Download Common Characteristics of New Firms that Initiate Dividends

The Dividend Initiation Decision of Newly Public Firms: Some Evidence on
Signaling with Dividends
Jayant R. Kale a,*, Omesh Kini b, and Janet D. Payne c
a
Robinson College of Business, Georgia State University, Atlanta, GA 30303
Robinson College of Business, Georgia State University, Atlanta, GA 30303
c
McCoy College of Business, Texas State University, San Marcos, TX 78666
b
This version: January 4, 2011
Forthcoming: Journal of Financial and Quantitative Analysis
☆We appreciate the comments from an anonymous referee, George Benston, David Blackwell, Harry
DeAngelo, Vladimir Gatchev, Paul Irvine, Michael Keefe, Steve Smith, Isabel Tkatch, Sunil Wahal, and
participants at the 2009 Financial Management Association Meeting, Atlanta Finance workshop,
University of Otago, Seoul National University, Pusan National University, and Chonnam National
University. The usual disclaimer applies. Kale‘s research was supported, in part, by the H. Talmage
Dobbs, Jr. Chair and a research grant from the Robinson College of Business at Georgia State University.
*Corresponding author. Robinson College of Business, Georgia State University, Atlanta, GA 30303,
USA. Tel. + 1-404-413-4375; Fax: + 1-404-413-7312.
E-mail addresses: [email protected] (Jayant R. Kale), [email protected] (Omesh Kini), [email protected]
(Janet D. Payne).
Abstract
We track the dividend initiation decisions of a sample of 6,588 firms that went public during the period
1979-2005 and find that 873 of them initiated dividends. Our primary objective is to determine whether
information signaling can explain the dividend initiation (DI) decision. We find that variables suggested
by the dividend-signaling models of John and Williams (1985) and Allen, Bernardo, and Welch (2000)
are significant determinants of the DI decision and the associated announcement-period stock price effect.
We also find support for the residual, agency, tax, clientele, transactions costs, catering, and life cycle
explanations of dividend policy.
JEL classification: G35; G32
Keywords: Dividend initiations, Signaling models, Level of dividends, Timing of initiations
The Dividend Initiation Decision of Newly Public Firms: Some Evidence on
Signaling with Dividends
“The price responses to dividend announcements are evidence that the potential for signaling—
the motive and opportunity, as it were—is already in place. If, therefore, signaling does not
occur, it can be only because some lower cost (i.e. less dissipative), but still incentive-compatible
and time-consistent route has been found to communicate the information in the dividend. The
challenge becomes thus to explain why the price jump we see is not signaling; and that may be
even harder to explain than why it is”
Merton H. Miller (1987, p. 54)
I.
Introduction
Probably the only aspect of dividend policy for which there is consensus among finance
researchers is that announcements of dividend initiations and dividend level changes engender
significant effects on a firm‘s stock price. There is, however, considerable debate (and
disagreement) regarding the reasons for these stock price effects. Consistent with theoretical
dividend-signaling models, it seems reasonable that stock prices change because changes in
dividend policy alter investors‘ information sets. However, empirical evidence on the
information-signaling role of dividends is mixed. In this study, we track the dividend initiation
(DI) behavior of a sample of firms that went public over the period 1979–2005. We restrict our
attention to dividend initiations since a recent survey by Brav, Graham, Harvey, and Michaely
(2005) confirms the predominant sentiment that managers are extremely conservative with
respect to their firm‘s dividend policy, largely because they believe that dividend policy is
significantly more inflexible than repurchase policy. This perceived inflexibility makes managers
2
particularly averse to initiating dividends, which makes dividend initiation an important
milestone in the firm‘s life cycle.
Our primary focus is to examine whether dividend-signaling models can explain the DI
decision and the stock price effects of DI announcement. In the process, we also shed light on the
determinants of the dividend level and the time taken (from IPO) to initiate dividends. While the
focus of our paper is on empirically testing whether there is an information-signaling role for
dividends, our tests also control for clientele, tax, agency, transactions costs, catering, and
residual theories of dividends.
John and Williams (1985) (henceforth, JW) and Miller and Rock (1985) show that the
level of dividends signals the level for a firm‘s cash flows, while Kale and Noe (1990)
demonstrate that the level of dividends signals the variance of the firm‘s cash flows.1 In these
models, the decision to initiate dividends does not depend on firm quality but on a liquidity
condition that may be unrelated to firm quality. Furthermore, the positive relation between the
dividend level and firm quality exists only for those firms that decide to initiate dividend
payment. In the JW dividend-signaling equilibrium, a firm will signal with dividends if the
supply of cash in the firm is less than the sum of the personal cash needs of the firm‘s owners
and the funds needed for the firm‘s optimal investment policy. Thus, a cash-rich high-quality
firm will not initiate dividends for signaling purposes; but a cash-poor low-quality firm will. The
important implication is that firms will try to obtain correct market valuation through dividend
signaling only when shares of equity have to be sold in the market, either by insiders to satisfy
1
See Bhattacharya (1979) and Lipson, Maquieira, and Megginson (1998) for signaling models in which dividends
provide information about the level of a firm’s cash flows.
3
personal cash needs or by the firm to raise investment capital. Then, conditional on this decision
to initiate dividends, the dividend level will signal firm quality and result in the correct valuation
of the firm‘s shares.2
Allen, Bernardo, and Welch (2000) (henceforth, ABW) assume that institutional
investors have superior ability in assessing firm quality and, therefore, higher-quality firms bear
the tax-based costs of dividends to attract these better informed investors. Lower-quality firms
cannot mimic this action because they do not want their true type to be revealed as a result of
institutional monitoring. The result is a separating equilibrium in which firms signal higher
quality by paying dividends to attract the better informed institutional investors. Since we focus
on the DI decision only of firms that conducted an IPO, our sample is particularly suited to test
the implications of the ABW framework. The ABW predictions encompass two aspects. First,
firms initiate dividends because they wish to attract certain investor clienteles. Second, because
these firms want to signal superior future prospects, they wish to attract investor clienteles that
have superior monitoring ability and can validate the higher quality of the dividend initiating
firm. Thus, firms that suffer less from asymmetric information (e.g., large seasoned firms) may
still wish to initiate dividends to attract a certain clientele but this clientele need not be the type
that will monitor the firm (e.g., retirees). Younger firms such as the ones in our sample of IPO
firms, on the other hand, are more prone to informational asymmetry problems. Thus, higher-
2
The dividend-signaling models of Miller and Rock (1985) and Kale and Noe (1990) also predict a similar relation
between that the likelihood of DI and the need to sell equity. In these models, insiders maximize the weighted
average of the market price and the true value of the firm‘s stock. A necessary condition for dividend signaling
equilibrium is that the weight placed on the market price be strictly positive.
4
quality firms in our sample are more likely to initiate dividends to attract investor clienteles such
as institutional investors who will monitor them and validate the superior future prospects of
their firms.
We investigate the predictions of both the JW-genre models that relate DI to the need to
raise funds in the future and the ABW model that relates DI to the need to attract informed
clienteles. We measure the cash needs of the firm and its shareholders by the probability that the
firm will issue seasoned equity (either primary and/or secondary shares) in the near future and
hypothesize that this probability relates positively to the likelihood that the firm will initiate
dividends. The ABW model implies that DI is more likely if the firm‘s ownership does not have
informed investors to certify firm quality. Assuming (as in ABW) that institutions are informed
investors, empirically, a firm is more likely to initiate dividends if the level of institutional
ownership in the firm is lower than what it should be given the characteristics of the firm. The
ABW model predicts that the greater this deficit, the more likely is the firm to initiate dividends.
Consistent with the predictions of both these models, we find that the likelihood of DI
relates positively to the firm‘s propensity to issue seasoned equity in the near future. We also
find that this propensity rises monotonically in the three years prior to the year of initiating
dividends. In support of the ABW prediction, we find that the greater the deficit in the firm‘s
level of institutional ownership, the greater is the probability that the firm will initiate dividends.
Furthermore, the evolution of the deficit institutional ownership reveals a clear pattern; the
deficit rises monotonically in the three years prior to DI and then monotonically decreases in the
years after the initiation of dividends. In addition, consistent with JW and Kale and Noe (1990),
we find a significantly negative relation between the probability of DI and the firm‘s asset beta
and the residual standard deviation in stock returns. Thus our findings support the predictions of
5
several dividend-signaling models.
As in the prior empirical studies, we find significantly positive announcement effects for
dividend initiation. We investigate the relation between DI announcement returns and the
variables suggested by dividend-signaling models. Consistent with the prediction of all dividendsignaling models that higher quality firms choose a higher level of dividend, we find that DI
announcement returns relate positively to the level of dividends (measured by the dividend
yield). The DI announcement returns relate negatively to the probability of a seasoned equity
issue and, further, the positive relation between dividend yield and announcement returns
becomes less positive as the probability of seasoned equity becomes higher. These findings offer
further evidence in support of dividend signaling. The need for raising capital at the firm level is
a crucial feature in the dividend-signaling model of JW and a higher probability of seasoned
equity issue makes DI more likely. The extant theoretical and empirical literature suggests that
seasoned equity issue announcements reduce stock prices.3 Thus, the significantly negative
relation between the probability of a seasoned equity issue and DI announcement returns
indicates that investors expect either the firm and/or its shareholders to issue seasoned equity and
indeed take the probability of its occurrence into account while reacting to DI. We also find that
the shortfall in optimal institutional ownership relates positively to DI announcement returns,
which supports the dividend-signaling paradigm in ABW.
We next simultaneously model the DI and the time-to-DI decisions using Cox
Proportional Hazard models. To examine the time-to-DI issue further, we also estimate Poisson
regressions that model the time-to-initiation and probit regressions that model a firm‘s DI versus
3
See Eckbo and Masulis (1995) and DeAngelo, DeAngelo, and Skinner (2008) for a summary of this evidence.
6
postpone DI decision. All these analyses yield a consistent inference; variables suggested by
dividend-signaling models, such as the probability of equity issue, shortfall in institutional
ownership, and risk, are significant determinants of the DI timing decision.
While the above findings offer significant support for dividend-signaling, our results are
consistent with the other major theories of dividends.4 In support of the residual and agency
theories of dividends, we find that firms with lower growth opportunities, lower research and
development expenditures, lower capital expenditures, and higher operating returns are more
likely to initiate dividends. Next, consistent with the transactions cost hypothesis (Miller and
Modigliani (1961) and Banerjee, Gatchev, and Spindt (2007)), we find that firms with more
liquid stocks are less likely to initiate dividends. Our results support the catering theory in Baker
and Wurgler (2004) in that we find firms are more likely to initiate dividends when the market
premium for dividend-paying stocks is higher. Finally, consistent with life-cycle explanations for
the payment of dividends, we find that firms are more likely to initiate dividends when retained
earnings are a larger proportion of total assets (see, e.g., Fama and French (2001), Grullon,
Michaely, and Swaminathan (2002), and DeAngelo, DeAngelo, and Stulz (2006)). As in Brav,
4
These theories have been analyzed extensively in the empirical literature. See, for example, Pettit (1972), Aharony
and Swary (1980), Kalay (1980), Asquith and Mullins (1983), Healy and Palepu (1988), Eades (1982), Venkatesh
(1989), and Yoon and Starks (1995) for studies supportive of the information content of dividends. See Rozeff
(1982), Lang and Litzenberger (1989), and Smith and Watts (1992) for evidence consistent with the agency aspects
of dividends. In contrast, Benartzi, Michaely, and Thaler (1997) argue that their findings are most consistent with
the classic Lintner (1956) model of dividends. In fact, none of our findings are inconsistent with the residual theory
of dividends.
7
Graham, Harvey, and Michaely (2005), most of our findings for DI also hold for the dividend
level decision.
Our DI analysis also includes variables suggested by the signaling models of Allen and
Faulhaber (1989), Grinblatt and Hwang (1989), and Welch (1989). While the first two models
relate IPO underpricing and the fraction of shares retained by the entrepreneur to the dividend
decision, Welch (1989) relates the IPO underpricing decision to the propensity to return to the
equity issuance market. Our analysis spans these three models by linking IPO firms‘ DI initiation
decision to the likelihood of their issuing equity subsequent to the IPO.
The article is organized as follows. The next section contains a description of our data
sources, sample selection criteria, and variable definitions.
In Section 3, we present our
empirical findings on the DI decision. The following section contains our analysis of the stock
price announcement effects of dividend initiations. We present other related findings in Section
5. Finally, we offer concluding remarks in Section 6.
II.
Data, Sample Selection, and Variable Definitions
A.
Data Sources
We analyze the DI decision and the information content of the DI decision for firms that
went public during the period 1979-2005. We obtain our initial sample of IPO firms from
Thomson Financial‘s New Issues Database, of which 6,588 firms are listed on both the CRSP
NYSE/AMEX/NASDAQ and the Compustat Annual and Research files. We exclude financial
and utility firms from our sample. We check the dividend distribution codes on CRSP until the
end of year 2006 to identify the date of the first regular cash dividend payment and denote that
8
year as the DI year.5 We obtain exchange listing, stock returns, and trading volume data from
CRSP, and information on firm characteristics such as book values of total assets and total debt,
operating earnings, and R&D and capital expenditures from Compustat. Thomson Financial is
the source for information on variables related to the IPO decision, such as the offering price, the
IPO issue date, the fraction of the equity retained by the entrepreneur, the identity of the
underwriter, and future security issuances. We use the updated Carter, Dark, and Singh (1998)
measure of underwriter reputation.6 The variable, dividend premium, related to the catering
theory of dividends is from Baker and Wurgler (2004).7 Finally, we obtain data on institutional
ownership from CDA/Spectrum database.
B.
Sample Selection
Table 1 describes the final sample of 6,588 firms and their distribution by the year of
going public. We find that 873 of these firms initiated dividends during the period of the study.8
Columns four to thirteen of the table provide the breakdown on the timing of the DI decision,
which is given relative to the year of the IPO (year zero). In Figure 1, we present a bar chart that
5
We check a sample of these declarations and ex-dividend dates and dividend payment amounts on CRSP with
reports in the Wall Street Journal, to verify the accuracy of this CRSP data.
6
This measure is from Professor Jay Ritter’s website: http://bear.warrington.ufl.edu/ritter/ipodata.htm.
7
The updated data on this variable is from Professor Jeff Wurgler’s website: http://pages.stern.nyu.edu/~jwurgler.
8
Grullon and Michaely (2002) find that the propensity of firms, particularly younger ones, to pay a cash dividend is
being systematically replaced by a preference to pay cash through share repurchases over the last two decades.
DeAngelo, DeAngelo, and Skinner (2000), however, do not find evidence for substitution between special dividends
and share repurchases. The evidence in Jagannathan, Stephens, and Weisbach (2000) leads them to conclude that
share repurchases are used to pay out transitory shocks to earnings and dividends are reserved for permanent
earnings. In our paper, we focus on regular (which are more likely to be permanent) dividend initiations.
9
represents the proportion of total dividend initiations occurring in each year after the IPO as well
as the cumulative percentage of dividend initiations. The dividend initiation data by year
suggests that if a firm is to initiate dividends, it is most likely to do so in the first two years
(years 0 and 1) after going public. Of the 873 dividend initiations in the sample, 268 (30.7
percent) occur in the year of the IPO and 153 (17.5 percent) occur in the following year.
[Insert Table 1 approximately here]
[Insert Figure 1 approximately here]
The primary objective of our empirical analysis is to investigate the determinants of two
aspects of a firm‘s dividend decision: (i) whether to initiate dividends, and (ii) the information
content of dividends. To analyze the decision to initiate dividends, we include in the analysis
firms that initiate dividends as well as firms that do not initiate dividends. We track each firm in
our sample from its IPO year until the year 2006 or until they leave the CRSP database,
whichever is earlier, to determine whether the firm initiates dividends. We stop tracking the firm
once it initiates dividends.9 Following is an example that illustrates how we classify IPO firms in
each year from 1979-2006 as DI and NDI. Of the 416 firms that went public in 1999, 22 initiated
dividends in the sample period; seven in 1999; one in 2000, two in 2001, zero in 2002, two in
2003, three in 2004, four in 2005, and three in 2006 (our last observation year), and the
remaining 394 firms did not initiate dividends. We classify the seven firms that initiate in 1999
as DI and the remaining 409 as NDI for that year. Of these 409 NDI firms, we classify the one
that initiates in 2000 as DI and the remaining 408 as NDI for the year 2000. Of these 408 NDI
9
Thus an IPO firm remains in our sample until it either initiates dividends or is delisted, whichever is earlier. Thus,
we do not expect survivorship to be an issue in our analysis.
10
firms, we classify the two that initiate in 2001 as DI and the remaining 406 as NDI. Since no
firm has a DI in 2002, all 406 are classified as NDI in 2002. Two out of these 406 are DI in 2003
and the remaining 404 are NDI. In 2004, three of these 404 NDI firms initiated dividends leaving
401 NDI firms. Of these 401 NDI firms, we classify the four that initiate in 2005 as DI and the
remaining 397 as NDI. Finally, three out of these 397 are DI in 2006 and the remaining 394 are
NDI. Therefore, the 416 IPO firms that went public in 1999 provide 22 observations for the DI
sample and 3,225 observations for the NDI sample (409 + 408 + 406 + 406 + 404 + 401 + 397 +
394). We repeat this procedure for firms that went public in each year of the sample to obtain
the DI and NDI samples for our analysis.10
Except the IPO-related variables whose values are computed at the time of the IPO, we
compute of all the other independent variables as follows. In our analyses, the period of
observation is one year. We classify a firm as an NDI firm in all years after going public until the
DI year; in the DI year, we classify it as a DI firm. The firm drops out of the sample for all the
years subsequent to the DI year in the analyses. Consider a firm that goes public in 1999 and
initiates dividends in 2003. We classify this firm as an NDI firm in each of the four years prior
to 2003 and compute all the independent variables in each year for this firm. In 2003 (year 4), we
classify the firm as DI and compute all the variables for that year; and after 2003, the firm does
not enter the sample. In our procedure for forming DI and NDI samples, NDI firms enter the
sample more than once (possibly every year) whereas a firm that initiates dividends never enters
the sample in the years subsequent to the initiation year. The advantage of the procedure is that
it allows us to compare why, in a particular year, one firm initiates dividends whereas another
10
See, for example, Warner, Watts, and Wruck (1988) and Weisbach (1988) for variants of this basic procedure.
11
does not. The assumption here is that the decision to initiate dividends or not is made every year
and, thus, each firm that has not initiated dividends in one year is, in effect, a new firm that will
be making the decision next year.
C.
Variable Definitions
1.
Signaling Variables
The main variables of interest for our analysis are those suggested by the dividend-
signaling models. The JW dividend-signaling model suggests the firm‘s need to issue seasoned
equity subsequent to the IPO as a determinant of the DI decision. The variable SEO02 (SEO12)
is a dummy variable that equals one if the IPO firm conducts a primary and/or secondary
seasoned equity issue in the three-year (two-year) period that includes (excludes) the observation
year and (but includes) the two years following the observation year. According to the JW
model, the DI decision is related to the likelihood that a firm will issue equity. Therefore, for our
empirical tests, we also compute the predicted values of SEO02 and SEO12, and denote them by
PROBSEO02 and PROBSEO12, respectively. These variables are the predicted values from
probit regressions (see Models 1 and 2 in Table A1 in the Appendix) with SEO02 and SEO12 as
the dependent variables, respectively. We measure the level of dividends with the variables
DIVYLD1 and DIVYLD15 that are annual dividends divided by the stock price one and 15 days
prior to dividend initiation announcement, respectively.
The ABW model suggests the deficit in the level of institutional ownership, which we
denote by DEFICIT_INSTOWN, as a determinant of a firm‘s dividend policy. We measure
institutional ownership (INSTOWN) as the fraction of the firm‘s equity owned by all institutions,
and DEFICIT_INSTOWN as the difference between the predicted and actual level of
institutional ownership. We compute the predicted value of institutional ownership from OLS
12
regressions that use predictors suggested by the extant literature on the patterns of institutional
investment (see Model 3 in Table A1 in the Appendix).11
To test the predictions in JW and Kale and Noe (1990) that firm risk and profitability
variables are determinants of a firm‘s dividend policy, we include the beta of assets (A), which
is the equity of the firm divided by 1 plus the market value debt-equity ratio, where we obtain
equity by estimating the market model regression over the observation year. We also include the
residual standard deviation (RESSTD) measured as the RMSE from the market model estimated
to obtain equity, and profitability (ORA), which is the ratio of the firm‘s operating income before
depreciation and taxes to total assets.
2.
Other Variables
We control for the other potential explanations of dividend payout suggested in the
literature. The agency theoretic framework in Jensen (1986) predicts that managers of firms with
excess free cash flows can commit to minimizing wasteful expenditures by adopting a policy of
paying out excess free cash flows through dividends. Agency theory, therefore, predicts that the
likelihood of DI is negatively related to the firm‘s perceived future growth opportunities, and
positively related to the existing supply of free cash flows. 12 We measure a firm‘s growth
opportunities by MBA – the ratio of the market value (MV) of the firm‘s assets (sum of the MV
of equity and the book value of all debt) to their book value, RDA – the ratio of the firm‘s R&D
11
Following Badrinath, Gay, and Kale (1989) and Del Guercio (1996), the independent variables in the estimated
regression are MBA, LTA, LTDA, AGE, A, RESSTD, and TURN.
12
The residual theory of dividends assigns a passive role to dividends and states that firms will pay a dividend when
they have cash left over after satisfying the firm‘s investment needs and, consequently, its predictions are the same
as the agency theory.
13
expenditures to total assets, and CEA – the ratio of the firm‘s capital expenditure to its total
assets. We measure the cash available for manager‘s discretionary expenditures by ORA - the
ratio of the firm‘s operating income before depreciation and taxes to total assets and LTDA – the
ratio of long-term debt to total assets.
Miller and Modigliani (1961) argue that if investors can costlessly replicate corporate
dividends by trading in shares, then dividend policy becomes value irrelevant. If the firm‘s stock
is more liquid then it may be cheaper for investors to create homemade dividends by selling
shares than to rely on the firm to pay cash dividends. We measure the degree of liquidity by
share turnover (TURN), which is the ratio of annual trading volume to shares outstanding. The
transactions cost theory predicts a negative relation between the probability of DI and TURN.
Baker and Wurgler (2004) find support for the notion that the decision by firms to pay dividends
results from the demand for dividends by market participants. We measure investor demand for
dividends by DIVPREM, which is the difference between the logarithms of the market-to-book
ratios of dividend payers and non-payers, where book values are used to weight the market-tobook ratios across dividend payers and non-payers (Baker and Wurgler (2004), Table II).
Allen and Faulhaber (1989) and Grinblatt and Hwang (1989) model both IPO
underpricing and the fraction of the shares that the entrepreneur retains at the time of the IPO as
signals of firm quality. Therefore, we include UP – the return to the IPO on the offer date,
ALPHA – the fraction of firm equity retained by the original owner in the IPO, and AGE – one
plus the number of years elapsed between the observation year and the IPO year. In view of the
findings in Carter and Manaster (1990) and Loughran and Ritter (2004), we include UNDREP –
the updated Carter, Dark, and Singh (1998) IPO underwriter reputation measure. Following
DeAngelo, DeAngelo, and Stulz (2006), we include REA, which is the firm‘s retained earnings
14
divided by total assets. Finally, in keeping with the empirical literature on dividends, we also
include NYSE – a dummy variable that equals one if the firm is listed on the NYSE, else it
equals zero, and REPUR – a dummy variable that equals one if the firm repurchases shares in the
observation year, else it equals zero.
The variables MBA, RDA, CEA, TA, LTDA, ORA, and TURN are computed as follows.
If the values for these variables are available for the observation year and the prior year, the
variable is the average of these two values. If the value is missing for either the observation or
the prior year, we use the non-missing value. Since 48.2% of the firms that initiate do so in the
IPO year and the year after (see Table 1 and Figure 1 in the paper), this approach allows us to
retain most of these observations in our sample. Furthermore, it also allows us to retain
observations close to the IPO year for the non-dividend-initiating firms. All the other variables
are for the observation year.
III. Empirical Findings on the Dividend Initiation Decision
In this section, we present results on the DI decision from both univariate and
multivariate tests. First, we provide an analysis of how the variables suggested by the dividendsignaling models in JW and ABW evolve prior to and after the DI event. Then, we present tests
of differences in the means and medians of firm characteristics for DI and NDI firms. We then
analyze the DI decision in a multivariate setting – first using probit models and then Cox
Proportional Hazard models.
A.
Evolution of Signaling Variables around Dividend Initiation
1.
Evolution of the Probability of SEO prior to Dividend Initiation
The JW model posits that firms initiate dividends when they have a need to issue
seasoned equity in the near future. We investigate the evolution of the need to issue equity
15
(PROBSEO02 and PROBSEO12) in the four years prior to DI year and present the results in
Table 2 and Figures 2 and 3. The table presents the mean and median values of PROBSEO02
and PROBSEO12 in each of the four years prior to the dividend initiation year and compares
them to the corresponding values in the DI year.
[Insert Table 2 approximately here]
[Insert Figures 2 and 3 approximately here]
The mean and median values for PROBSEO02 in the DI year (last column of Panel A of
Table 2) are 20.983% and 21.529, respectively. The PROBSEO02 mean values for years t-1, t-2,
t-3, and t-4 are 18.694%, 16.904%, 16.902%, and 17.051% respectively. The t-test and Wilcoxon
test statistics for significance of differences in means and medians, respectively, in the lower
rows of the Panel indicate that the mean and median value for PROBSEO02 in each of the four
prior years is significantly lower than that in the dividend initiation year. Furthermore, starting in
year t-3, the probability of issuing seasoned equity rises steadily up to the DI year. The findings
are identical in Panel B for PROBSEO12. Figure 2 (Figure 3) presents the evolution of mean
PROBSEO02 (PROBSEO12) values in the preceding years and the DI year as bar charts. The
findings that the probability of SEO issuance is highest for the DI year and the increasing pattern
from year t-3 are clearly apparent in both the bar charts. The evolution of the probability of SEO
is consistent with the prediction of the dividend signaling framework in JW.
2.
Evolution of the Level of and Deficit in Institutional Ownership around Dividend
Initiation
According to ABW, firms initiate dividends to attract institutional investors. We
investigate the evolution of the level of institutional ownership (INSTOWN) and the deficit in
institutional ownership (DEFICIT_INSTOWN) in the four years before and the four years after
16
the DI year. We present the findings from this analysis in Table 3 and Figures 4 and 5. In Panel
A of the table, we present the mean and median values for INSTOWN in the DI year (column 5)
and in each of the four years before (columns 1 – 4) and after (columns 6 – 9) the DI year. Panel
B presents the mean and median values for DEFICIT_INSTOWN in a similar manner.
[Insert Table 3 approximately here]
[Insert Figures 4 and 5 approximately here]
In the case of INSTOWN, from Panel A we see that the level of institutional ownership
in the DI year is approximately the same as in the four previous years. Since there has been a
steady increase in institutional ownership over time, the flat pattern in institutional ownership in
the years prior to DI indicates that these firms were not attracting institutional funds. This
observation is borne out by the values for DEFICIT_INSTOWN in Panel B. The mean (median)
deficit for these firms in year t-4 is 1.19% (3.877%), which increases to 3.51% (5.014%) in the
DI year.
The patterns in both the level and the deficit in institutional ownership change
dramatically in the years after the dividend initiation year. The mean (median) level of
institutional ownership increases from 36.879% (31.558%) in the DI year to 43.512% (41.607%)
in year t+4. The mean (median) deficit in institutional ownership correspondingly decreases from
3.51% (5.014%) in the DI year to 1.342% (1.619%) in year t+4. Figure 4 (Figure 5) shows the
evolution from years t-4 to t+4 in INSTOWN (DEFICIT_INSTOWN). These bar charts,
particularly the one for DEFICIT_INSTOWN, clearly highlight how the desire to increase
institutional ownership is a likely reason for initiating dividends. Firms that find themselves
increasingly shunned by institutional investors as indicated by the increasing deficit in the period
prior to DI, initiate dividends and find themselves to be increasingly favored by institutions in
17
the years following DI. The evolution of institutional ownership, in particular the evolution of
the deficit in institutional ownership, is consistent with the underlying premise of the dividendsignaling framework in ABW.
B.
Univariate Analysis of the Dividend Initiation Decision
Table 4 presents mean and median values of the all the remaining variables described in
the previous section for the full sample as well as the sub-samples of dividend initiating (DI) and
non-dividend initiating (NDI) firms. The last two columns present the t-statistic and Wilcoxon Z
statistics for differences in mean and median values, respectively, in characteristics of the firms
in the two sub-samples DI and NDI.13
Consistent with our hypothesis that firms initiate
dividends when their cash needs at the corporate level are high, we find that the DI sample firms
are more likely to conduct seasoned equity offerings as compared to the NDI sample. As
predicted by JW, the mean for SEO02 (SEO12) for DI firms is 17.526% (11.711%), which is
significantly greater than the mean of 13.857% (8.015%) for the NDI sample. Similarly, the
predicted values PROBSEO02 and PROBSEO12 are significantly greater for the sample of DI
firms. Consistent with ABW, the mean value for deficit in institutional ownership
(DEFICIT_INSTOWN) is 3.510% for the DI sample, which is significantly greater than the
mean of -0.067% for the NDI sample. We observe similar patterns when we examine median
instead of mean values for the above variables.
[Insert Table 4 approximately here]
13
We winsorize all variables at their 1 and 99 percentile levels to mitigate the effect of outliers.
18
Generally speaking, the dividend-initiating firms are larger, have lower growth
opportunities (MBA and RDA), less discretionary expenditures (RDA), higher earnings (ORA),
lower risk (A and RESSTD), lower underpricing (UP), have higher fractions retained by original
owners at IPO (ALPHA), and have IPOs underwritten by more prestigious underwriters
(UNDREP). Consistent with the catering theory, the average value for DIVPREM is larger for
DI firms. As expected, we find that DI firms are more likely to be listed on the NYSE. We find
that the fraction of firms that repurchase shares is higher for DI firms. Finally, DI sample firms
have significantly greater levels of retained earnings (REA).
C.
Multivariate Analysis of the Dividend Initiation Decision
We have two primary hypotheses on the dividend initiation decision that are based on a
signaling role for dividends. The first is that firms initiate dividends because they need to raise
capital at the firm and personal levels and the second is that they initiate dividends because they
wish to attract more informed investors such as institutions.
We test these two hypotheses using both a Heckman two-stage treatment effect model
and a probit regression. In the Heckman two-stage treatment effect model, we estimate a probit
regression where the dependent variable is the dummy variable SEO02 (SEO12) in the first
stage. The second stage is a probit model where the dependent variable is DI, which equals zero
in all the years since the IPO and equals one in the year in which the firm initiates dividends. In
this specification, we include SEO02 (SEO12) and the ―Inverse Mills Ratio‖ from the first stage
as additional independent variables. In the second specification, we use PROBSEO02
(PROBSEO12), the predicted value of SEO02 (SEO12), as independent variable in the probit
regression instead of SEO02 (SEO12). The dependent variable in this probit regression is again
19
DI.14 The hypotheses are that the likelihood of initiating dividends is positively related to the two
SEO and the two PROBSEO variables, and to DEFICIT_INSTOWN.
In addition to the main variables of interest described above, we also include firm and
IPO characteristics described above to control for the other determinants of dividends that have
been suggested in the literature. Since firms may appear in the sample multiple times, errors may
be correlated and t-statistics may be overstated because of the ―cluster sample‖ problem (see,
e.g., Wooldridge (2002)). Therefore, we use adjusted standard errors that account for the possible
correlations between forecast errors for a firm. Our adjustments are made under the assumption
that forecast errors across firms are independent (see, e.g., Huber (1967), Rogers (1993), White
(1980), and Wooldridge (2002)). We compute t-values that are bootstrapped using 100
replications since we are using the predicted values of some explanatory variables in our
regressions. Finally, we control for industry effects using single-digit SIC codes in all our
estimated regressions. Our findings continue to hold if we control for industry effects using the
48 Fama-French industry classifications.
We present the results from estimating the Heckman treatment effect and probit models
in Table 5. The first two columns of the table present the findings from the second-stage of the
Heckman treatment effect model with SEO02 (Model 1) and SEO12 (Model 2) as the measures
14
Another approach we use is to estimate a system of two equations with binary dependent variables – either
SEO02 or SEO12 in one equation and DIVPAID in the other equation using the BIPROBIT command on STATA.
This procedure fits maximum likelihood two equation models in a similar fashion to the seemingly unrelated
estimation in the sense that it takes into account the contemporaneous correlation across the two equations. We can
safely ignore the endogeneity in the formulation of the likelihood function because we have a recursive system
(Greene (2007, p. 823)). The results from the bivariate probit model are similar to those reported in Table 5.
20
of the propensity to issue seasoned equity. The last two columns present the findings from the
probit regressions with PROBSEO02 (Model 3) and PROBSEO12 (Model 4) as measures of the
propensity to have a seasoned equity issuance.
[Insert Table 5 approximately here]
Consistent with the hypothesis that firms initiate dividends when the need to issue
seasoned equity is greater, the coefficients on the SEO variables in the treatment effect models
and the PROBSEO variables in the probit models are positive and statistically significant. The
coefficient on DEFICIT_INSTOWN is also significantly positive in all the four models, which
supports the hypothesis that dividend initiation is more likely when firms have a lower than
desired level of institutional ownership. These positive signs on SEO and PROBSEO offer
strong support for the dividend signaling models of JW and Miller and Rock (1985); while the
positive sign on DEFICIT_INSTOWN supports ABW. As predicted by JW and Kale and Noe
(1990), the coefficients on A and RESSTD are negatively related, and the coefficient on ORA is
positively related, to the likelihood of dividend initiation.15
The coefficients on MBA, RDA, CEA, and LTDA are negative and significant and
support the agency and residual explanations for dividends. We do not find a significant relation
for any IPO-related variable with DI probability. The coefficient on TURN is negative and
significant implying that firms with more liquid stocks are less likely to initiate dividends.16 The
15
In results not reported in the paper, we also find that A declines significantly after dividend initiation. This result
is consistent with the decline in systematic risk after dividend initiations documented in Dyl and Weigand (1998)
and the decline in systematic risk after dividend increases documented in Grullon, Michaely, and Swaminathan
(2002).
16
This finding is consistent with the argument in Miller and Modigliani (1961) that states that if investors can
21
coefficient on AGE is negative and weakly significant which is consistent with the pattern
detected in Table 1 that the longer IPO firms wait, the less likely they are to initiate dividends.
We investigate this timing issue in greater detail in a subsequent section of the paper. Next, we
find that DIVPREM and NYSE are positively related and REPUR is unrelated to the dividend
initiation decision. The positive sign on DIVPREM is in line with the catering theory in Baker
and Wurgler (2004) which posits that firms are more likely to pay dividends when investors are
willing to pay a premium for dividend paying stocks. We find no evidence that firms
systematically use share repurchases (REPUR) as either substitutes or complements to dividends.
Consistent with the life-cycle explanation, the coefficients on REA and LTA are both positive
and statistically significant, indicating that firms with greater retained earnings and larger firms
are more likely to initiate dividends (see, e.g., DeAngelo, DeAngelo, and Stulz (2006)).
To assess the economic significance of each explanatory variable related to dividend
signaling, we compute the change in implied probability of dividend initiation by changing the
value of that variable from its 25th percentile value to its 75th percentile value while holding all
other explanatory variables at their median values. For dummy variables, we change their values
from zero to one irrespective of their 25th and 75th percentile values. Further, while computing
the economic significance of other variables, we maintain the dummy variables at their mean
instead of their median value. The primary reason for using a different procedure for dummy
costlessly replicate corporate dividends by trading in shares, dividend policy becomes value irrelevant. In a recent
paper, Banerjee, Gatchev, and Spindt (2007) argue that since trading costs have declined significantly over the
years, firms are less likely to pay dividends. These authors provide empirical evidence that the increase in stock
market liquidity is a likely explanation for the decline over the years in the propensity of firms to pay dividends.
They also find evidence that past liquidity is a significant determinant of the decision to initiate dividends.
22
variables is that some of them have non-zero values only for a small proportion of the sample.
We follow this treatment for dummy variables in all our subsequent computations of economic
significance. The economic significance for each of the signaling-related variables is reported in
the ―Change in implied probability (%)‖ rows at the bottom of Table 5. In addition, to the
change in implied probability, we also report the probability of initiating dividends at the 25th
and 75th percentile values of the explanatory variable in brackets.
In Model 1, the change in implied probability if SEO02 varies from a value of zero to one
is 16.28% (ranging from 1.33% to 17.61%), while in Model 2, the change in implied probability
if SEO12 varies from a value of zero to one is 36.98% (ranging from 1.34% to 38.32%). These
values for economic significance indicate that the likelihood of dividend initiation is very
sensitive to whether the firm will issue equity in the near future. These values should be viewed
with caution since the proportion of firms that issue seasoned equity is quite small (13.92% and
8.08% in the three- and two-year periods, respectively), and a change in the value of SEO02 or
SEO12 from zero to one is major change. In Models 3 and 4, we use PROBSEO02 and
PROBSEO12, both of which are continuous variables and, thus, do not suffer the problem just
described for dummy variables SEO02 and SEO12. When we vary PROBSEO02 and
PROBSEO12 from their 25th to 75th percentile value, the changes in implied probability are
1.58% (ranging from 0.78% to 2.36%) and 1.38% (ranging from 0.77% to 2.15%), respectively.
Further, in Model 1, the change in implied probability for DEFICIT_INSTOWN, A, and
RESSTD are 0.45% (ranging from 1.93% to 2.38%), -0.68% (ranging from 2.48% to 1.80%),
and -1.52% (ranging from 2.89% to 1.37%), respectively. Across the four models, we find that,
on average, the changes in implied probability for DEFICIT_INSTOWN, A, and RESSTD are
0.38%, -0.62%, and -1.09%, respectively. In these tests, there are 715 DI and 38,090 NDI
23
observations, that is, 1.84% of the firm-year observations are dividend initiators. Therefore, the
change in implied probability percentages should be viewed in relation to this 1.84% value.
Therefore, it appears that all the dividend signaling-related variables have economically
meaningful effects on the probability of dividend initiation.
D.
Results from Cox Proportional Hazard Models
We model the determinants of DI by assuming that managers arrive at the dividend
initiation decision and the time-to-initiation simultaneously. We now jointly estimate the
dividend initiation and time-to-initiation decisions using the Cox Proportional Hazard (CPH)
model.17 The primary benefit of hazard analysis over regression lies in its ability to explicitly
account for time and handle censored observations and time-varying covariates (Shumway
(2001)). Thus, hazard models can predict whether an event will occur and, at the same time,
explicitly model the time it takes to reach that outcome. The sample construction in this test is
identical to that used earlier in our probit analysis. Censored firms are defined as the IPO firms
that do not initiate dividends by the end of our tracking period (the earlier of the delistment year
from CRSP or year 2006). The dependent variable is the number of months from the beginning
of each observation year until the month during which the firm initiates dividends combined with
the dichotomous status variable (initiated dividends status versus did not initiate dividends status
at end of tracking period). The dependent variable in the hazard model, therefore, denotes the
likelihood that an IPO firm will initiate dividends each period.
17
See Cox (1972) and Kalbfleisch and Prentice (1980) for a detailed discussion of the Cox Proportional Hazard
model.
24
We present results from estimating two CPH models, one using PROBSEO02 and the
other with PROBSEO12 as a dependent variable in Table 6.
A positive coefficient on a
dependent variable in the estimated CPH model indicates that an increase in that variable leads
to an increase in the likelihood of DI and a decrease in the time-to-DI. The reverse holds true for
a negative coefficient. The coefficients on PROBSEO02 and PROBSEO12 are positive and
statistically significant, which implies that a higher likelihood of seasoned equity issuance relates
positively to likelihood of DI and negatively to the time-to-DI. The coefficient on
DEFICIT_INSTOWN is also significantly positive indicating its positive (negative) effect on the
likelihood of (time to) DI. The significantly negative coefficients on A and RESSTD and the
significantly positive coefficient on ORA are also consistent with dividend signaling. The
coefficients on the other variables are generally of the same sign as in the previous analyses.
[Insert Table 6 approximately here]
We assess the economic impact of these variables by evaluating their effects on the risk
or hazard that a currently non-initiating firm will initiate dividends in the future. To achieve this
objective, we evaluate the hazard ratio associated with each explanatory variable. The estimated
percent change in the hazard of initiating dividends for a one unit increase in that variable is
obtained by subtracting one from the hazard ratio and multiplying by 100. 18
For dummy
variables, the hazard ratio is interpreted as the estimated hazard of initiating dividends for those
firms for whom the dummy variable takes on a value of 1 relative to the estimated hazard for
those firms for whom the dummy variable takes on a value of 0.
18
Prior to estimating the hazard ratios, we express all variables in percentage units with the exception of A,
UNDREP, AGE, NYSE, REPUR, and LTA.
25
The hazard ratio associated with PROBSEO02 is 1.023 in Model 1, which implies that
for a 1% increase in PROBSEO02, the rate of DI increases by 2.30% holding all other variables
constant. Similarly, a 1% change in PROBSEO12 increases the rate of DI by 3.85%. A 1%
increase in DEFICIT_INSTOWN increases the rate of DI by 0.44% and 0.42% in Models 1 and
2, respectively. A one unit increase in A (RESSTD) decreases the rate of DI by 15.68% (6.27%)
and 15.68% (4.95%) in Models 1 and 2, respectively; and a 1% change in ORA increases the rate
of dividend initiation by 2.96% and 2.77% in Models 1 and 2, respectively. The relative
importance of these variables is hard to assess since they have different scales. Regardless, all
our dividend signaling-related variables appear to have economically meaningful effects on the
rate of dividend initiation.
IV.
Stock Price Announcement Effects of Dividend Initiations
We compute the announcement returns associated with dividend initiations by the IPO
firms in our sample and then investigate how the dividend yield (DIVYLD1), a firm‘s likelihood
of seasoned equity issue (either PROBSEO2 or PROBSEO12), and DEFICIT_INSTOWN affect
these announcement effects. We compute three-day (-1, 0, and +1) cumulative abnormal returns
on announcements of dividend initiations using the Fama-French three-factor model (with valueweighted market index) and present the findings in Table 7. For the full sample of 788 dividend
initiations with enough data to estimate the cumulative abnormal return (Panel A), the mean and
median three-day abnormal returns for DI are 1.708% and 0.823%, respectively, and are
statistically significant.
[Insert Table 7 approximately here]
26
According to JW, while both high and low quality firms initiate dividends when they
need to issue seasoned equity, higher quality firms will separate themselves by choosing higher
dividend levels. We investigate this hypothesis by comparing the announcement effects of two
sub-samples of DI firms, those with DIVYLD1 greater than the median and those with
DIVYLD1 lower than the median. We present the findings in Panel B of Table 7. Consistent
with the JW prediction, the mean abnormal return for the high DIVYLD1 firms of 2.381% is
significantly greater than the 0.939% for low DIVYLD1 firms. In unreported results, we find a
similar pattern when we divide the sample by the median value of DIVYLD15.
Next we compare the announcement returns in the sub-samples of high and low
PROBSEO02 and PROBSEO12 and present the findings in Panels C and D of Table 7,
respectively. There is ample evidence in the literature that announcements of seasoned equity
offerings result in negative stock price effects. The results in both panels indicate that the
announcement returns of dividend initiations are significantly lower when the likelihood of an
equity issue is higher. Thus, it appears that the stock price reaction of dividend initiations
impound the market‘s perception of the probability of a seasoned equity issue. In Panel E, we
present findings from sorting the sample of DI announcements on the basis of
DEFICIT_INSTOWN. The magnitude of the announcement returns appears to be bigger when
the deficit is greater but the difference is not statistically significant.
We then investigate the relation between DI announcement returns and the variables
DIVYLD1, PROBSEO02, and DEFICIT_INSTOWN in a multivariate setting using three
different empirical specifications. We do not report the results using DIVYLD15 and
PROBSEO12 for space considerations but simply note that they are quite similar. The first
specification is an OLS regression with the three-day announcement CAR as the dependent
27
variable. The second specification uses the Adjusted CAR, which is the CAR divided by one
minus the probability of dividend initiation. This adjustment attempts to account for the fact that
some of the announcement-period wealth effect is already anticipated by the market. For the
third specification, we use a Heckman selection model framework, in which we first model the
decision to initiate dividends using the probit models described earlier and, conditional on having
initiated a dividend, we estimate an OLS regression of DI announcement returns on the above
variables. The two-stage selection model accounts for the distinction (e.g. in JW) between
dividend initiation and dividend-signaling. The DI decision depends on the cash needs of the
firm, whereas the signaling aspect depends on firm quality—higher quality firms pay more
dividends. We adjust for the propensity to initiate dividends here through the presence of the
Inverse Mills ratio in the second stage OLS regression. In each specification, we estimate two
models, the first with the three variables mentioned above and the second with an additional
interaction term for DIVYLD and PROBSEO02. The findings from the second-stage OLS of the
Heckman procedure are reported in Table 8.
[Insert Table 8 approximately here]
Consistent with the signaling-theory predictions that higher-quality firms choose higher
levels of dividends, the coefficient on DIVYLD1 is significantly positive in five of the six
specifications. The coefficient on PROBSEO02 is negative and significant in four out of the six
models indicating that the DI announcement effect reflects the market‘s perception of the
probability of there being a seasoned equity offering. The coefficient on DEFICIT_INSTOWN is
significantly positive in five out of six models, which indicates that if a firm initiates dividends
when the level of institutional ownership is lower than it should be, the market perceives
dividend initiation as a mechanism for attracting informed institutions and reacts positively.
28
Finally, the coefficient on the interaction term DIV_PROBSEO02 is negative indicating that the
positive relation between the level of dividends and the DI announcement effect is less positive
when the probability of a seasoned equity issuance is high. In summary, the results presented in
Tables 7 and 8 on the stock price effects of DI announcements offer considerable support to the
predictions in the dividend-signaling models of JW, Miller and Rock (1985), and ABW.
We also examine the stock price reaction to announcements of SEO issuances by our
sample IPO firms. We find that 574 firms issue seasoned equity after DI and 2,537 firms conduct
a seasoned offering either before DI or did not initiate dividends during the study period. The
three-day mean (median) abnormal returns around announcements of these issuances are -1.928
% (-1.370%) for the DI firms and -3.340% (-3.117%) for the NDI firms. The difference between
the mean (median) abnormal returns for these two groups is significant at the 1% level. These
results suggest that DI indeed reduces informational asymmetries and increases the likelihood of
SEO, which results in less negative stock price reactions upon announcements of the SEO issues.
V.
Other Related findings
The DI decision is coupled with the dividend level decision as well as the timing of DI. In
this section, we present some findings from tests that shed light on these issues that are
intimately related to the DI decision. First, we investigate the dividend level selected by firms
that choose to initiate dividends. Second, we investigate a firm‘s DI choice in an initiate versus
postpone framework and the time between IPO and DI. We restrict our attention to firms that
initiate dividend in the examination of these timing issues.
29
A.
The Level of Dividends
When the firm decides to initiate a dividend, it also chooses how much to pay. We
employ Tobit regression analysis in order to investigate the determinants of both the dividend
initiation and the level of dividend decisions. The dependent variable in the Tobit regressions is
the dividend yield which is the ratio of the annual dividends per share and the stock price either
one (DIVYLD1) or fifteen (DIVYLD15) days prior to the announcement of dividend
initiation.19 The dividend yield is zero for all non-dividend paying firms. A firm is considered to
be a dividend paying firm only for the year of initiation. For all earlier years, it is treated as a
non-dividend paying firm. The independent variables are the same as those used in the earlier
probit regression analysis. We estimate four Tobit specifications: two specifications each for
DIVYLD1 and DIVYLD15 – one with PROBSEO02 (Model 1) and PROBSEO12 (Model 2).
The results from estimating the Tobit regressions are presented in the first four columns of Table
9. Since the results for the control variables are similar to those presented earlier, we report the
coefficients only for the signaling variables of interest. The findings for these variables are the
same as in the probit analysis. Specifically, the coefficient on PROBSEO02 (PROBSEO12) is
significantly positive in both Model 1 (Model 2) specifications. Furthermore, the coefficients on
DEFICIT_INSTOWN and DIVPREM are significantly positive in all four models.20
19
We also compute dividend yields using the closing stock price for days -30 and -60 relative to the announcement
date of initiation. The results are robust to alternative definitions of dividend yield.
20
We use the decomposition suggested by McDonald and Moffitt (1980) to compute the marginal effects on
dividend yield and the probability of initiation. We do not report the findings in table but simply note that the
relative importance of the determinants is similar for both the level of dividends and the probability of dividend
initiation.
30
[Insert Table 9 approximately here]
B.
To Pay or to Postpone the Payment of Dividends?
Next, we focus only on the sample of those firms that initiated dividends during the
sample period to determine whether there are some observable criteria for the ―pay or postpone‖
decision. The underlying assumption here is that all the dividend-initiating firms in the sample
always ―knew‖ that they would pay dividends. Thus, in each year since the IPO, they make the
decision as to whether to initiate dividends in that year or not. Note that in the Cox Proportional
Hazard analysis (Table 6), the determinants of the dividend initiation decision and the time-toinitiation decision were intertwined, that is, a positive (negative) coefficient on an explanatory
variable implies a higher (lower) probability of dividend initiation and a lower (higher) time-toinitiation. By restricting our attention to dividend initiating firms, we attempt to delink the
initiation and the timing decisions. The dependent variable, DPOST we use in the probit
regression to investigate this aspect of DI timing is constructed as follows. All the firms in our
sample that do not initiate dividends in the IPO year (year 0) are assigned the value DPOST =1
and those that initiate dividends are assigned the value DPOST = 0. The firms that are assigned
a value DPOST = 0 leave the sample for all subsequent periods. In subsequent years, of the
DPOST = 1 firms from the previous year, those that do not initiate dividends in year 1 are
assigned the value DPOST = 1 and those that initiate dividends are assigned the value DPOST =
0. A positive coefficient in the estimated regressions implies that the explanatory variable relates
positively to the likelihood that the firm will postpone DI.
We again estimate two models, one with PROBSEO02 and the other with PROBSEO12
and present the findings in columns five and six of Table 9. The results again suggest the
importance of the dividend signaling variables. The probability of seasoned equity issue and
31
DEFICIT_INSTOWN relate negatively to the likelihood of postponing DI, although the latter
relation is not statistically significant at conventional levels. The coefficient on DIVPREM is
significantly negative in both specifications, which implies that when dividend premium in the
market is high, firms are less likely to postpone dividend initiation.21
C.
Time-to-Initiation: Poisson Regression Models
For this analysis, we again restrict attention to firms that initiate dividends and estimate
Poisson regression models to analyze the determinants of the time-to-initiation decision. The
time-to-initiation is measured as the number of months elapsed between the month of DI to the
beginning of each sample year. Thus, each firm could enter the sample several times with the
first entry being for the IPO year and the last entry being for the year of initiation. For example,
a firm that goes public in March 1992 and initiates dividends in November 1995 will enter the
sample four times. The first time it enters the sample is for the IPO year and the time-toinitiation is the number of months between the DI month (November 1995) and the beginning of
the IPO year (January 1992). The next time it enters the sample is for the year after the IPO year
and the time-to-initiation is the number of months between the DI month (November 1995) and
the beginning of 1993, and so on.
The results from the Poisson regression models are in the last two columns of Table 9.
The findings are generally similar to those for the ―pay versus postpone‖ decision. Specifically,
21
We find that for firms that eventually initiate dividends, a higher ALPHA– the fraction of the equity owned by the
original entrepreneurs, venture capitalists, and management after the IPO – implies delaying DI. We interpret this
result to be consistent with a tax-based explanation, namely, that these parties postpone DI to reduce the adverse
personal tax impact of dividends relative to share repurchases or capital gains.
32
we find that the time-to-initiation is significantly negatively related with the probability of
seasoned equity issue, the deficit in institutional ownership, and the dividend premium.
VI.
Discussion and Concluding Remarks
In an influential corporate finance textbook, Ross, Westerfield, and Jaffe (2005, p. 528)
state that ―Perhaps the most important dividend decision a firm must make is when to pay
dividends for the first time.‖ A recent survey article by Brav, Graham, Harvey, and Michaely
(2005) confirms the importance that senior financial executives attach to initiating dividends.
Specifically, managers tend to be extremely conservative in initiating dividends since they are
essentially permanent in nature. Thus, dividend initiation decisions by firms provide us with the
ideal experimental setting to test implications from the rich theoretical literature on dividend
signaling models.
In this article, we present a comprehensive analysis of various aspects of the dividend
initiation decision. Specifically, we empirically investigate the determinants of the: (i) dividend
initiation decision, (ii) dividend level at initiation, (iii) abnormal announcement returns at
dividend initiation, and (iv) time-to-dividend initiation. In our examination of the above aspects
of dividend initiation, our primary focus is on information-signaling explanations for dividends.
We, however, explicitly control for determinants suggested by the other major theories of
dividends, namely, residual, tax, transactions costs, clientele, agency, catering, and life cycle.
Unlike recent empirical papers that use exogenous identification to examine corporate policies,
our inferences are based on regression analyses. Given the well-known identification issues
associated with regression analysis, inferences regarding causation should be made with care.
33
Our examinations of the dividend initiation decision, the stock price effects associated
with dividend initiations, and the timing of dividend initiation highlight some novel findings that
offer strong support for the assumptions and predictions in extant dividend-signaling theories.
First, we find evidence consistent with the necessary and sufficient condition for a signaling
equilibrium in John and Williams (1985), which states that a firm will initiate dividends when its
total cash needs are greater than the supply of cash from the firm‘s operations. Second, we find
evidence in support of the dividend signaling framework in Allen, Bernardo, and Welch (2000)
in which firms signal higher quality by paying dividends to attract the better informed
institutional investors. Third, consistent with the predictions of the dividend signaling models of
John and Williams (1985) and Kale and Noe (1990), we find a significantly negative relation
between the probability of dividend initiation and both the beta of firm assets and residual
standard deviation of stock returns.
Finally, with the exception of tax-based models and the residual theory of dividends, in
most models where dividends have an effect (e.g., the agency-based models), the announcement
of higher level of dividends will have a greater impact on stock prices. The contribution of our
paper is to show that the dividend initiation decision and the associated announcement-period
abnormal returns are related to the likelihood that a firm will issue seasoned equity and to the
level of deficit institutional ownership in the firm. The positive relations of both these variables
to the probability of dividend initiation and their respective negative and positive relations with
dividend initiation announcement returns are not predicted by any of the alternative models that
propose investor preference for dividends.
In their survey of CFOs, Brav, Graham, Harvey, and Michaely (2005) conclude that
while executives believe that dividend decisions provide information to market participants, they
34
do not use these decisions as a costly signal to convey their true value to the market. While
managers may not ―consciously‖ use dividend decisions as a costly signal, our findings indicate
that their actions are consistent with this kind of behavior. DeAngelo, DeAngelo, and Skinner
(2000) state that ―…the juxtaposition of continued strong interest in signaling models on the one
hand, with the limited empirical support on the other, has made the relevance of dividend
signaling an important unresolved issue in corporate finance.‖ The empirical findings we report
in this paper suggest that firms use dividends as a credible mechanism for conveying information
to markets and, as a result, highlight the relevance of dividend signaling models towards
explaining corporate dividend policy decisions.
35
Appendix
To estimate the probability that the firm will issue equity, PROBSEO02 (PROBSEO12), over the
observation year and the following two years (following two years); we estimate a probit regression
where the dependent variable is SEO02 (SEO12). To compute the predicted value of the level of
institutional ownership, we estimate an OLS regression where INSTOWN is the dependent variable. We
then compute the deficit in institutional ownership, DEFICIT_INSTOWN, as the difference between the
predicted value and the actual value of institutional ownership for that observation year. In these tables,
the explanatory variables are drawn from the extant literature. The coefficents from these regressions are
reported in Table A1.
TABLE A1
Predicting the Probability of a Seasoned Equity Issue and the Level of Institutional Ownership
VARIABLES
Industry dummies
MBA
LTA
LTDA
AGE
Model 1
(SEO02)
Model 2
(SEO12)
Model 3
(INSTOWN)
Yes
Yes
Yes
0.053***
(17.07)
0.069***
(10.32)
0.325***
(5.86)
-0.066***
(-26.30)
0.026***
(7.35)
-0.035***
(-4.56)
0.532***
(8.57)
-0.073***
(-22.82)
-9.072***
(-18.09)
-9.496***
(-15.61)
0.009***
(25.95)
0.093***
(135.70)
-0.125***
(-22.22)
0.004***
(20.65)
0.009***
(7.76)
-2.219***
(-59.37)
0.030***
(40.34)
1.232***
(10.47)
0.965***
(10.75)
0.067
(1.15)
0.343***
(7.69)
-0.229***
(-7.27)
0.006
(1.62)
0.841***
(6.40)
1.149***
(11.26)
0.230***
(3.42)
0.448***
(8.74)
-0.294***
(-7.86)
0.015***
(3.51)
A
RESSTD
TURN
CEA
RDA
ALPHA
ORA
UP
UNDREP
36
DEPA
KZ3FAC
MKTRET
Constant
Observations
-1.437***
(-5.31)
-0.053***
(-10.17)
2.508***
(5.88)
-1.042***
(-19.04)
-0.548*
(-1.89)
-0.031***
(-5.29)
1.183**
(2.46)
-1.055***
(-16.57)
-0.054***
(-13.74)
39,068
39,036
42077
We estimate a probit regression to predict the probability of a seasoned equity offering over a: (i) three-year period
including the observation year (Model 1) and (ii) two-year period subsequent to the observation year (Model 2). In
Model 3, we estimate an OLS regression to predict the level of institutional ownership that the firm should have.
The determinant variables are: (i) MBA - the ratio of the market value (MV) of the firm‘s assets (sum of the MV of
equity and the book value of all debt) to their book value, (ii) LTA is the natural log of total assets of the firm, (iii)
LTDA - ratio of long-term debt to total assets, (iv) AGE – one plus the number of years elapsed between the
observation year and the IPO year, (v) A - the equity of the firm‘s stock divided by 1 plus the debt-equity ratio
where equity is obtained from estimating the market model regression over the observation year, (vi) RESSTD – the
RMSE from the market model estimated to obtain equity, (vii) TURN – the ratio of annual trading volume to shares
outstanding, (viii) CEA - the ratio of the firm‘s capital expenditure to its total assets, (ix) RDA - the ratio of the
firm‘s R&D expenditures to total assets, (x) ALPHA - the fraction of firm equity retained by the original owner in
the IPO, (xi) ORA - the ratio of the firm‘s operating income before depreciation and taxes to total assets, (xii) UP the return to the IPO on the offer date, (xiii) UNDREP - the updated Carter, Dark, and Singh (1998) IPO underwriter
reputation measure, (xiv) DEPA – the depreciation expense over total assets (xv) KZ3FAC– Kaplan-Zingales three
factor measure of financial constraint in which we exclude both Tobin‘s q and dividends-to-assets ratio from the
construction of this index., (xiii) MKTRET – the return on the CRSP value-weighted market index over past
calendar year, (xiv) DIVPREM – the difference between the logarithms of the market-to-book ratios of dividend
payers and non-payers, where book values are used to weight the market-to-book ratios across dividend payers and
non-payers (see Baker and Wurgler, 2004), Variables MBA, RDA, CEA, TA, LTDA, ORA, and TURN are average
values for the observation year and the prior year. Robust z-statistics (Models 1 and 2) and t-statistics (Model 3) are
in parentheses.
*** p<0.01, ** p<0.05, * p<0.1
37
References
Aharony, J., and I. Swary. ―Quarterly Dividend and Earnings Announcements and Stockholders‘
Return: An Empirical Analysis.‖ Journal of Finance, 35 (1980), 1-12.
Allen, F.; A. Bernardo; and I. Welch. ―A Theory of Dividends Based on Tax Clienteles.‖ Journal
of Finance, 55 (2000), 2499-2536.
Allen, F., and G. Faulhaber. ―Signaling by Underpricing in the IPO Market.‖ Journal of
Financial Economics, 23 (1989), 303-323.
Asquith, P., and D. Mullins, Jr. ―The Impact of Initiating Dividend Payments on Shareholders‘
Wealth.‖ Journal of Business, 56 (1983), 27-44.
Badrinath, S.; G. Gay; and J. Kale. ―Patterns of Institutional Investments, Prudence, and the
Managerial ‗Safety-Net‘ Hypothesis.‖ Journal of Risk and Insurance, 56 (1989), 605629.
Baker, M.; J. Stein; and J. Wurgler. ―When does the Market Matter? Stock Prices and the
Investment of Equity-Dependent Firms.‖ Quarterly Journal of Economics, 118 (2003),
969-1005.
Baker, M., and J. Wurgler. ―A Catering Theory of Dividends.‖ Journal of Finance, 59 (2004),
1125-1165.
Banerjee, S.; V. Gatchev; and P. Spindt. ―Stock Market Liquidity and Firm Dividend Policy.
Journal of Financial and Quantitative Analysis, 42 (2007), 369-398.
Benartzi, S.; R. Michaely; and R. Thaler. ―Do Changes in Dividends Signal the Future or the
Past?‖ Journal of Finance, 52 (1997), 1007-1034.
Bhattacharya, S.. ―Imperfect Information, Dividend Policy, and ‗the Bird in the Hand‘ Fallacy.‖
Bell Journal of Economics, 10 (1979), 259-270.
Brav, A.; J. Graham; C. Harvey; and R. Michaely. ―Payout Policy in the 21st Century.‖ Journal
of Financial Economics, 77 (2005), 483-527.
Carter, R., and S. Manaster. ―Initial Public Offering and Underwriter Reputation.‖ Journal of
Finance, 45 (1990), 1045-1067.
Carter, R.; F. Dark; and A. Singh. ―Underwriter Reputation, Initial Returns, and the Long-Run
Performance of IPO Stocks.‖ Journal of Finance, 53 (1998), 285-311.
Cox, D. R. ―Regression Models and Life Tables.‖ Journal of Royal Statistical Society, 34 (1972),
187-220.
DeAngelo, H.; L. DeAngelo; and D. Skinner. ―Special Dividends and the Evolution of Dividend
Signaling.‖ Journal of Financial Economics, 57 (2000), 309-354.
38
DeAngelo, H.; L. DeAngelo; and D. Skinner. ―Corporate Payout Policy.‖ Foundations and
Trends in Finance, 3 (2008), 95-287.
DeAngelo, H.; L. DeAngelo; and R. Stulz. ―Dividend Policy and the Earned/Contributed Capital
Mix: A Test of the Life Cycle Theory.‖ Journal of Financial Economics, 81 (2006), 227254.
Del Guercio, D. ―The Distortion Effect of Prudent-Man Laws on Institutional Equity
Investments.‖ Journal of Financial Economics, 40 (1996), 31-62.
Dyl, E., and R. Weigand. ―The Information Content of Dividend Initiations: Additional
Evidence.‖ Financial Management, 27 (1998), 27-35.
Eades, K. ―Empirical Evidence on Dividends as a Signal of Firm Quality.‖ Journal of Financial
and Quantitative Analysis, 17 (1982), 471-502.
Eckbo, E., and R. Masulis. ―Seasoned Equity Offerings: A Survey.‖ In Finance (North-Holland
Series of Handbooks in Operations Research and Management Science), R. Jarrow, V.
Maksimovic, and W. Ziemba, eds. North Holland (1995).
Fama, E., and K. French. ―Disappearing Dividends: Changing Firm Characteristics or Lower
Propensity to Pay?‖ Journal of Financial Economics, 60 (2001), 3-43.
Greene, W. Econometric Analysis, Upper Saddle River, NJ: Prentice Hall (2007).
Grinblatt, M., and C. Hwang. ―Signaling and the Pricing of New Issues.‖ Journal of Finance, 44
(1989), 393-420.
Grullon, G., and R. Michaely. ―Dividends, Share Repurchases, and the Substitution Hypothesis.‖
Journal of Finance, 57 (2002), 1649-1684.
Grullon, G.; R. Michaely; and B. Swaminathan. ―Are Dividend Changes a Sign of Firm
Maturity.‖ Journal of Business, 75 (2002), 387-424.
Healy, P., and K. Palepu. ―Earnings Information Conveyed by Dividend Initiations and
Omissions.‖ Journal of Financial Economics, 21, 149-176.
Huber, P. ―The Behavior of Maximum Likelihood Estimators under Non Standard Conditions.‖
In Procedures of the Fifth Annual Berkeley Symposium on Mathematical Statistics and
Probability, Vol. 1, L. LeCam and J. Neyman, eds Berkeley, CA: University of
California Press (1967).
Jagannathan M.; C. Stephens; and M. Weisbach. ―Financial Flexibility and the Choice between
Dividends and Stock Repurchases.‖ Journal of Financial Economics, 57 (2000), 355-384.
Jensen, M. ―Agency Costs of Free Cash Flow, Corporate Finance and Takeovers.‖ American
Economic Review, 76 (1986), 323-329.
39
John, K., and J. Williams. ―Dividends, Dilution and Taxes: A Signaling Equilibrium.‖ Journal
of Finance, 40 (1985), 1053-1070.
Kalay, A. ―Signaling, Information Content, and the Reluctance to Cut Dividends.‖ Journal of
Financial and Quantitative Analysis, 15 (1980), 855-869.
Kalbfleisch, J., and R. Prentice. The Statistical Analysis of Failure Time Data. New York, NY:
Wiley (1980).
Kale, J., and T. Noe. ―Dividends, Uncertainty, and Underwriting Costs under Asymmetric
Information.‖ Journal of Financial Research, 4 (1990), 265-277.
Kaplan, S., and L. Zingales. ―Do Investment-Cash Flow Sensitivities Provide Useful Measures
of Financial Constraints?‖ Quarterly Journal of Economics, 112 (1997), 169-215.
Lang, L., and R. Litzenberger. ―Dividend Announcements: Cash Flow Signaling Vs. Free Cash
Flow Hypothesis?‖ Journal of Financial Economics, 24 (1989), 181-191.
Lintner, J. ―Distribution of Incomes of Corporations among Dividends, Retained Earnings, and
Taxes.‖ American Economic Review, 46 (1956), 97-113.
Lipson, M.; C. Maquieira; and W. Megginson. ―Dividend Initiations and Earnings Surprises.‖
Financial Management, 27 (1998), 36-45.
Loughran, T., and J. Ritter. ―Why has IPO Underpricing Changed over Time?‖ Financial
Management, 33 (2004), 5-37.
McDonald, J., and R. Moffitt. ―The Uses of Tobit Analysis.‖ Review of Economics and Statistics,
62 (1980), 318-321.
Miller, M., and F. Modigliani. ―Dividend Policy, Growth and the Valuation of Shares.‖ Journal
of Business, 34 (1961), 11-33.
Miller, M., and K. Rock. ―Dividend Policy under Asymmetric Information.‖ Journal of Finance,
40 (1985), 1021-1051.
Miller, M. ―The Information Content of Dividends.‖ In Macroeconomics and Finance: Essay in
Honor of Franco Modigliani, R. Dornbusch and S. Fischer, eds., Cambridge, MA: MIT
Press, (1987).
Pettit, R. ―Dividend Announcements, Security Performance, and Capital Market Efficiency.‖
Journal of Finance, 28 (1972), 993-1007.
Rogers, W. ―Regression Standard Errors in Clustered Samples.‖ Stata Technical Bulletin, 13
(1993), 19-23.
Ross, S.; R. Westerfield; and J. Jaffe. Corporate Finance. New York, NY: McGraw-Hill Irwin
(2005).
40
Rozeff, M. ―Growth, Beta, and Agency Costs as Determinants of Dividend Payout Ratios.‖
Journal of Financial Research, 5 (1982), 249-259.
Shumway, T. ―Forecasting Bankruptcy More Accurately: A Simple Hazard Model.‖ Journal of
Business, 74 (2001), 101-124.
Smith, C., and R. Watts. ―The Investment Opportunity Set and Corporate Financing, Dividend,
and Compensation Policies.‖ Journal of Financial Economics, 32 (1992), 263-292.
Venkatesh, P. ―The Impact of Dividend Initiation on the Information Content of Earnings
Announcements and Returns Volatility.‖ Journal of Business, 46 (1989), 191-211.
Warner, J.; R. Watts; and K. Wruck. ―Stock Prices and Top Management Changes.‖ Journal of
Financial Economics, 20 (1988), 461-492.
Weisbach, M. ―Outside Directors and CEO Turnover.‖ Journal of Financial Economics, 20
(1988), 431-460.
Welch, I. ―Seasoned Offerings, Imitation Costs, and the Underpricing of Initial Public
Offerings.‖ Journal of Finance, 44 (1989), 421-449.
White, H. ―A Heteroskedasticity-Consistent Covariance Matrix and a Direct Test for
Heteroskedasticity.‖ Econometrica, 48 (1980), 817-838.
Wooldridge, J. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT
Press (2002).
Yoon, P., and L. Starks. ―Signaling, Investment Opportunities, and Dividend Announcements.‖
Review of Financial Studies, 8 (1995), 995-1018.
41
TABLE 1
The Timing of the Dividend Initiation Decision by Firms Conducting IPOs during 1979-2005
Year
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Totals
% DI
# IPOs
38
79
226
83
448
229
203
327
266
114
116
116
277
372
467
385
422
624
403
237
416
318
59
54
47
138
124
6,588
Total DI
13
15
45
15
85
43
44
66
63
24
20
19
47
60
64
47
35
37
37
14
22
6
7
7
5
15
18
873
zero
4
6
13
3
23
13
10
13
23
12
8
6
8
19
17
19
14
9
6
3
7
1
2
2
2
9
16
268
(0.307)
Number of dividend initiating firms in each year after the IPO year
one
two
three
four
five
six
1
1
2
0
0
0
1
1
0
1
0
0
8
0
2
2
2
2
3
1
2
0
1
2
12
5
3
4
7
4
8
3
2
4
2
1
5
3
3
4
3
3
20
7
5
2
1
4
11
6
2
5
2
3
6
1
0
1
0
0
6
0
1
1
2
0
1
4
1
4
0
1
15
1
2
2
1
1
14
2
2
1
2
0
12
4
1
2
3
5
5
2
2
0
2
1
2
2
0
2
1
1
5
4
3
2
1
0
3
1
2
2
0
8
3
2
1
0
1
3
1
2
0
2
3
4
0
0
3
1
1
0
1
2
0
1
1
n/a
1
2
1
1
n/a
n/a
2
1
0
n/a
n/a
n/a
5
1
n/a
n/a
n/a
n/a
n/a
2
n/a
n/a
n/a
n/a
153
58
40
44
36
43
(0.175)
(0.066)
(0.046)
(0.050)
(0.041)
(0.049)
seven
0
1
3
1
7
1
2
4
3
0
0
0
2
0
1
0
1
6
7
0
3
n/a
n/a
n/a
n/a
n/a
n/a
42
(0.048)
eight
0
0
0
1
4
0
3
1
2
1
0
0
0
1
2
1
8
2
7
1
n/a
n/a
n/a
n/a
n/a
n/a
n/a
34
(0.039)
> eight
5
5
13
1
16
9
8
9
6
3
2
2
15
19
17
15
4
5
1
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
155
(0.178)
42
Table 1 presents the distribution of the 1979-2005 IPO firms that appear on both CRSP and Compustat databases and the timing of their dividend initiations as
determined from the ―distribution codes‖ in the CRSP database. The sample excludes IPOs by financial and utility firms.
n/a: not applicable
43
TABLE 2
The Evolution of PROBSEO Prior to Dividend Initiation Year (t)
Div. Init. Yr. (t)
Year (t – 3)
Year (t – 2)
Year (t – 1)
Panel A. The Evolution of PROBSEO02 prior to dividend initiation year (t)
325
546
No. of Obs.
364
423
780
17.051
18.694
Mean (%)
16.092
16.904
20.983
3.932***
2.289***
Mean (t – (t – i))
4.891***
4.079***
(5.78)
(3.91)
(t-stat)
(7.54)
(6.56)
17.495
17.540
Median (%)
15.514
15.674
21.529
4.034***
3.989***
Med (t – (t – i))
6.015***
5.855***
(5.76)
(3.90)
(Wilc. z-stat)
(7.42)
(6.46)
Panel B. The Evolution of PROBSEO12 prior to dividend initiation year (t)
325
546
No. of Obs.
364
423
780
9.520
10.665
Mean (%)
8.861
9.386
12.116
2.596***
1.451***
Mean (t – (t – i))
3.255***
2.729***
(5.27)
(3.40)
(t-stat)
(7.03)
(6.12)
8.060
9.330
Median (%)
7.282
7.389
12.163
4.103***
2.833***
Med (t – (t – i))
4.881***
4.774***
(5.49)
(3.66)
(Wilc. z-stat)
(6.78)
(6.03)
Table 2 presents the evolution in periods before the dividend initiation (year t) of PROBSEO02 and
Year (t – 4)
PROBSEO12. PROBSEO02 is the probability of a seasoned equity offering in the next couple of years
including the current calendar year and PROBSEO12 is the probability of a seasoned equity offering in
the next couple of years.
*** p<0.01, ** p<0.05, * p<0.1
44
TABLE 3
The Evolution of INSTOWN and DEFICIT_INSTOWN Relative to Dividend Initiation Year (t)
Panel A. The Evolution of INSTOWN around dividend initiation year (t)
Year (t-4)
Year (t-3)
Year (t-2)
Year (t-1)
No. of Obs.
340
374
431
576
Mean (%)
35.471
35.694
37.168
36.620
Mean (t – (t ± i))
1.408
1.186
-0.289
0.259
(t-stat)
(0.78)
(0.69)
(-0.18)
(0.17)
Median (%)
25.207
28.864
30.208
31.437
Med (t – (t ± i))
6.351
2.694
1.350
0.121
(Wilc. z-stat)
(1.07)
(0.68)
(-0.13)
(0.27)
Panel B. The Evolution of DEFICIT_INSTOWN around dividend initiation year (t)
Year (t-4)
Year (t-3)
Year (t-2)
Year (t-1)
Year (t)
Year (t+1)
Year (t+2)
Year (t+3)
Year (t+4)
845
36.879
692
39.871
-2.992**
(-2.10)
35.052
-3.494**
(-2.29)
630
42.873
-5.994***
(-4.10)
39.566
-8.008***
(-4.31)
583
43.787
-6.908***
(-4.63)
39.291
-7.733***
(-4.92)
502
43.512
-6.633***
(-4.31)
41.607
-10.049***
(-4.70)
Year (t+1)
Year (t+2)
Year (t+3)
Year (t+4)
31.558
Year (t)
No. of Obs.
333
363
424
559
780
632
Mean (%)
1.190
1.571
1.811
2.635
3.510
2.671
Mean (t – (t ± i))
2.320*
1.940
1.700
0.876
0.836
(t-stat)
(1.81)
(1.60)
(1.46)
(0.81)
(0.77)
Median (%)
3.877
3.636
3.570
4.464
5.014
5.279
Med (t – (t ± i))
1.137
1.378
1.444
0.550
-0.265
(Wilc. z-stat)
(1.60)
(1.49)
(1.34)
(0.54)
(-0.36)
Table 3 presents the evolution in periods around the dividend initiation (year t) of INSTOWN, and DEFICIT_INSTOWN.
567
524
455
2.196
2.047
1.342
1.314
1.463
2.168*
(1.18)
(1.29)
(1.83)
4.463
3.917
1.619
0.551
1.097
3.395*
(0.93)
(1.20)
(1.91)
INSTOWN is total institutional ownership,
and DEFICIT_INSTOWN is the deficit in institutional ownership measured as the difference between the predicted institutional ownership and the actual institutional
ownership.
*** p<0.01, ** p<0.05, * p<0.1
45
TABLE 4
Means and Medians of Firm Characteristics of Dividend-Initiating and Non-Dividend-Initiating Firms
Full Sample
Variable
SEO12(%)
Dividend-initiating (DI)
Non-dividend-initiating (NDI)
t-stat
Wilc. Z
#
Mean
Median
#
Mean
Median
#
Mean
Median
DI – NDI
DI – NDI
49,952
8.080
0.000
871
11.711
0.000
49,081
8.015
0.000
3.97***
3.97***
***
3.10***
SEO02 (%)
49,990
13.921
0.000
873
17.526
0.000
49,117
13.857
0.000
3.10
PROBSEO12 (%)
43,822
8.200
6.443
780
12.116
12.163
43,042
8.130
6.369
16.20***
15.27***
PROBSEO02 (%)
43,822
14.457
12.607
780
20.983
21.529
43,042
14.339
12.464
17.70***
17.59***
DEFICIT_INSTOWN (%)
42,077
0.000
1.775
780
3.510
5.014
41,287
-0.067
1.730
5.49***
5.02***
DIVYLD1 (%)
861
2.012
0.995
DIVYLD15 (%)
832
2.514
1.006
MBA (%)
49,228
2.419
1.506
866
1.839
1.391
48,362
2.430
1.510
-10.73***
-3.40***
RDA (%)
49,605
8.225
1.299
873
1.724
0.000
48,732
8.342
1.460
-43.19***
-16.07***
CEA (%)
49,896
7.099
4.587
871
7.273
5.186
49,025
7.096
4.576
0.67
3.679***
TA ($ m.)
49,990
245.32
55.26
873
609.85
165.29
49,117
238.84
54.37
10.70***
18.40***
LTDA (%)
49,461
14.833
6.522
868
18.264
13.597
48,593
14.772
6.412
5.46***
7.40***
A
RESSTD (%)
44,294
1.245
1.106
844
0.969
0.908
43,450
1.250
1.112
-12.14***
-7.68***
47,848
4.873
4.138
873
2.779
2.483
46,975
4.881
4.717
-42.09
***
-30.06***
ORA (%)
49,841
-2.472
7.970
868
18.340
17.727
48,373
-2.841
7.718
45.35***
27.00***
UP (%)
49,971
17.183
6.897
873
10.254
3.982
49,098
17.306
6.985
-10.11***
-5.75***
ALPHA (%)
49,294
67.161
69.141
853
68.910
71.631
48,441
67.130
69.101
3.29***
5.47***
***
9.85***
UNDREP
48,713
6.391
7.001
847
7.281
8.000
47,866
6.375
7.001
10.13
TURN (%)
47,563
1.500
1.037
854
1.059
0.777
46,709
1.508
1.045
-12.35***
-9.66***
AGE (Years)
49,990
5.118
4.000
873
4.073
2.000
49,117
5.136
4.000
-6.34***
-10.44***
DIVPREM (%)
49,990
-14.202
-13.960
873
-11.563
-12.930
49,117
-14.249
-13.960
7.59***
6.47***
***
26.35***
NYSE (%)
49,990
9.798
0.000
873
36.083
0.000
49,117
9.331
0.000
16.40
REPUR (t, t) (%)
44,760
14.973
0.000
811
20.222
0.000
43,949
14.876
0.000
4.23***
4.23***
REA (%)
49,856
-87.97
-5.22
869
14.685
18.243
48,987
-89.79
-6.20
42.00***
25.94***
46
Table 4 presents the means and medians of firm characteristics and the statistical significance of the differences in these statistics for dividend-initiating and nondividend-initiating firms. The firm characteristics are: (i) SEO02 (SEO12) – dummy variable that equals one if the IPO firm conducts a primary and/or secondary
seasoned equity issue in the three-year (two-year) period that includes (excludes) the observation year and (but includes) the two years following the observation year.,
(ii) PROBSEO02 (PROBSEO12) – the predicted value of the probability of a seasoned equity offering from a probit regression where SEO02 (SEO12) is the dependent
variable, (iii) DEFICIT_INSTOWN - deficit in institutional ownership measured as the difference between the predicted institutional ownership and the actual institutional
ownership, (iv) DIVYLDt – the annual dividend divided by the stock price t days before initiation, (v) MBA – the ratio of the market value (MV) of the firm‘s assets
(sum of the MV of equity and the book value of all debt) to their book value, (vi) RDA – the ratio of the firm‘s R&D expenditures to total assets, (vii) CEA – the ratio of
the firm‘s capital expenditure to its total assets, (viii) TA – the book value of the firm‘s total assets in millions of dollars, (ix) LTDA – ratio of long-term debt to total
assets, (x) A – the equity of the firm‘s stock divided by 1 plus the debt-equity ratio where equity is obtained from estimating the market model regression over the
observation year, (xi) RESSTD – the RMSE from the market model regression estimated to obtain equity, (xii) ORA – the ratio of the firm‘s operating income before
depreciation and taxes to total assets, (xiii) UP – the return to the IPO on the offer date, (xiv) ALPHA – the fraction of firm equity retained by the original owner in the
IPO, (xv) UNDREP – the updated Carter, Dark, and Singh (1998) IPO underwriter reputation measure, (xvi) TURN – the ratio of annual trading volume to shares
outstanding, (xvii) AGE – one plus the number of years elapsed between the observation year and the IPO year, (xviii) DIVPREM – the difference between the
logarithms of the market-to-book ratios of dividend payers and non-payers, where book values are used to weight the market-to-book ratios across dividend payers and
non-payers (see Baker and Wurgler, 2004), (xix) NYSE – dummy variable that equals one if the firm is listed on the NYSE, else it equals zero, (xx) REPUR – dummy
variable that equals one if the firm repurchases shares in the dividend initiation year, else it equals zero, and (xxi) REA – retained earnings over total assets. Variables
MBA, RDA, CEA, TA, LTDA, ORA, and TURN are average values for the observation year and the prior year.
*** p<0.01, ** p<0.05, * p<0.1
47
TABLE 5
Probit Regression Results on Determinants of the Dividend Initiation Decision
VARIABLES
SEO02
Heckman treatment effect models
Model 1
Model 2
Probit models
Model 3
Model 4
1.301**
(2.27)
SEO12
1.928***
(2.92)
PROBSEO02
2.936***
(5.85)
PROBSEO12
DEFICIT_INSTOWN
MBA
CEA
RDA
LTDA
A
RESSTD
ORA
UP
ALPHA
UNDREP
TURN
AGE
DIVPREM
NYSE
REPUR
REA
LTA
LAMBDA02
0.381***
(3.56)
-0.066***
(-3.58)
-1.571***
(-4.75)
-2.538***
(-3.40)
-0.676***
(-4.92)
-0.106***
(-3.28)
-10.746***
(-3.58)
2.302***
(7.00)
-0.052
(-0.40)
0.029
(0.20)
0.000
(0.03)
-0.096***
(-4.13)
-0.008
(-0.78)
0.015***
(6.98)
0.175***
(3.43)
0.024
(0.54)
0.232**
(2.11)
0.087***
(4.08)
-0.794**
(-2.36)
LAMBDA12
Constant
-1.749***
0.393***
(3.53)
-0.054***
(-3.14)
-1.506***
(-5.03)
-2.576***
(-3.61)
-0.802***
(-5.37)
-0.109***
(-3.44)
-10.253***
(-3.45)
2.192***
(6.28)
-0.031
(-0.26)
-0.053
(-0.37)
-0.004
(-0.52)
-0.096***
(-4.21)
-0.009
(-1.04)
0.015***
(8.14)
0.186***
(3.51)
0.027
(0.64)
0.244*
(1.94)
0.122***
(6.20)
0.371***
(3.36)
-0.096***
(-4.50)
-1.969***
(-6.39)
-2.904***
(-3.88)
-0.779***
(-5.46)
-0.120***
(-3.85)
-7.546***
(-2.63)
2.206***
(6.50)
0.035
(0.29)
-0.008
(-0.06)
-0.002
(-0.29)
-0.089***
(-3.97)
0.016*
(1.74)
0.016***
(8.22)
0.167***
(3.13)
0.036
(0.86)
0.242*
(1.91)
0.076***
(3.85)
4.313***
(6.86)
0.349***
(3.11)
-0.069***
(-3.87)
-1.877***
(-6.33)
-3.100***
(-4.17)
-1.009***
(-6.76)
-0.120***
(-3.88)
-6.368**
(-2.20)
1.989***
(5.85)
0.070
(0.59)
-0.140
(-1.01)
-0.010
(-1.20)
-0.091***
(-4.03)
0.013*
(1.92)
0.016***
(8.30)
0.180***
(3.37)
0.037
(0.87)
0.255**
(1.98)
0.155***
(7.17)
-1.068***
(-2.88)
-1.805***
-2.017***
-2.186***
48
Industry dummies
Observations
Change in implied probability
∆Prob (SEO02) (%)
∆Prob (SEO12) (%)
∆Prob (PROBSEO02) (%)
∆Prob (PROBSEO12) (%)
(-9.25)
Yes
38,805
(-10.33)
Yes
38,773
(-11.59)
Yes
38,805
(-11.67)
Yes
38,805
16.28
(1.33, 17.61)
36.98
(1.34, 38.32)
1.58
(0.78, 2.36)
1.38
(0.77, 2.15)
∆Prob (DEFICIT
_INSTOWN) (%)
0.45
0.44
0.32
0.29
(1.93, 2.38)
(1.82, 2.26)
(1.33, 1.65)
(1.30, 1.59)
-0.68
-0.67
-0.57
-0.54
∆Prob (A) (%)
(2.48, 1.80)
(2.36, 1.69)
(1.77, 1.20)
(1.71, 1.17)
∆Prob (RESSTD) (%)
-1.52
-1.38
-0.79
-0.66
(2.89, 1.37)
(2.71, 1.33)
(1.86, 1.07)
(1.75, 1.09)
Table 5 presents the findings from estimating probit regressions on the sample of all the firms that conducted IPOs during
the period 1979 – 2005. The dependent variable D for the probit regressions is constructed as follows. Firms are tracked
by the year of their IPO. For example, consider the group of 38 firms (Table I) that conducted an IPO in 1979, the four
firms that initiated dividends in 1979 are assigned the value D = 1, the remaining 34 are assigned D = 0. Of these 34, in
1980, one initiated dividends, and is assigned D = 1 and the remaining 33 are assigned D = 0. This process is continued
till the end of the investigation period 2006 for IPO firms in each of the sample years. In Models 1 and 2, we employ the
Heckman two-step treatment effect model. In the first stage, we estimate probit models with SEO02 (Model 1) or SEO12
(Model 2) as the dependent variable, where SEO02 (SEO12) is a dummy variable that equals one if the firm issues equity
in the appropriate time window, else it equals zero. We then include the Inverse Mills ratio (LAMBDA02 or
LAMBDA12) from the first stage as an additional independent variable in the second stage probit regression modeling the
dividend initiation decision. In Models 3 and 4, we use the probability of an equity issue, PROBSEO02 (Model 3) and
PROBSEO12 (Model 4) estimated from probit models where SEO02 and SEO12 are the dependent variables, respectively.
DEFICIT_INSTOWN is the deficit in institutional ownership measured as the difference between the predicted
institutional ownership and the actual institutional ownership. The other determinant variables are: (i) MBA – the ratio of
the market value (MV) of the firm‘s assets (sum of the MV of equity and the book value of all debt) to their book value,
(ii) CEA – the ratio of the firm‘s capital expenditure to its total assets, (iii) RDA – the ratio of the firm‘s R&D
expenditures to total assets, (iv) LTDA – ratio of long-term debt to total assets, (v) A – the equity of the firm‘s stock
divided by 1 plus the debt-equity ratio where equity is obtained from estimating the market model regression over the
observation year, (vi) RESSTD – the RMSE from the market model estimated to obtain equity, (vii) ORA – the ratio of the
firm‘s operating income before depreciation and taxes to total assets, (viii) UP – the return to the IPO on the offer date,
49
(ix) ALPHA – the fraction of firm equity retained by the original owner in the IPO, (x) UNDREP – the updated Carter,
Dark, and Singh (1998) IPO underwriter reputation measure, (xi) TURN – the ratio of annual trading volume to shares
outstanding, (xii) AGE – one plus the number of years elapsed between the observation year and the IPO year, (xiii)
DIVPREM – the difference between the logarithms of the market-to-book ratios of dividend payers and non-payers, where
book values are used to weight the market-to-book ratios across dividend payers and non-payers (see Baker and Wurgler,
2004), (xiv) NYSE – dummy variable that equals one if the firm is listed on the NYSE, else it equals zero, (xv) REPUR –
dummy variable that equals one if the firm repurchases shares in the observation year, else it equals zero, (xvi) REA retained earnings divided by total assets, and (xvii) LTA - the natural log of total assets of the firm. Variables MBA, RDA,
CEA, TA, LTDA, ORA, and TURN are average values for the observation year and the prior year. ∆Prob is the change in
the implied probability as the value of the variable changes from its 25 th to 75th percentile value (0 to 1) for continuous
(dummy) variables, holding all other variables at their median values. The t-values are in parentheses and reflect standard
errors that are bootstrapped using 100 replications and corrected for the cluster sample problem arising from multiple
observations across years for each firm.
*** p<0.01, ** p<0.05, * p<0.1
50
TABLE 6
Determinants of the Dividend Initiation and Time-to-Initiation Decisions: Cox Proportional Hazard
Models
Model 1
VARIABLES
Industry dummies
PROBSEO02
Model 2
Coefficient
Yes
Hazard Ratio
2.270***
(2.67)
1.0230
PROBSEO12
DEFICIT_INSTOWN
MBA
CEA
RDA
LTDA
A
RESSTD
ORA
UP
ALPHA
UNDREP
TURN
AGE
DIVPREM
NYSE
REPUR
REA
LTA
Observations
0.439**
(2.05)
-0.039
(-1.26)
-1.293**
(-2.49)
-6.525***
(-4.87)
-0.562**
(-2.02)
-0.170***
(-4.12)
-6.472**
(-2.01)
2.921***
(6.98)
0.196
(0.68)
0.490
(1.13)
-0.002
(-0.08)
-0.129***
(-2.92)
0.043**
(2.42)
0.010***
(6.04)
0.311**
(2.35)
0.068
(0.94)
0.394**
(2.28)
0.193***
(4.47)
38,934
1.0044
0.9996
0.9872
0.9368
0.9944
0.8432
0.9373
1.0296
1.0020
1.0049
0.9982
0.9987
1.0437
1.0104
1.3648
1.0699
1.0040
1.2123
Coefficient
Yes
Hazard Ratio
3.778***
(4.16)
0.418*
1.0385
(1.94)
-0.020
(-0.80)
-1.297***
(-2.72)
-6.756***
(-5.11)
-0.763***
(-2.65)
-0.171***
(-4.18)
-5.072
(-1.64)
2.729***
(6.51)
0.247
(0.87)
0.376
(0.86)
-0.009
(-0.36)
-0.130***
(-2.95)
0.046***
(3.04)
0.010***
(6.23)
0.316**
(2.36)
0.067
(0.93)
0.410**
(2.33)
0.259***
(5.55)
38,934
1.0042
0.9998
0.9871
0.9347
0.9924
0.8432
0.9505
1.0277
1.0025
1.0038
0.9914
0.9987
1.0469
1.0104
1.3718
1.0694
1.0041
1.2955
51
Table 6 presents the findings from estimating Cox proportional hazard models on the sample of all the firms that
conducted IPOs during the period 1979-2005. The time-to-initiation for dividend initiators is measured as the
number of months elapsed between the initiation month and the beginning of each year. We predict the probability
of an equity issue, PROBSEO02 and PROBSEO12 by estimating probit models where SEO02 and SEO12 are the
dependent variables, respectively, and employ these predicted values as independent variables in the Cox
proportional hazard model regressions. DEFICIT_INSTOWN is the deficit in institutional ownership measured as
the difference between the predicted institutional ownership and the actual institutional ownership. The other
determinant variables are: (i) MBA - the ratio of the market value (MV) of the firm‘s assets (sum of the MV of
equity and the book value of all debt) to their book value, (ii) CEA - the ratio of the firm‘s capital expenditure to its
total assets, (iii) RDA - the ratio of the firm‘s R&D expenditures to total assets, (iv) LTDA - ratio of long-term debt
to total assets, (v) A - the equity of the firm‘s stock divided by 1 plus the debt-equity ratio where equity is obtained
from estimating the market model regression over the observation year, (vi) RESSTD – the RMSE from the market
model estimated to obtain equity, (vii) ORA - the ratio of the firm‘s operating income before depreciation and taxes
to total assets, (viii) UP - the return to the IPO on the offer date, (ix) ALPHA - the fraction of firm equity retained by
the original owner in the IPO, (x) UNDREP - the updated Carter, Dark, and Singh (1998) IPO underwriter
reputation measure, (xi) TURN – the ratio of annual trading volume to shares outstanding, (xii) AGE – one plus the
number of years elapsed between the observation year and the IPO year, (xiii) DIVPREM – the difference between
the logarithms of the market-to-book ratios of dividend payers and non-payers, where book values are used to
weight the market-to-book ratios across dividend payers and non-payers (see Baker and Wurgler, 2004), (xiv) NYSE
- dummy variable that equals one if the firm is listed on the NYSE, else it equals zero, (xv) REPUR - dummy
variable that equals one if the firm repurchases shares in the observation year, else it equals zero, (xvi) REA retained earnings divided by total assets, and (xvii) LTA - the natural log of total assets of the firm. Variables MBA,
RDA, CEA, TA, LTDA, ORA, and TURN are average values for the observation year and the prior year. The tvalues are in parentheses and reflect standard errors that are bootstrapped using 100 replications and corrected for
the cluster sample problem arising from multiple observations across years for each firm.
*** p<0.01, ** p<0.05, * p<0.1
52
TABLE 7
Announcement Period Abnormal Returns of Dividend Initiations
Mean
Three-day Cumulative Abnormal Returns (%)
Median
Number of Observations
Panel A: Full Sample of Dividend Initiators
Full Sample
1.708***
(0.00)
0.823***
(0.00)
788
Panel B: Subsamples Based on High DIVYLD1 and Low DIVYLD1 Dividend Initiators
High DIVYLD1
Low DIVYLD1
Difference: t-stat/z-stat
2.381***
(0.00)
0.939***
(0.00)
2.57**
1.069***
(0.00)
0.573***
(0.00)
1.59
383
384
Panel C: Subsamples Based on High PROBSEO02 and Low PROBSEO02 Dividend Initiators
High PROBSEO02
Low PROBSEO02
Difference: t-stat/z-stat
0.601**
(0.0)
2.601***
(0.00)
-3.51***
0.555***
(0.01)
1.263***
(0.00)
-2.35**
332
381
Panel D: Subsamples Based on High PROBSEO12 and Low PROBSEO12 Dividend Initiators
High PROBSEO12
Low PROBSEO12
Difference: t-stat/z-stat
0.700**
(0.0)
2.500***
(0.00)
-3.15***
0.650***
(0.01)
1.150***
(0.00)
-2.16**
329
384
Panel E: Subsamples Based on High DEFICIT_INSTOWN and Low DEFICIT_INSTOWN Dividend Initiators
High DEFICIT_INSTOWN
Low DEFICIT_INSTOWN
Difference: t-stat/z-stat
2.040***
(0.00)
1.804***
(0.00)
0.38
1.027***
(0.00)
0.668***
(0.00)
1.34
350
366
Table 7 reports descriptive statistics for the three-day (-1, +1) cumulative abnormal returns on announcements of
dividend initiations computed using the Fama-French three-factor model (with value-weighted market index) both
for the full sample as well as for subsamples of dividend initiators. The subsamples are created based on the median
values of: (i) DIVYLD1 – the dividend yield computed as the annual dividend divided by the stock price the day
before the announcement date, (ii) PROBSEO02 – the probability of a seasoned equity offering in the next couple
of years including the current calendar year, (iii) PROBSEO12 – the probability of a seasoned equity offering in the
53
next couple of years not including the current year, and (iv) DEFICIT_INSTOWN – the deficit in institutional
ownership measured as the difference between the predicted institutional ownership and the actual institutional
ownership. P-values are in parentheses.
*** p<0.01, ** p<0.05, * p<0.1
54
TABLE 8
Cross-sectional Determinants of Announcement Period Abnormal Returns of Dividend Initiations
OLS Regression Model
(CAR)
OLS Regression Model
(Adjusted CAR)
Heckman Regression Model
(CAR)
Variable
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Constant
0.032***
(3.64)
0.424*
(1.84)
-0.120***
(-3.99)
0.027*
(1.69)
0.027***
(2.87)
0.722*
(1.86)
-0.068
(-1.58)
0.033**
(2.18)
-4.332*
(-1.68)
0.032***
(3.58)
0.429
(1.56)
-0.119***
(-3.48)
0.032**
(2.42)
0.028***
(2.82)
0.731*
(1.71)
-0.066
(-1.52)
0.035**
(2.82)
-4.484
(-1.62)
0.057
(1.43)
0.476**
(2.17)
-0.135***
(-3.03)
0.023
(1.58)
0.066*
(1.66)
0.836**
(2.34)
-0.086*
(-1.66)
0.026*
(1.74)
-4.923**
(-2.01)
-0.017
(-1.03)
Yes
DIVYLD1
PROBSEO02
DEFICIT_INSTOWN
DIV_PROBSEO02
Inverse Mills Ratio
Industry dummies
Yes
R-sq.
0.108
Chi-squared
Observations
657
Table 8 reports the results from cross-sectional regressions in which
-0.011
(-0.65)
Yes
0.135
Yes
0.100
Yes
0.125
Yes
27.75***
28.82***
657
655
655
38,353/655
38,353/655
the three-day (-1, +1) cumulative abnormal returns (CAR) on announcements of dividend
initiations computed using the Fama-French three-factor model (with value-weighted market index) as the dependent variable in Models 1, 2, 5, and 6. Models 1 and
2 are estimated as OLS regression models. Models 3 and 4 are also estimated as OLS regression models with the difference that we adjust the CAR for the
probability of dividend initiation. Specifically, we compute the Adjusted CAR as the CAR divided by (1 minus the probability of dividend initiation). Models 5 and 6
are estimated as Heckman selection models. The first-stage regression in the Heckman regression model is a probit regression modeling the dividend initiation
decision as in Table 5. We use this same model to obtain the probability of dividend initiation. The independent variables are: (i) DIVYLD1 – the annual dividend
55
divided by the stock price the day prior to the announcement, (ii) PROBSEO02 – the probability of a seasoned equity offering in the next couple of years including
the current observation year, (iii) DEFICIT_INSTOWN – the deficit in institutional ownership measured as the difference between the predicted institutional
ownership and the actual institutional ownership, and (iv) DIV_PROBSEO02 – the interaction between DIVYLD1 and PROBSEO02. The t-values are in
parentheses and reflect standard errors that are bootstrapped using 100 replications and corrected for the cluster sample problem arising from multiple observations
across years for each firm.
*** p<0.01, ** p<0.05, * p<0.1
56
TABLE 9
Determinants of Dividend Level and Timing of Dividend Initiation: Results for Selected Signaling Variables
Tobit
Dep. Var. →
Ind. Var. ↓
DIVYLD1
Model 1
Model 2
DIVYLD15
Model 1
Model 2
PROBSEO02
0.195***
(4.00)
0.224***
(3.44)
Probit
Postpone/Initiate Dummy
Model 1
Model 2
-3.215***
(-4.68)
Poisson Regressions
Months-to-Initiation
Model 1
Model 2
-1.555***
(-2.62)
0.292***
0.334***
-5.522***
-3.605***
(4.38)
(3.74)
(-5.59)
(-5.05)
0.022***
0.021**
0.030***
0.028***
-0.265
-0.240
-0.508***
-0.486***
DEFICIT_INSTOWN
(2.76)
(2.51)
(2.85)
(2.65)
(-1.56)
(-1.42)
(-3.56)
(-3.41)
0.001***
0.001***
0.002***
0.002***
-0.021***
-0.021***
-0.009***
-0.010***
DIVPREM
(6.10)
(6.10)
(6.78)
(6.80)
(-6.92)
(-7.17)
(-6.33)
(-6.65)
Observations
39,068
39,068
39,068
39,068
3,950
3,950
3,816
3,816
The sample is of firms that went public during 1979-2005 that initiated dividends over the period 1979-2006. A firm is considered to be a dividend paying firm only for the
PROBSEO12
year of initiation. For all earlier years it is treated as a non-dividend paying firm. A firm leaves the sample once it initiates dividends. The table presents the findings from
estimating: (i) Tobit regressions where the dependent variable in the is the dividend yield, DIVYLD1 (DIVYLD15) which is the ratio of the annual dividends per share and
the stock price one day (fifteen days) prior to the announcement of dividend initiation. For non-dividend paying firms, the dividend yield is zero. (ii) Probit regressions
results for the ―postpone versus initiate‖ decision where the dependent variable, DPOST is constructed as follows. Those firms that do not initiate dividends in the IPO year
(year 0) are assigned the value DPOST =1 and those that initiate dividends are assigned the value DPOST = 0 and leave the sample for all subsequent periods. Of the
DPOST = 1 firms from the previous year, those that do not initiate dividends in year 1 are assigned the value DPOST = 1 and those that initiate dividends are assigned the
value DPOST = 0. This criterion is applied until the year 2006 (our last tracking year) is reached. (iii) Poisson regressions where the dependent variable is the months-toinitiation and is measured as the number of months between the initiation month and the beginning of each year. Thus, a firm can potentially enter the sample several times
with the first entry being for the IPO year and the last entry being for the initiation year. We predict the probability of an equity issue, PROBSEO02 (Model 1) and
PROBSEO12 (Model 2) by estimating probit models where SEO02 and SEO12 are the dependent variables, respectively, and employ these predicted values as independent
variables in the regressions. DEFICIT_INSTOWN is the deficit in institutional ownership measured as the difference between the predicted institutional ownership and the
57
actual institutional ownership. DIVPREM is the difference between the logarithms of the market-to-book ratios of dividend payers and non-payers, where book values are
used to weight the market-to-book ratios across dividend payers and non-payers (see Baker and Wurgler, 2004). The other determinant variables (coefficients are similar to
those reported earlier, so are not reported here for brevity) are: (i) MBA – the ratio of the market value (MV) of the firm‘s assets (sum of the MV of equity and the book
value of all debt) to their book value, (ii) CEA – the ratio of the firm‘s capital expenditure to its total assets, (iii) RDA – the ratio of the firm‘s R&D expenditures to total
assets, (iv) LTDA – ratio of long-term debt to total assets, (v) A – the equity of the firm‘s stock divided by 1 plus the debt-equity ratio where equity is obtained from
estimating the market model regression over the observation year, (vi) RESSTD – the RMSE from the market model estimated to obtain equity, (vii) ORA – the ratio of the
firm‘s operating income before depreciation and taxes to total assets, (viii) UP – the return to the IPO on the offer date, (ix) ALPHA – the fraction of firm equity retained by
the original owner in the IPO, (x) UNDREP – the updated Carter, Dark, and Singh (1998) IPO underwriter reputation measure, (xi) TURN – the ratio of annual trading
volume to shares outstanding, (xii) AGE – one plus the number of years elapsed between the observation year and the IPO year, (xiii) NYSE – dummy variable that equals
one if the firm is listed on the NYSE, else it equals zero, (xiv) REPUR – dummy variable that equals one if the firm repurchases shares in the observation year, else it equals
zero, (xv) REA - retained earnings divided by total assets, and (xvi) LTA - the natural log of total assets of the firm. Variables MBA, RDA, CEA, TA, LTDA, ORA, and
TURN are average values for the observation year and the prior year. The t-values are in parentheses and reflect standard errors that are bootstrapped using 100 replications
and corrected for the cluster sample problem arising from multiple observations across years for each firm.
*** p<0.01, ** p<0.05
58
FIGURE 1
Percentage (Cumulative Percentage) of Dividend Initiators
Relative to IPO Year for Firms that Initiate
Percentage of dividend initiatiors
120
120
100
100
80
80
60
60
40
40
20
20
0
0
0
1
2
3
4
5
6
7
8
Cumulative percentage of dividend initiators (%)
Percentage of dividend initiators (%)
Cumulative percentage of dividend initiators
>8
Years relative to IPO year
Figure 1 presents the distribution of dividend initiations by the 1979-2005 IPO firms that appear on both CRSP and
Compustat databases and the timing of their dividend initiations relative to the IPO year. The bars represent the
percent of initiating firms that initiated dividends in the year. The graph represents the cumulative percentage of firms
that initiated dividends.
59
FIGURE 2
Evolution of PROBSEO02 Prior to Dividend Initiation Year
22
21
PROBSEO02 (%)
20
19
18
17
16
15
14
13
t-4
t-3
t-2
t-1
t
Year relative to dividend initiation year
Figure 2 presents the probability of seasoned equity offering (PROBSEO02) during the four years prior to the
initiation year and the year of initiation. PROBSEO02 is the probability of the firm issuing seasoned equity during
the current and two subsequent years. It is computed using the estimated probit regression model in Model 1 in
Table A1 in the Appendix.
60
FIGURE 3
Evolution of PROBSEO12 Prior to Dividend Initiation Year
13
PROBSEO12 (%)
12
11
10
9
8
7
t-4
t-3
t-2
t-1
t
Year relative to dividend initiation year
Figure 3 presents the probability of seasoned equity offering (PROBSEO12) during the four years prior to the
initiation year and the year of initiation. PROBSEO12 is the probability of the firm issuing seasoned equity during
the next two years (not including the current year), and is computed using the estimated probit regression model in
Model 2 in Table A1 in the Appendix.
61
FIGURE 4
Evolution of INSTOWN around Dividend Initiation Year
46
44
INSTOWN (%)
42
40
38
36
34
32
30
t-4
t-3
t-2
t-1
t
t+1
t+2
t+3
t+4
Years relative to dividend initiation year
Figure 4 presents the percent of shares owned by institutions (INSTOWN) around the dividend initiation year t for all
firms that initiated dividends during the sample period.
62
FIGURE 5
Evolution of DEFICIT_INSTOWN around Dividend Initiation Year
4
DEFICIT_INSTOWN (%)
3.5
3
2.5
2
1.5
1
0.5
0
t-4
t-3
t-2
t-1
t
t+1
t+2
t+3
t+4
Years relative to dividend initiation year
Figure 5 presents the deficit in institutional ownership (DEFICIT_INSTOWN) around the dividend initiation year t
for all firms that initiated dividends over the sample period. DEFICIT_INSTOWN is computed as the difference
between the predicted level of institutional ownership and the actual level of institutional ownership. The predicted
level of institutional ownership is obtained using the estimated regression in Model 3 in Table A1 in the Appendix.