequency Percentage of 1s Standard

name observations0 1

(mean) [%] deviation [%]

CSHDIV 206 12 194 94.17 23.48

IRA 206 193 13 6.31 24.37

OCP 206 9 197 95.63 20.49

ACH 206 162 46 21.36 41.08

DISC 206 112 94 45.63 49.93

LAH 206 205 1 0.49 6.97

AF 206 5 201 97.57 15.43

ADR 206 196 10 4.85 21.54

RSA 206 203 3 1.46 12.01

PTYPE 206 49 157 76.21 42.68

MNG 195 181 14 7.18 25.88

E 157 1 157 100.00 0.00

(B) Quantitative variables

Variable name Number of

observations

Minimum Maximum Mean Standard

deviation

MININSH 157 1 100 2.88 10.02

MINOCP 205 0 $600.00 $51.53 $91.13

MAXOCP 200 0 $480,000.00 $53,031.00 $67,165.82

OCPFEE 138 0 7.5 0.59 1.56

PUCOM 138 0 0.25 0.01 0.36

SALESCOM 44 0 0.25 0.10 0.05

SALESFEE 62 0 15 $7.15 $5.62

TERMFEE 68 0 15 $2.35 $5.14

ENROLFEE 138 0 15 $0.87 $2.76

SK 106 0 10 $0.33 $1.47

NSF 11 0 25 $18.63 $9.51


! have no ADR3 (because they are domestic firms);

! do not require any special affiliations; and

! have an agent who administers the plan.

In addition, almost half the plans offer a discounted share price, and more than 75% are

registered dividend reinvestment plans.

Fees are just averages and are therefore quite misleading because one must look at the

specific combinations of fees with other factors (discounted share price, for instance). The

other two aspects of the sample that justify special scrutiny are the values for the

minimum, maximum and average dollar investment required for OCP. The minimums

range from 0 to $600, with an average of $51.53, whereas the maximums are from 0 to

$480,000, with an average of $53,031. It seems that some of the OCPs are designed for the

large investor who most likely will benefit from bypassing the broker in a deal.

Next, we select 17 financial and stock market variables on which a meaningful within-

group analysis and a comparison between the primary sample and a control sample may be

made. To compare and contrast DRIP firms with No-DRIP firms, we match our primary

samplewith a control sample constructed by stratified random sampling, where thematching

criterion, in addition to the industry stratification, is firm size as measured by total assets.

Although a wide variety of such variables have been used in accounting and financial

research, there is no clear-cut method that would determine the minimum set and its ex-

clusivity. Prior research in this regard was, by and large, arbitrary and depended almost

exclusively onwhat seemed logical and onwhether data were available. Nevertheless, some of

these variables appear almost in every study both as matters of logical selection and as

tradition. The approachwe take here does not differ fromprior practice, and that being the case,

we would be, despite our good intentions, subject to the same criticism as our predecessors.

Data are obtained from COMPUSTAT and represent accounting information and/or

market data as of December 31, 2001. Beta is available directly from COMPUSTAT,

where it is calculated from 60 monthly observations of rate of return on the firm’s stock as

the dependent variable and the S&P 500 Index as the independent variable. Table 3 is a

reference list of the names and the definitions of the 17 accounting/market variables.

Although the selection of these variables is either arbitrary or it is necessitated by data

availability, it represents a reasonable group of variables for which meaningful

comparisons can be made because most are mentioned in conjunction of prior studies

of the DRIP phenomenon.

Naturally, the most critically revealing, stand-alone variable is DPS. Next is a group of

variables of various empirical measures of return and profitability (ROA, ROE, NPM, PE

and EPS). Following return and profitability variables, we have a measure of leverage/

financial risk (LTDEQ) and, after that, variables that traditionally proxy for liquidity (FCF,

CR, NWC), then an additional measure of size, independent of the creation of the control

sample (NSTA), and variables that reflect on growth potential (R&D/S and SAGR). Closing

the set of variables serving for comparison purposes are ownership (IO and INST) and

proxies of risk (B/M and BETA). With regard to this last group, we advise the reader to

peruse the voluminous literature on the CAPM, especially Fama and French (1992).

3 American depository receipt.

Table 3

Accounting variables used in within- and between-group analyses

Variable name Definition

DPS The last dividend paid by the firm from COMPUSTAT

Measures of return or profitability

ROA Return on assets, calculated from financial statements (net income/total assets)

ROE Return on equity, calculated from financial statements (net income/total equity)

NPM Net profit margin (net income/sales), as calculated from financial statements

PE Stock price/earnings, calculated from income statement and COMPUSTAT

EPS Earnings per share, calculated form financial statements

Measure of financial risk

LTDEQ Long-term debt/total equity, calculated from balance sheet

Measures of liquidity

FCF Free cash flowa

CR Current assets/current liabilities (also known as the current ratio),

calculated from financial statements

NWC Net working capital (total current assets less total current liabilities)

Measure of size

NSTA Net sales/total assets (also known as the total asset turnover),

calculated from financial statement

Measures of growth potential

R&D/S R&Db expenses/net sales

SAGR Five-year sales growth ([St/St�4])1/5�1.0, where t=2001

Measures of ownership

IO Insider ownership calculated from baseline and Yahoo finance

INST Institutional ownership as a fraction of total ownership

Market proxies of risk

B/M Book/market ratio calculated from balance sheet and market value

of stock at 2001 year end

BETA As of the ubiquitous market model

a Net cash flow, less dividends, less capital expenditures, COMPUSTAT mnemonic bFREECFLQ.b R&D is all costs that relate to the development of new products or services, COMPUSTAT mnemonic

bXRDQ.


3.1. Within-group analysis

First, we analyze with a series of probit regressions whether accounting variables

can differentiate/separate within DRIPs. This we call the within-group analysis. In this

analysis, the dependent variable is some factors defined in Table 1 as binary (1,0).

We use in this analysis only DISC, ACH, PTYPE and MNGT. This we do because

the remaining factors fail to partition regarding size, and thus, they would be

meaningless. In addition, we do not consider the fees charged on services as a

differentiating factor because almost all firms charge at least one type of fee


(commission on purchase or sales, sales fee, termination fee, enrollment fee,

safekeeping fee etc.).4

A binary probit model can be approached in two ways:

(1) as a regression model or

(2) as a random utility model.

In essence, the two models are quite similar. The reason we opt for the latter is that it

allows for a random vector. Its underlying assumption is that micro units (DRIPs, in this

case) separate/distinguish themselves in the margin by the respective choices they offer.

In its general form, the model is expressed as

y4 ¼ bVXþ e

where y*, bVand e are vectors, and X is a matrix with columns equal to the number of

independent variables. The vector e is a vector of random disturbances distributed standard

normal.

Under the random utility model, we consider DRIP factors as ym if the coding of the

factor is unity and yn, otherwise, corresponding to Ua and Ub as the respective utilities

derived, given the choice.5 Then we have

U a ¼ baVXþ ea and U b ¼ bbVXþ eb:

If we denote Y=0 (choosing the first alternative response), then

Prob Y ¼ 0jX½ � ¼ Prob ½U abU b� ¼ Prob ½baVXþ ea �bbVXþ ebjX�

¼ Prob baV� bbVÞXþ ea � ebÞb0jXð � ¼ Prob b ¼ Xþ eb0jX�:½ð½

For maximum likelihood estimation of the probit model’s parameters, see Greene

(1997, pp. 873–888).

Our interest is in how DRIP firms distinguish one from the other across the 17 financial

variables we defined in Table 3.

We look at the slope coefficients of the individual probit regression run for each

factor. Because our analysis is marginal, in the interest of clarity, we show in Table 4

only the slope coefficients of those variables that are statistically significant at the

level of 0.10 or less. Moreover, we omit those accounting variables for which none of

the factors were distinguishable at the same level of significance of the slope

coefficients.6

Table 4 displays the DRIP factors (dependent variables) as rows and the

accounting/ financial variables (independent variables) as columns with their estimated

5 Please see Table 1 for the binary designations.6 Complete results are available, upon request, from the authors.

4 A subgrouping of the fee structure and hence using dollar amount for each proved to be useless, as in many

cases, this information was not available.

Table 4

Within-group probit analysis

DRIP

features

Accounting

variables

ROA NPM EPS LTDEQ CR NSTA R&D/S SAGR IO INST BETA

DISC 0.041 �0.363 0.407 0.405 122.458 �0.003 0.947 0.532

0.042 0.002 0.052 0.006 0.002 0.001 0.037 0.042

PTYPE 0.293 �0.672 0.001 �0.928

0.014 0.008 0.043 0.004

ACH �0.252 �0.252 0.863 0.767

0.021 0.021 0.003 0.021

MNG 0.052 �0.235

0.072 0.062


slope coefficient and, in italics, the corresponding probability of error type I. Thus

presented, the reader can verify both the value of the coefficient (specially note its

sign) and the strength of the rejection of the null hypothesis (the probability of a

zero slope).

The strongest bwithin-groupQ separation one can find for the factor DISC (discount).

Eight out of the 12 remaining financial/accounting variables are significantly different than

0 at the 0.05 level of error type I (although for CR, the probability is just a marginal

0.052). The coefficients’ signs are positive with two exceptions, meaning that the higher

the value of a particular accounting measure the higher the probability of offering

discount. The exceptions are SAGR and LTDEQ, implying that lower growth rate and

lower financial risk firms tend to offer discount as part of the plan, other things being

equal.

The next two factors with four significantly nonzero coefficients are ACH and PTYPE

(direct debit from bank and plan type, respectively). Two variables, CR and BETA, are

common to both factors; the other two are not. From the signs of the coefficient for ACH,

it seems that DPS and NPM are negatively correlated with DRIPs that offer a direct debit

and positively correlated with CR and BETA. Other things being equal, these firms have a

higher systematic risk and, perhaps because of that, a higher current ratio. With respect to

plan type, precisely for these two variables, registered plans are less risky (both

coefficients are negative). In addition, they have higher LTDEQ and IO (insider

ownership) than direct stock plans. With regard to the last factor, MNG, the distinguishing

variables are only two (ROA and EPS) and are significant at error type I level higher than

0.05.

For the financial/accounting variables, BETA and CR are the most separating for

four factors, whereas the majority of variables are separating for one or two. Recall

that we omitted already five variables that were not separating for even a single

factor.

In conclusion, we suggest that, as far as the variables we study go, the DRIP plans seem

to be quite homogeneous with the exception of BETA and a liquidity risk measure, where

the signs are consistent with what one would logically expect regarding systematic risk

taking. In the next subsection, we analyze the differences between the primary and the

control samples.


3.2. Between-group analysis

Tables 5 and 6 present the results of our tests and contrasts of the primary and the control

samples. Because we match the DRIP firms with No-DRIP firms by a random selection of

size within an industry and because of missing data or other reasons, not all the measures are

present for all the firms initially selected from either the 206 DRIP or the No-DRIP firms.

This is why all the accounting/market variables have less than 206 observations. In fact, the

highest number of pairings is for ROA and NPM (173), and the fewest is for R&D/S (30).

Table 5 is the simple tabulation of sample statistics, first five columns showing the

mean, the number of observations, standard deviation and standard error of the mean,

respectively, for each of the 17 accounting variables for two groups. The last two columns

Table 5

Paired variables of DRIPs and No-DRIPs

Variable Mean N Standard

deviation

Standard error

of mean

Correlation Significance

Pair 1 DPS1 1.00 172 0.908 0.069 0.337 0.000

DPS2 0.78 0.705 0.054

Pair 2 ROA1 2.78 173 4.932 0.375 �0.074 0.330

ROA2 2.04 6.383 0.485

Pair 3 ROE1 9.20 172 18.261 1.392 �0.065 0.397

ROE2 3.12 60.117 4.584

Pair 4 NPM1 9.28 173 14.866 1.130 0.316 0.000

NPM2 15.07 123.178 9.365

Pair 5 PE1 26.30 68 44.527 5.400 0.075 0.546

PE2 30.08 54.655 6.628

Pair 6 EPS1 0.98 82 2.686 0.297 0.056 0.615

EPS2 1.37 3.337 0.369

Pair 7 LTDEQ1 1.03 169 0.874 0.067 0.370 0.000

LTDEQ2 1.13 1.332 0.102

Pair 8 FCF1 0.04 57 0.542 0.072 0.030 0.827

FCF2 �0.87 7.100 0.940

Pair 9 CR1 1.30 103 0.720 0.071 0.294 0.003

CR2 1.46 1.019 0.100

Pair 10 NWC1 196.91 103 1548.897 152.617 0.576 0.000

NWC2 112.96 1103.859 108.766

Pair 11 NSTA1 0.66 171 0.671 0.051 0.688 0.000

NSTA2 0.64 0.691 0.053

Pair 12 R&D1/S1 0.02 30 0.044 0.008 0.532 0.002

R&D2/S2 0.02 0.033 0.006

Pair 13 SAGR1 0.13 147 0.141 0.012 0.317 0.000

SAGR2 0.17 0.181 0.015

Pair 14 IO1 0.11 75 0.120 0.140 0.214 0.065

IO2 0.23 0.217 0.025

Pair 15 INST1 0.51 87 0.261 0.028 0.278 0.009

INST2 0.47 0.280 0.030

Pair 16 B/M1 0.25 71 4.760 0.564 0.000 1.000

B/M2 0.82 0.813 0.096

Pair 17 BETA1 0.52 107 0.450 0.044 0.435 0.000

BETA2 0.58 0.526 0.051

Table 6

Paired difference tests

Variable Paired differences 95% Confidence

interval

t-Value DF Significance

Mean

difference

Standard

deviation

Standard

error

Lower Upper

Pair 1 DPS1–DPS2 0.218 0.943 0.072 0.076 0.360 3.026 171 0.003

Pair 2 ROA1–ROA2 0.746 8.352 0.635 �0.508 1.999 1.174 172 0.242

Pair 3 ROE1–ROE2 6.077 63.955 4.877 �3.549 15.703 1.246 171 0.214

Pair 4 NPM1–NPM2 �5.792 119.321 9.072 �23.698 12.115 �0.638 172 0.524

Pair 5 PE1–PE2 �3.783 67.874 8.231 �20.211 12.646 �0.460 67 0.647

Pair 6 EPS1–EPS2 �0.397 4.165 0.460 �1.312 0.518 �0.863 81 0.391

Pair 7 LTDEQ1–LTDEQ2 �0.101 1.294 0.100 �0.298 0.095 �1.017 168 0.311

Pair 8 FCF1–FCF2 0.907 7.105 0.941 �0.979 2.792 0.963 56 0.340

Pair 9 CR1–CR2 �0.158 1.061 0.105 �0.365 0.050 �1.508 102 0.135

Pair 10 NWC1–NWC2 83.947 1283.767 126.493 �166.952 334.846 0.664 102 0.508

Pair 11 NSTA1–NSTA2 0.022 0.538 0.041 �0.060 0.103 0.523 170 0.602

Pair 12 R&D/S1–R&D/S2 0.002 0.039 0.007 �0.012 0.016 0.287 29 0.776

Pair 13 SAGR1–SAGR2 �0.033 0.191 0.016 �0.065 �0.002 �2.125 146 0.035

Pair 14 IO1–IO2 �0.120 0.225 0.026 �0.171 �0.068 �4.608 74 0.000

Pair 15 INST1–INST2 0.044 0.325 0.035 �0.026 0.113 1.249 86 0.215

Pair 16 B/M1–B/M2 �0.566 4.826 0.573 �1.708 0.577 �0.988 70 0.327

Pair 17 BETA1–BETA2 �0.061 0.523 0.051 �0.161 0.039 �1.209 106 0.229


present the correlation coefficient of the 17 paired variables and the probability under the

null of correlation. At 0.05 level of error type I, the following 10 variables are significantly

correlated: DPS, NPM, LTDEQ, CR, NWC, NSTA, R&D/S, SAGR, INST and BETA.

With the exception of ROA, all correlations, whether significant or not, are positive.

Therefore, it is safe to conclude that, for the majority of variables, the data cannot show

drastically different group characteristic. Comovement, nevertheless, does not mean that

there are no significant differences between the two types of firms. To test for statistically

significant differences, in Table 6, we show the tests of paired mean differences.

Table 6 is organized in 10 columns. Columns 1 and 2 are the numbered pairs and the

direction of the difference (DRIP minus No-DRIP). Column 3 is the mean difference

(equals to the difference of the means). In columns 4 and 5 are the standard deviation of

the difference and its standard error. Columns 6 and 7 show the 95% confidence interval

of the mean difference, column 8 is the t-value of the difference, and column 9 is the

number of degrees of freedom for a particular pairing. Finally, column 10 is the

probability under the null of error type I of the mean difference coming from the same

population.

It can be seen that, at 0.05 level or less of error type I, just three pairs come from two

different populations: DPS, SAGR and IO. Although significant differences are few, their

signs are nevertheless consistent with what one would expect from the two types of firms.

DRIP firms pay more dividends and, at the same time, entice their shareholders to bleavethe money on the table.Q The growth factor of No-DRIP firms is higher than that of DRIP

firms, and thus, they plow back more internally generated funds because it is a cheap

source of capital (Myers & Majluf, 1984). In addition, insiders’ ownership is higher in No-


DRIP firms; therefore, they need less enticement and consistently pay out less in dividends

(DPS1-DPS2 is positive).

4. Future work and conclusions

Perhaps more questions than answers remain at the conclusion of this study. This may

be so because, despite all our good intentions, resources are limited. With more readily

available data, one could carry out more detailed analyses. An obvious avenue of further

research and a different dimension of exploration must follow a route where corporate

decision makers and investors are asked about the good and bad things DRIPs do for them

and why they do or do not use this instrument of financing/investment in the firm. This

issue may obtain an additional edge by considering the 2003 dividend tax reform whereby

dividends are taxed at the fix rate of 15%.

The focus of the survey we propose is the motivation for initiating a DRIP. Such a

survey is badly needed because of the total lack of this line of research on the subject. We

hope that we can also increase the scope of investigation by examining a fuller, more

diverse sample of firms, as well as DRIPs investors. This would be important because,

although they are not a new phenomenon, DRIPs are gaining in popularity as a long-term

investment tool for individual investors. This increase in popularity has led to a dramatic

increase in the number of firms offering DRIPs. This increase is buttressed by a

concomitant increase in the complexity of DRIP characteristics.

The bad news is that such research requires resources that very few researchers have.

But if the role of science is discovery (a search for the truth), then there is no way around

finding both the resources and the know-how to follow this path. Short of that, finance as

an academic profession will never get to the bottom of the dividend puzzle.

Acknowledgements

The authors are indebted to Ms. Kim Alexander, who, as a research assistant of the

second author, did initial exploratory literature search on the subject. All usual disclaimers

of responsibility to others than the authors apply, nevertheless.

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Documents

Exploratory analyses of dividend reinvestment plans and some comparisons