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Dividends and Subsequent Profitability: An
Examination of a Dual Dividend Stock Market
Chin-Sheng Huang
Department of Finance, National Yunlin University of Science and Technology, Taiwan
Chun-Fan You
Department of Finance, Transworld University, Taiwan
Sam Ting-Hsin Hsu
Department of Finance, National Yunlin University of Science and Technology, Taiwan
Abstract
For decades, studies on dividend signal hypotheses have focused on cash
dividend markets, with a handful of researchers discussing stock dividends. Utilizing a
unique set of data from a dual dividend stock market, this study identifies the
correlation between dividend changes and future profitability. A fundamental
characteristic of dual dividend payouts is that both components, cash dividends and
stock dividends emit separate dividend signals for subsequent profitability. The ratio
of cash to stock dividends may have a similar impact. Therefore, this study employs a
variant of the Bivariate-Ordered Probit model to screen for the dividend signal sample
used in the hypotheses tests. To analyze dividend signal theories, this study partitions
the sample into three sub-samples according to the ratio of cash to stock dividends.
Empirical evidence strongly indicates that dual dividend changes are positively
associated with future profitability in the balanced dividend subsample. The results of
this study are generally robust in terms of accommodating the factors of stock
repurchases, investment growth opportunities, and the business cycles.
JEL classification: G35
Keywords：Dividend, Dividend Change, Dual Dividend, Dividend Signal

Corresponding author: Department of Finance, TransWorld University, Taiwan. Tel: +886 5
533-4463; Fax: +886 5 537-0989. E-mail address: [email protected].
Dividends and Subsequent Profitability: An
Examination of a Dual Dividend Stock Market
Chin-Sheng Huang
Department of Finance, National Yunlin University of Science and Technology, Taiwan
Chun-Fan You
Department of Finance, Transworld University, Taiwan
Sam Ting-Hsin Hsu
Department of Finance, National Yunlin University of Science and Technology, Taiwan
Abstract
For decades, studies on dividend signal hypotheses have focused on cash
dividend markets, with a handful of researchers discussing stock dividends. Utilizing
a unique set of data from a dual dividend stock market, this study identifies the
correlation between dividend changes and future profitability. A fundamental
characteristic of dual dividend payouts is that both components, cash dividends and
stock dividends emit separate dividend signals for subsequent profitability. The ratio
of cash to stock dividends may have a similar impact. Therefore, this study employs
a variant of the Bivariate-Ordered Probit model to screen for the dividend signal
sample used in the hypotheses tests. To analyze dividend signal theories, this study
partitions the sample into three sub-samples according to the ratio of cash to stock
dividends. Empirical evidence strongly indicates that dual dividend changes are
positively associated with future profitability in the balanced dividend subsample.
The results of this study are generally robust in terms of accommodating the factors
of stock repurchases, investment growth opportunities, and the business cycles.
JEL classification: G35
Keywords：Dividend, Dividend Change, Dual Dividend, Dividend Signal

Corresponding author: Department of Finance, TransWorld University, Taiwan. Tel: +886 5
533-4463; Fax: +886 5 537-0989. E-mail address: [email protected].
1/36
1. Introduction
Bhattacharya (1979), Miller and Rock (1985), and John and Williams (1985), among
others, are the main originators of dividend signal theories. The basic argument of
these theories is based on information asymmetry between corporate managers and
market investors about the firm’s future profitability. To help investors accurately
evaluating the firm’s fundamental value, corporate managers convey the firm’s
future operating performance, profitability, and cash flow information to the market
through a variety channels. Dividend policy is one of the most effective methods of
conveying this information. However, a necessary condition for this argument is that
the message sent must be reliable and informative. If such is not the case, Spence
(1973) argued that false information is costly to the organization.
Cash dividends are costly signals because the distribution of cash immediately
reduces corporate retained earnings, or even worsens them by creating external debt.
Most managers hesitate to promote dividends, even if current earnings are high, due
to the possibility of future profitability uncertainty. On the contrary, few managers
reduce dividends for the fear of disturbing market prices, even when current
earnings are low. Brav et al. (2005) called this phenomenon dividend policy rigidity.
Therefore, market investors can form rational opinions on the peculiar information
content of dividend increases or decreases.
Dividend data from the Taiwan stock exchange shows that cash dividend
payouts only account for 9.74% of the total market, compared to the dual dividend
payout of 55.21% in 2006. Therefore, research on the dividend signal hypothesis in
the Taiwan stock market is necessary to examine a variety of dividend payout
patterns, and dual dividend payouts in particular.
The stock dividend component of dual dividends is not, technically speaking, a
costly signal, nor does the stock dividend component account for the rigidity of
dividend changes. In fact, the stock dividend only affects the transfer of retained
earnings into common stocks, and is therefore irrelevant to corporate value.
However, Grinblatt et al. (1984) and Rankine and Stice (1997a、1997b) argued that if
companies cannot generate sufficient future earnings growth to recoup retained
earnings, then cash dividend distribution is necessarily restricted.1 Moreover, future
stock splits will lose their attractiveness to market investors. Hence the stock
dividend is still expensive though may be not a highly cost signal. Previous authors
presumed that, in the presence of information asymmetry, the distribution of stock
dividends is a signal of optimism for future profitability. This is particularly true
when stock dividends are distributed from retained earnings.2
In the Taiwan stock market, stock dividends are usually transferred from
1
For the protection of debt holders or bona fide third parties in the US, debt covenants or state
incorporation laws often utilize the retained earnings item in the balance sheet to restrict the
distribution of cash dividends.
2
Crawford et al. (2005) duplicated the empirical method of Rankine and Stice (1997a, 1997b) and
found that adverse evidence for retained earnings hypothesis when adding the relevant missing
variables. However, the authors’ results remain largely consistent with those in the literature for
sample firms issuing 20% or 25% stock dividends and the firms within the states imposing cash
dividend restrictions.
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retained earnings; in contrast, the allocation of stock dividends in America depends
on the size of the dividends. According to American accounting principles (AICPA,
1953, Ch. 7B, par. 10), small stock dividends (less than 20%) must issue new shares
at market prices in addition to the common stocks transferred from retained earnings.
This amendment caused large stock dividends3 (25% with par values) to replace
small stock dividends, which were popular from 1920 to 1930. These new large
stock dividends are issued either by transferring additional paid-in capital,
transferring retained earnings, or by a pure stock split.
In contrast, there are few stock splits in Taiwan because stock dividends can be
issued in par by transferring cumulative capital surplus and/or current after-tax
earnings into common stocks. However, the dual dividends of Taiwan stock listed
firms still share the same essential of total dividends, even though they bear no
resemblance to the cash dividends and stock dividends in US markets. In their
empirical studies on dividend signal hypotheses, Allen and Michaely (2003), Zhou
and Ruland (2006), and Skinner (2008) pointed out the increasingly visible trend of
utilizing total dividends instead of cash dividends4.
Before 1998, stock dividends constituted the primary dividend payout method
in the Taiwan stock market and cash dividends appeared only rarely. Rapid earnings
growth has mitigated the potential problem of earnings dilution caused by stock
dividends in the period. However, the income tax amendment of 1998, which
initiated a new 10% tax on corporate retained earnings, has created a positive
motivation for the optimal distribution of current earnings. First, corporate managers
must determine how much of the earnings to hold for future investment, and then
consider the dividend payout patterns for the remainder in terms of cash dividends,
stock dividends or a mix of both5. Traditional mature firms generally prefer cash
dividends or a mix of large cash dividends with small stock dividends. On the
contrary, high-tech firms with future investment opportunities often choose stock
dividends or a mix of large stock dividends with small cash dividends. After year
2000, the economic growth of Taiwan initiated its decline, investors began their
pursuit of stocks that generate large sums of cash dividend. This has changed the
dividend policy from stock dividend orientation to more cash dividends or a mix of
high cash dividends and stock dividends. The results of this study show more
samples of cash dividend firms and fewer stock dividend firms appearing in the
3
For stock dividends between 20-25%, managers, following standard accounting principles, can
decide to use market prices or par values for the new issues at their discretion. However, most firms
adopt the accounting principles similar to those in large size stock dividends.
4
The practices of implementing stock repurchases to replace dividend distribution have been more
visible in US markets since 1980. In 2004, according to Skinner (2008), the amount of stock
repurchases was larger than that of cash dividends. Skinner further classified dividend payout patterns
into five groups: cash-only dividends, cash dividends and regular stock repurchases, only regular
stock repurchases, only irregular stock repurchases, and no dividends. Among these groups, the
cash-only dividends and regular stock repurchases groups account for 61.6% of total dividends. This
implies that research should use the total dividends, by including stock dividends into cash dividends,
to investigate the dividend signal hypotheses.
5
The highest corporate income tax rate in Taiwan is 25%, while the highest personal income tax rate
is 40%. If a company holds all the current earnings, then the corporate income tax rate will increase to
32.5%. Taiwanese income tax codes allow corporate income tax as an exemption from personal
income tax, and there is no capital gain tax in the market. Therefore, large shareholders with personal
income tax exceeding corporate income tax will select a higher after-tax retained earnings ratio and
reduce cash payout.
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market since 2000.
In summary, dual dividends constitute the primary dividend payout method in
the Taiwan stock market. Consequently, a sample consisting of only cash dividends
cannot provide an adequate picture of market dividend information for investigating
dividend signal hypotheses. However, mixing cash dividends with stock dividends
usually obscures the dividend signals of dual dividends. Grinblatt and Titman (1998)
pointed out that market investors might exhibit heterogeneous responses for
companies with less cash dividends accompanied by more stock dividend payouts.
Moreover, Ghosh, and Woolridge (1988) and Michaely et al. (1995) found out that
the stock dividend sample can mitigate the negative impacts of a decline in, or
termination of, cash dividends. However, most conclusions on the dividend signal
hypotheses in the literature are drawn from cash dividend samples. Therefore, this
study employs a unique set of dual dividends data to reflect the various dividend
payout patterns in the market. This study also adopts a variant of the
Bivariate-Ordered Probit model to screen for the effect of the dividend signal sample
used in dividend signal hypotheses tests. The issue of dividend signals is directed
into a unique context in terms of the positive linkage from the changes of dual
dividends into positive future profitability.
The remainder of the paper is organized as follows. Section 2 surveys literature
on dividend payout theories and dividend signal hypotheses. Section 3 describes the
study data. Section 4 describes the research design and model specifications.
Sections 5 and 6 report the main empirical findings and the relevant robustness tests,
respectively. Finally, Section 7 draws conclusions and provides final remarks.
2. Literature
This literature survey on dividend payout theories and dividend signal hypotheses
first covers cash dividend markets, and then stock dividend markets. Miller and
Modigliani (1961) claimed that in perfect capital markets, dividend policy,
especially cash dividend, is irrelevant to corporate value. However, they observed
that the dividend announcements around markets do indeed affect stock price
changes. They then attributed the relevance of dividend policy to information
asymmetry between corporate insiders and market investors, and showed that
dividend changes are an efficient way for managers to reveal the fundamental values
of the corporation. Bhattacharya (1979) and other researchers further developed
asymmetric information models to delineate the role of costly dividend signals in
providing more transparent fundamental value for equity transactions. Laub (1972)
and other researches empirically supported that dividend changes include
information about future profitability6.
6
Some examples of earlier literature include Pettit (1976), Penman (1983), Brickley (1983) and
Healy and Palepu (1988); for the literature of 1990s, Bajaj and Vijh (1990), Aharony and Dotan
(1994) and Yoon and Starks (1995).
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However, some influential studies clearly indicate that dividend changes are
associated with negative subsequent profitability. Jensen and Johnson (1995), and
Michaely et al. (1995) reported the phenomenon of increasing subsequent future
earnings when companies stop paying cash dividends. DeAngelo, DeAngelo, and
Skinner (1996) found similar results using a sample of corporations with at least
nine years of consecutive earnings growth that ended in shrinking: two thirds of the
companies switched from the original earnings growth into the stage of zero growth
in years when dividends increased. Benartzi et al. (1997) discovered that dividend
changes are only significantly associated with previous earning changes, and lack
significant connections with future earning changes. Finally, in Japanese markets,
Fukuda (2000) obtained similar conclusions and attributed the adverse evidence of
dividend signal hypothesis to the over-reactions of corporate managers regarding the
firm’s future prospects.
Contrary to the evidence above, Nissim and Ziv (2001) argued that both
measurement errors and model misspecifications might account for adverse effects
of dividend signal hypotheses. Firstly, they observed that most studies falsely use the
previous market value of equity, which can reflect future earnings too early, as a
deflator of subsequent earning changes, and instead employ the previous book value
of common stocks in their empirical analysis. Secondly, as reported in the literature
they defined return on equity (ROE) as a key predicator for earning changes. In
particular, the mean reversion of ROE implies decreased future earnings when the
current ROE level is higher than its long-term average, and vice versa. Moreover,
Nissim and Ziv (2001) assumed that current earnings follow the data generating
mechanism of first order autocorrelation. Accordingly, they specified current ROE as
a proxy for omitted correlated variables for future profitability and found robust
evidence for the dividend signal hypotheses regardless of the dependent variable of
future earning changes, future earnings, or future abnormal earnings.
Following similar logic, Harada and Nguyen (2005) presented another
argument that the diversity of motivations adopted by managers in dividend
adjustments makes the actual dividend changes data easily fall into adverse dividend
signal hypotheses. Therefore, they believed that expected dividend increases are
only informative when corroborative with current profit increases and brighter
financial measures; otherwise, they might only represent managers’ optimisms
regarding future prospects. Accordingly, Harada and Nguyen (2005) employed the
Logit Model to screen the sample of firms with consistent prospects, and discovered
the validity of dividend signal hypotheses in terms of expected dividend change
models.
This literature survey next turns to the issue of dividend signal content
regarding stock dividends. For the stock dividend practices in American stock
markets, Rankine and Stice (1997b) indicated that the sources of stock dividends,
taking the example of 2-for-1 distribution, consist of pure stock split, additional
paid-in capital, retained earnings, and a mix of additional paid-in capital and retained
earnings. These dividends account for 23.15%, 54.60%, 15.73%, and 6.52% of the
total, respectively. However, Huang et al. (2009) pointed out that the stock dividends
of dual dividend payouts in Taiwan stock markets are always distributed via addition
paid-in capital, retained earnings, and a mix of additional paid-in capital and retained
earnings. These types of dividends account for 3.25%, 71.67%, and 25.08% of the
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total, respectively. The salient discrepancy is the retained earnings source for stock
dividends only accounts for 22.25% in US markets, but reaches 96.75% in Taiwan7.
The main point of this study hinges on the proposal for linking dual dividend
changes and subsequent profitability. The common free cash flow hypothesis and
retained earnings hypothesis can be employed in either cash dividend payout or
stock dividend payout samples. However, the literature development is still in the
infancy for the dual dividend payout markets. Huang et al. (2009) illustrated that a
dual dividend payout firm adopting a balanced dividend payout ratio is significantly
associated with positive subsequent profitability 8 . Fundamentally, a firm is a
going-concern profit-motivated organization that must maintain an optimal cash
level for both current operations and future capital expenditures. Therefore, the
over-distribution of cash dividends might cause a shortage of funds; on the contrary,
too much stock dividend payout aggravates the agency problem, and may cause the
firm to fall victim to acquisition by market competitors (Amit et al., 1989; Smith and
Kim, 1994; Guo et al., 1995). Moreover, companies experiencing either slow growth
or high stock dividend payouts must face strict market pressures from investor
clienteles demanding higher cash dividends, particularly from aged investors and
annuity fund managers (Baker and Wurgler, 2004; Graham and Kumar, 2006; Eun
and Huang, 2007).
Finally, some caveats on the dividend signal hypotheses in the literature deserve
special attention. Firstly, Grullon et al. (2005) re-examined the results of Nissim and
Ziv (2001) using thirty-five years of cross-sectional data, and found that only 29% of
the sample years supported the dividend signal hypothesis for the following years
after dividend payouts. Therefore, this study employs cross-sectional data to
supplement the main pooled cross-sectional data, and examines the association
between dividend changes and subsequent profitability. Secondly, Grullon and
Michaely (2004) indicated that dividend changes did not suggest positive future
profitability based on a sample of stock repurchases. Therefore, the current study
investigates the dividend signal hypothesis by excluding the stock repurchases
sample as a sensitivity check for the main results.
3. Data description
The study uses data from the Taiwan Economic Journal (TEJ) that includes variables
of dividends, financial statements, equity prices, corporate governance, and stock
repurchases. The basic data was gathered annually, with the exception of the profit
data, which was reported from annual first quarters. The lengths of data periods in
previous studies vary greatly. Studies on American markets generally adopt longer
study horizons. For example, Nissim and Ziv (20001) researched the period of
1963-1998, while Grullon et al. (2005) covered a thirty-five year period. In contrast,
7
One caveat is that this study draws on a sample of stock dividends from additional paid-in capital.
This might affect the empirical results regarding the association between dual dividends and future
profitability. Therefore, this study executes the robustness test based on this concern in section 5.4.
8
The authors presume that the managers adopt balanced dividends based on two considerations.
Firstly, distributing optimal cash dividends convey positive signals of self-discipline and solvent
financial prospects. Secondly, adopting optimal stock dividends might indicate optimism about future
profitability. The authors find, through trial-and-error, that ratios of cash dividends to stock dividends
for dual dividend sample ranging between 1 and 2.33 can generate a positive association between
dual dividends and future profitability.
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related studies in Japanese markets typically involve shorter horizons. Kato et al.
(2002) and Harada and Nguyen (2005) used ten-year data, for instance. Due to the
lack of cash dividend data before 1997, the current study sets up the ten-year
research horizon of 1997-2006. However, the necessary empirical data should
include future profits, future returns, and some lagged variables. As a result the
processing data actually covers a 14-year period, from 1995-2008. This study applies
the following sample selection criteria.
1. The sample is consisted of firms listed on the Taiwan Stock Exchange.
2. This study excludes samples of preferred stocks, TDR, or firms with incomplete
financial data.
3. This study excludes firms in the financial sectors as financial firms have
different financial structures than non-financial firms.
4. The sample firms used to test the dividend signal hypotheses must generate
dividends in two consecutive years. The research sample was divided into three
sub-samples according to dividend payout patterns: cash dividends, stock
dividends, and dual dividends. Finally, the sample of dividend changes was
partitioned into three sub-samples: dividend increase, dividend decrease, and
dividend constant.
Table 1 presents the sample distribution of firms with two consecutive years of
dividend payout patterns following the above sample selection criterions. The total
sample includes 5165 firms. Of this total, there are 440 firms with cash dividends,
648 with stock dividends, and 1515 with dual dividends. The remaining firms belong
to the categories of no dividends and other dividends. In 1997, the total sample firms
reached 310, where firms with cash dividends and dual dividends accounted for 3
and 32, respectively. In 2006, however, the whole sample doubled to 646, and both
cash dividend and dual dividend samples increased to 110 and 242, respectively.
However, the stock dividend sample significantly decreased from 181 in 1997 to
only 6 in 2006. In general, the dual dividend sample exhibits a steady increase from
the first year of the research up to 2005, while the cash dividend sample surges in
2002, followed by a steady growth trend thereafter.
<insert Table 1 here>
Next, this study examines the sample distribution of firms with two consecutive
years of dividend payout patterns in terms of market payout weights. As Table 2
illustrates, the market dividend payout weights of cash dividends, stock dividends,
and dual dividends in 1997 respectively accounted for 0.18%, 59.45%, and 26.33%
of the total. However, these ratios changed to 9.74%, 0.27%, and 55.21% in 2006.
Similar to Table 1, the payout weight of stock dividends significantly decreased
during the period, while the proportions of cash dividends and dual dividends soared.
After partitioning dual dividends into cash components and stock components, these
figures exhibit the phenomenon of increasing cash components versus decreasing
stock components. However, there is a surprising twist from 2005-2006: the
dividend payout ratio of the other dividend category increased from 12.11% to
29.10% while the ratio for dual dividends decreased from 73.975% to 55.21%. A
7/36
closer inspection of the other dividends firms in 2006 reveals that the switch of dual
dividends into cash dividends and the newly increasing cash dividends accounted for
24.35% of the entire market. Compatible with the trend of the changes in dividend
payout patterns above, the market weight of cash dividends reached 31.00% in the
extrapolative year of 2007, and the total sample firms increased to 148.
<insert Table 2 here>
DeAngelo et al. (2004) reported the phenomenon that large companies in
American markets are the primary distributors of cash dividends. In contrast, only
five of the top 20 in Taiwan firms paid out cash dividends in 2007; the other 15 firms
employed a dual dividend policy. The dividend payout patterns in Taiwan apparently
bear little resemblance to those in American markets. However, even the grand
blue-chip stocks in Taiwan classified as dual dividend payout firms generated huge
cash dividend components compared to their stock dividend components. Taiwan
Semiconducting Company, the highest dividend payout firm in the Taiwan stock
market, is a notable example. This company distributed a cash dividend component
of up to US$ 2.37 billion, but only US$0.02 billion for the stock dividend
component. A similar phenomenon appears in the other 14 top dual dividend payouts
companies. Moreover, cash dividends from the top 20 firms account for 54.10% of
all cash dividend payouts in the market. In short, with regard to the real content of
dividend payouts in Taiwan, the concentration of cash dividends in large companies
mimics the behaviors observed in American markets.
Next, this study examines the details in the sample of dividend changes. In the
cash dividends category, firms with increasing, decreasing, and constant dividends
respectively account for 222, 134, and 84 firms. In contrast, Table 1 of Nissim and
Ziv (2001) shows that the samples of corporate accounting years with dividend
constants reached 19004 from 1963-1997, with the next category being the dividend
increase sample at 12105, and finally the dividend decrease sample at 697. A similar
pattern appears in Table 1 of Harada and Nguyen (2006), indicating that the samples
of firms with constant, increasing, and decreasing dividends respectively account for
6564, 4002, and 3142 firms. These figures indicate that the sample of firms with
constant dividends is the primary pattern in both American markets and Japanese
markets, while increasing dividends accounts for the most firms in Taiwanese
markets. However, after adding the cash dividend and dual dividend samples, the
number of firms with constant, increasing, and decreasing dividends in Taiwan
becomes 758, 627, and 570, respectively. The relative size of dividend changes in
the Taiwanese market agrees with the results reported in the literature.
The previous figures of dividend changes indicate that the dividend policy is
most rigid in American markets, followed by Japanese markets, and finally
Taiwanese markets. Even through several business cycles from 1963-1997,
American markets exhibit a huge size constant dividend sample compared to the
decreasing dividend sample: the former is 27.27 times the size of the latter. The
number of firms with constant dividends in Japanese markets and Taiwanese markets
is much smaller. The following rationales may be ascribed to this dichotomy. Firstly,
American markets distribute dividend payouts on a quarterly basis, and the corporate
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profitability apparently exhibits less volatility on a quarterly frequency. Therefore,
firms tend to maintain constant dividends unless there are strong signs indicating
future profitability changes. Secondly, American companies strive for global
diversification, and are therefore less susceptible to the impacts of regional business
cycles than firms in Japan or Taiwan are. This may partially explain the more stable
dividend payouts in American firms compared to those in Japan or Taiwan. Thirdly,
as Zeff (1982) pointed out, the statutes of accounting principles have discouraged the
practice of stock dividend payouts since 1953. Due to an insufficient stock dividend
buffer, the practice of cash dividends changes diminished thereafter. On the contrary,
according to Kato and Tsay (2002), unpaid stock dividends were popular in Japanese
markets from the end of the war to the economic recession of the 1990s. Stock
dividends also played a major role in Taiwanese markets until the year 2000.
Based on the observations above, the practice of dividend payouts in American
markets might long data-horizon research better suited to examining the association
between dividend changes with subsequent profitability. However, merging quarterly
dividend data into annual data to match annual financial data has drawbacks. First,
merging data might obscure the seasonal patterns of dividend changes, and therefore
weaken the association between dividend policy information and future profitability.
On the contrary, the dividend payout practices in Taiwan are generally on annual
basis, and may help reveal the association between dividend changes and subsequent
profitability.
<insert Table 3 here>
4. Research Design
Finance literature contains two common methodologies for dividend signal
research. The first method is event study, which is typically used to evaluate the
short-run stock market reactions of dividend announcements. Examples of this
approach include, among others, Pettit (1972), Charest (1978), Aharony and Swary
(1980), Michaely et al. (1995), Fukuda (2000), and Lee and Yan (2003). The other
method involves using multiple regressions to examine the association between
future profitability and dividend changes; Nissim and Ziv (2001), Harada and
Nguyen (2005), and Grullon et al. (2005) adopt this approach. Using the former
method, financial academics generally agree that market reactions follow the
directions of dividend changes. However, there still controversies surrounding the
latter method. Therefore, this study presents a novel three-stage approach to revisit
the issue of dividend signal hypothesis.
4.1. Model of actual dividend changes
A quick way to estimate the association between future profitability and
dividend change is to employ dividend changes as the explanatory variable, and then
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observe the signs of the estimated coefficients. Nevertheless, a more elaborate model
is necessary if investors prefer to look at how dividend increases or decreases
individually affect future profitability. Harada and Nguyen (2005) used dummy
variables to represent the observations of dividend increases and dividend decreases
separately in two estimators. Nissim and Ziv (2001) combined these two variables
into one estimator. For parsimony, this study adopts the latter method and establishes
the association of future profitability with dividend changes as follows.
ROACHGt 1   0  1 DIVUPt   2 DIVDNt   3 ROAt   4 ROAt 1   t 1
(1)
Where ROACHGt+1 represents the ROA changes in the next period；DIVUPt
(DIVDNt) is the dummy for dividend increase(decrease), in the case of dividend
increase (decrease), DIVUPt (DIVDNt) =1; otherwise, DIVUPt (DIVDNt) =0；ROAt
and ROAt-1 respectively represent the asset return for the current and previous
periods, and are calculated by the earnings before interest and tax divided by total
asset；εt+1 represents the disturbance term. In general, DIVUPt (DIVDNt) should have
a positive (negative) association with ROACHGt+1.
Equation (1) must consider the data generating process of the ROAt+1 change.
Therefore, this equation incorporates a dynamic time series model generated by the
first order auto-regression,9 which fits well in the data, along with the proxy for
ROAt change,10 to mitigate the possible bias due to corporate earnings management
behavior and other omitted correlated variables.
In addition to the ROA in Eq. (1), the literature commonly uses equity return
(ROE), earning per share (EPS), and continuing earnings per share (Cont_EPS) to
measure future profitability. ROE is defined by the earnings before interest and tax
divided by stockholders’ equity, and Conti_EPS represents the manager’s expected
normal EPS. However, this study ultimately adopts ROACHGt+1 as the measure of
future profitability due to the following considerations. Firstly, ROA is more robust
to the changes of capital structure than other measures, such as EPS, CEPS, and
ROE. Secondly, ROA is mostly unaffected by the before tax non-recurring items as
well as non-cyclic items. Thirdly, managers are used to manipulating earning
managements for window dressing on operating performance. Fourthly, Barber and
Lyon (1996) pointed out that under most circumstances, ROA is the most efficient
measure for measuring future operating performance. Finally, for empirical
considerations, this study examines the explanatory power of the ROA change and
9
This study employs ARMA model estimation to find the appropriate data generating process of
ROACHGt+1 as AR (1).
10
This study employs Q statistics to examine the residual of ROACHGt+1 . Empirical evidence shows
that the past 36 periods exhibit white noise and then form a dynamic model. Meanwhile, this study
decomposes the ROACHGt into ROAt and ROAt-1 in Eq. (1) for better model fitness.
10/36
ROA growth rate in early working stages. Results indicate that the former is superior
to the latter.
4.2. Screening method on dividend signal sample
Harada and Nguyen (2005) recently proposed a Logit Model that is able to both
reflect corporate financial status and capture potential dividend changes. The present
study extends Harada and Nguyen’s (2005) approach. Firstly, this study implements
a three-dimension Ordered Probit Model instead of the two-dimension Logit Model
to capture the information hidden in dividend constant firms, which account for the
majority of dual dividend payouts. Firms with constant dividends might simply be
firms with increasing or decreasing dividends, but whose corporate managers are
ignorant of future prospects. In the two-dimension Logit Model, similar situations
can occur in firms with dividend increases or decreases. Secondly, this study
estimates the effects of the changes on cash dividends, stock dividends, and dual
dividends using three separate models. The first Ordered Logit model of cash
dividend changes is specified as follows.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 SalesGR
t
  6 M At   7 Ln ( MV t )   t
(2)
Where DIVCHGt represents the cash dividend changes at time t. This term is
specified respectively as 0,1, and 2 for the cases of decreasing dividends, constant
dividends, and increasing dividends; DIVEQTYt-1 represents the dividend payout
ratios at time t-1(total dividends/book value of stockholder equity); ROAte represents
the manager’s expected ROA at time t, and is defined by the proxy of ROA in the
first quarter at time t+111; Ln(REt) is the natural log of the retained earnings at time t;
SalesGRt is the sale growth rate at time t; M/At is the proxy for investment growth
opportunity at time t, and is calculated as the sum of the book value of debts and
market value of stockholder equity divided by the book value of total assets (Fama
and French, 2002; Zhou and Ruland, 2006)；Ln(MVt) is the natural log of the market
value at time t; and εt represents the disturbance term.
The stock dividend change specified by the second Ordered Probit Model is as
follows.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 AGR t   6 Beta t   7 Ln ( At )   t
(3)
Where Divchgt represents the stock dividend changes at time t. For the explanatory
variables, AGRt is the growth rate of total asset at time t; Betat stands for the
11
Most dividend announcements in Taiwan are made after the first quarter of the subsequent year.
This phenomenon justifies the specification of Eq. (1) because corporate insiders possess information
about company earnings in the first quarter of the next year.
11/36
systematic risk of individual stocks; Ln(At) is the natural log of total asset at time t;
and the other variables are the same as those in Eq. (2).
Since dual dividend changes consists of both the cash dividend changes
component and the stock dividend changes component, the specification of Eq. (2)
or Eq. (3) alone assumes that any missing information is embedded in the dual
dividend payout sample. This study further employs a Bivariate-Ordered Probit
Model to capture the effects of cash dividend changes and stock dividend changes as
follows12.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 SalesGR
t
  6 M At   7 Ln ( MV t )   t
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 AGR t   6 Beta t   7 Ln ( At )   t
(4)
These variables are defined as those in Eq. (2) and Eq. (3).
The estimated parameters of Eq. (2) through (4) and the expected dividend
change thresholds are used to compute the probabilities of decreasing dividends,
constant dividends, and increasing dividends for the individual firms, according to
Eq. (5).
Pr( yt  0 xt ,  ,  )  F ( 1  xt  )
Pr( y t  1 xt ,  ,  )  F ( 2  xt  )  F ( 1  xt  )
Pr( yt  2 xt ,  ,  )  1  F ( 2  xt  )
(5)
Where the terms γ1 and γ2 represent the expected dividend change thresholds, and F
(‧) is the cumulative distribution of the disturbance term. The dual dividend sample
is classified into three types (expected dividend increase, expected dividend decrease,
and expected dividend constant) according to the expected cash dividend changes
and the expected stock dividend changes calculated above.
Finally, this study considers the empirical implications of the dividend payout
practices in Taiwan. Specifically, corporate managers prefer the rigidity of cash
dividend payouts and the trend of upturn instead of downturn in stock dividend
payouts. Accordingly, the probabilities of cash dividend increase, cash dividend
decrease, and stock dividend decrease are adjusted upwards. Ultimately, the process
of dividing the dividend changes sample into three distinct categories is as follows:
Expected Dividend Decrease
Expected Dividend Constant
γ1
Expected Dividend Increase
γ2
12
For estimation efficiency, this study employs a two-dimensional Bivariate-Ordered Probit Model
to screen the sample of dual dividend firms. For details on the Bivariate-Ordered Probit Model, refer
to Yamamoto and Shankar (2004) and Zayeri and Kazemnejad (2006).
12/36
4.3. Model of Expected Dividend Changes
In the final step, this study replaces the model of dividend changes with the model of
expected dividend changes to screen for the effective dividend signal sample. The
expected dividend change model presumably provides more informative content of
subsequent profitability than the dividend change model. The model of expected
dividend changes is specified as follows.
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt   3 ROAt   4 ROAt 1   t 1 (6)
Where EXPDIVUP(EXPDIVDN) is a dummy variable that takes the value of 1 in the
case of expected dividend increase (decrease); otherwise 0; the other variables are
defined as in Eq. (1).
4.4. Description of research variables
This study next explores the effect of the explanatory variables in Eq. (2) and
Eq. (3) on the associations with dividend changes and hypothesizes the theoretical
expectations.
According to investment intuition, the first factor might influence the dividend
changes would be the previous dividend levels. However, after screening for the
dividend signal sample using Eq. (2) to (5), this study employs DIVEQTYt-1 instead
of dividend levels since the latter shows no explanatory power on future earnings.
The adoption of DIVEQTYt-1 can be attributed to Miller and Modigliani (1961).
These authors argued that, in the presence of target payout ratios and an
unwillingness to cut dividends, investors are much more likely to interpret a change
in dividends as a change in managements’ view of the future prospects of the firm.
Harada and Nguyen (2005) conjectured a negative association of DIVEQTYt-1 with
future earnings. The following rationales support this negative association. Firstly,
the lower dividend payout ratio is, the more room for dividend increase will be and
the less the pressure for subsequent profitability. Secondly, lower dividend payout
ratios, according to conventional wisdom, represent higher investment opportunities
and better prospects.
Next, this study postulates that past profitability has a major affect on dividend
changes. Brav et al. (2005) argued that managers try hard to maintain a fixed
dividend policy until corporate earnings have significantly changed for several
consecutive years. Fukuda (2000) provided similar results, indicating that dividend
increases usually accompany increases in current and past earnings, and particularly
for current earnings. On the contrary, negative current and past earnings often appear
before dividend decreases. Therefore, this study employs changes in asset return,
ROACHGt , as a proxy for current and past earnings. This approach captures the
positive association between ROACHGt and dividend changes.
The dividend decisions that mangers make depend primarily on the prospects of
corporate future profitability (Lintner, 1956). On the timing of dividend
announcements, most companies release current dividends in the second quarter.
Consequently, first quarter earnings are related to the content of expected dividends.
Therefore, this study adopts the total asset return of the first quarter in the
13/36
subsequent period, ROAte , as a proxy for future profitability and anticipates a
positive association between ROAte and dividend changes.
For institutional consideration, corporate dividend changes exhibit a close
relationship with retained earnings (Ln(REt)). In the US, for the protection of
bondholders and other claimers, bond contracts and state legislation usually imposes
restrictions on the retained earnings distributed in cash dividends. Similarly,
corporate laws in Taiwan prohibit companies with negative retained earnings from
distributing cash dividends. However, companies with high-retained earnings
generally possess high free cash flows, and readily fall to the acquisitions of
competitors. Therefore, managers often use high dividend payouts as an
entrenchment tool to prevent potential threats from the competition (Amit et al.,
1989; Smith and Kim, 1994; Guo et al., 1995). Following the argument above,
companies with higher retained earnings tend to issue more cash dividends.
Next, sales growth (SalesGRt), which acts as a proxy for corporate operating
performance may exert a significant influence on current profitability, and therefore
influence corporate dividend changes. In particular, sales growth remains the major
factor affecting the real profitability of Taiwanese firms. This study postulates a
positive association of the sale growth with dividend changes.
Investment growth opportunity (M/At) generally reflects corporate future
profitability, and hence affects dividend policy. Most market investors do not foresee
high future profitability and high cash dividends in a company with low investment
growth. When market expectation is consistent with corporate profitability prospects,
then dividend changes can be associated with investor forecasts. Therefore, this
study predicts a positive relationship between investment growth opportunity and
corporate dividend changes.
The size of a firm may be a determining factor for dividend changes, and has
little to do with the profitability. Since large firms usually have more retained
earnings, their current earnings have a lesser impact on dividend policy. In addition,
the managers of large firm usually believe that a stable dividend policy will benefit
the corporate stock prices in the markets. In contrast, the managers of small firms
tend to adjust dividend payouts more often due the insufficiency of accumulated
retained earnings. This study employs the market value (Ln(MVt)) and total
asset(Ln(At)) as explanatory variables for cash dividend changes and stock dividend
changes, and postulates a negative relationship between firm size and dividend
changes.
Besides financing through equity and debt, the growth of profitability is a major
factor in sustaining total asset growth (AGRt). In general, high profitability growth
implies a high level of positive cash flow for the firm. Therefore, this study
hypothesizes a positive association between total asset growth and dividend changes.
In addition to the performance factors above, market risk is the final factor
influencing dividend policy. This study employs the systematic risk Betat to
represent the associated market risk that firms face. A high Betat implies that firms’
performance may be more vulnerable to the external economy, and the ties between
14/36
customers and the firms’ products and services are loose. Accordingly, managers
attempt to avoid distribute dividends when there is high uncertainty in future
markets. Therefore, this study conjectures a negative relationship between market
risk and dividend changes.
Finally, this study explores the potential multicollinearity among explanatory
variables in the regression analysis above in terms of the covariance matrix reported
in Table 4. Panel A in Table 4 shows that all the coefficients of correlation in the
cash dividend sample are well below 0.7, except for the retained earnings and
market value, with a coefficient of 0.7903. For the stock dividend sample, reported
in Panel B of Table 4, the coefficients of correlation are all smaller than 0.6. In
addition, the diagnostics of the regression analysis indicate that the average VIF
coefficients are well below 2.52 for both samples. Accordingly, this study ignores
the potential multicollinearity problem when estimates Eq. (2),(3), and (4).
<Table 4 is inserted here>
5. Empirical results and analysis
This study investigates the dividend signal hypothesis using a unique pooled
cross-sectional dataset supplemented with cross-sectional data. This study compares
empirical evidence with the results of Nissim and Ziv (2000) and Narada and
Nguyen (2005) to determine the commonalities and unique factors in different
markets.
5.1. Model of Actual Dividend Changes
Conventional wisdom hypothesizes that dividend changes are positively
associated with subsequent profitability. The empirical results in Model 1 of Table 5
show that, in the absence of control variables (ROAt and ROAt-1), the postulated
association only holds for the dual stock dividend sample at the 1% significance
level. In contrast, adding the control variables in the Model 2 of Table 5 shows that,
except for the stock dividend sample, there is a significantly positive association in
both cash dividend and dual dividend samples. These findings agree with those of
Nissim and Ziv (2001, P2119), who stated that dividend changes are followed by a
significant positive future profitability. However, this conclusion comes with the
caveat that instead of using dividend changes, Nissim and Ziv employed the rate of
change in dividend per share in their analysis.
<insert Table 5 here>
Next, to clarify the linkage between the direction of dividend changes and
15/36
future profitability, this study employs the dummies of dividend increase and
dividend decrease to replace the dividend changes in the regression analysis above.
Model 1 of Table 6 shows that in the absence of the control variables, the dividend
dummy is the only significant explanatory variable in the cash dividend and dual
dividend samples. Similar to the results of Table 5, after adding the control variables,
all the explanatory variables, except the dividend decrease dummy in the cash
dividend sample, exhibit the hypothesized associations. Moreover, the dividend
increase dummy in both cash dividend and dual dividend samples indicates a
significantly positive association with subsequent profitability. The evidence in Table
6 agrees with Nissim and Ziv (2001, P2119) and Harada and Nguyen (2005, P512),
indicating that dividend increase is often followed by positive future profitability.
However, the association between dividend decrease and future profitability still
lacks statistical support.
<insert Table 6 here>
5.2. Screening for dividend signal samples
To explore the evidence supporting the hypothesis made by the decreasing
dividend sample, this study employs the Ordered Probit Model to screen for the
dividend signal samples. The empirical results of the Ordered Probit Model of
expected dividend changes are as follows. Firstly, Model 1 in Table 7 shows that all
explanatory variables display a significant influence on the expected dividend
changes in the context of the cash dividend sample. Secondly, in the stock dividend
model, all explanatory variables except Betat are significantly associated with
expected dividend changes. Finally, in the Bivariate-Ordered-Probit model for the
dual dividend sample, there is a dichotomy between cash dividends and stock
dividends: all explanatory variables are significant in the former, whereas retained
earnings (Ln(REt)) and total assets (Ln(At)) do not show any significant influence
upon expected dividend changes in the latter. Moreover, the signs of all estimated
coefficients agree with the hypothesized associations across all dividend payout
e
patterns. These empirical results imply that higher ROAchgt, ROAt , Ln(REt),
SalesGRt, M/At, and AGRt; and lower Diveqtyt-1, Ln (MVt), Betat, and Ln(A t ) create
a higher tendency for dividend increase announcements. The opposite is true for
dividend decrease announcements.
Finally, this study uses the sample of cash dividend to provide details on the
procedure of transforming dividend changes into the version of expected dividend
16/36
changes. Before this procedure, the samples of dividend increase, constant, and
decrease included 222, 84, and 134 firms, respectively. After the estimation on Eq.
(2), two threshold values were incorporated into Eq. (5) to calculate the probabilities
of three dividend changes for each sample firm. Moreover, by considering the
rigidity of dividend policy in the related literature, this study adopts a trail-and-error
approach to adjust the probabilities for both dividend increase and dividend decrease
until the best-expected profitability is reached. This adjusting process eventually
results in the three sub-samples of expected increasing dividend, constant dividend,
and decreasing dividend, with 154, 224, and 62 firms, respectively.
<insert Table 7 here>
5.3. Models of Expected Dividend Changes
This study further tests the dividend signal hypothesis by examining the
information content of the expected dividend change sample instead of the actual
dividend change data on future profitability. Table 8 reports the empirical results for
both actual dividend changes (illustrated by Model 1) and expected dividend
changes (illustrated by Model 2). The evidence strongly indicates that the expected
dividend change model creates a more significant linkage between dividend changes
and future profitability across three dividend payout patterns. Model 2 exhibits
superior model fitness than Model 1 in terms of R2 and F statistics. Ultimately, the
empirical evidence reveals expected dividend changes, which strongly suggest a
significant association between expected dividend changes and subsequent
profitability, particularly for the dual dividend sample13.
<insert Table 8 here>
5.4. An Examination of Balanced Dividend Hypothesis
This study further analyzes why the dividend signal hypothesis gains firm
support in the dual dividend sample in terms of the balanced dividend hypothesis.
Following Huang et al. (2009), this study decomposes the dual dividend sample into
three sub-samples (low cash/stock dividend ratio, balanced dividend ratio, and high
cash/stock dividend ratio) based on the proportions of cash dividends to stock
13
Interestingly, this study conducts an analysis using return data instead of ROA in Eq. (6). The
empirical results show that there exists strong association between expected dividend change and
future return in the dual dividend-paying sample. For saving space, these results are available upon
request.
17/36
dividends. Table 9 indicates that the expected dividend model in the sample of
balanced dividends strongly suggests the dummy variables of expected dividend
increase and decrease are significantly associated the subsequent ROA changes.
Moreover, the balanced sample exhibits superior model fitness in terms of R2 and F
value compared to those in the other two sub-samples. This evidence remains largely
unchanged after excluding data for firms with stock dividends accrued from paid-in
capitals.
<insert Table 9 here>
5.5. Evidence on annual cross-sectional data
The empirical evidence on the association between dividend changes and future
profitability above was drawn from the pooled cross-sectional data. However, the
issue of the stability of the association in cross-sectional annual data might be a
concern for market practitioners. This study addresses this concern by re-examining
the dividend signal hypothesis using cross-sectional data. The empirical data are
only available for the samples of cash dividends and dual dividends during the
period 2001-2006 because, prior to 2001, the practice of cash dividends was
relatively rare in Taiwan, as were stock dividends after 2003. The empirical results
of the case of dividend increase in the cash dividend sample, as Panel A of Table 10
indicates, show that the proportion of years with significant association for dividend
change model (Model 1) and expected dividend change model (Model 2) reach
16.67% and 66.67%, respectively, while the figures decline to zero and 33.33% in
the case of dividend decrease. Moreover, the linkage between dividend changes and
subsequent profitability is rather strong in the dual dividend sample, with at least
66.67% significant years uniformly across both cases of dividend increase and
dividend decrease. Ultimately, the empirical evidence drawn on the proportion of the
significant association predicted by our expected dividend change model in the case
of dividend increase is far larger than the 29% found in Grullon et al. (2005,
Page1665-1666).
<insert Table 10 here>
6. Robustness Tests
This section presents, reports the results of robustness tests to investigate
the sensitivity of the empirical results above in terms of the following eight
18/36
potential factors that might exert an influence on the nature of dividend signal
hypothesis14.
6.1. Alternative measures of future profitability
Finance literature commonly uses equity return, earnings per share, and
continuing earnings per share to measure future profitability. This study adopts
the criterion of the model fitness in terms of R2 among the dividend signal
hypothesis tests and finds out the ROA serves best.
6.2. Excluding irregular dividend sample
When companies incur deficits and then distribute dividend payouts using
non-surplus items, the sample of dividend changes may be less informative
regarding the content of dividend signals. However, a normal company would
not pay out more than its current surplus. After empirically retesting the
dividend signal hypothesis using data that excludes companies incurring a
negative current surplus or a dividend payout ratio larger than 1, the main
findings of this study remain largely unchanged.
6.3. Alternative estimation procedures
This study employs the generalized least-squares estimator (GLS) to adjust for
the non-spherical disturbances on heterogeneity and autocorrelation of
covariance matrices that frequently appear in pooled cross-sectional data.
Moreover, this study applies the Fama and MacBeth (1973) procedure for cross
validation. The evidence from this procedure largely supports the main findings
of the GLS method.
6.4. Effect of stock repurchases
To clearly delineate the linkage between dividend changes and future
profitability, this study re-tests the dividend signal hypothesis using a database
that exclude companies that carry out stock repurchases. The main findings
from this new data largely agree with those from the original data.
14
For the sake of brevity, this section only reports the main results of the related robustness tests.
Details are available from the authors upon request.
19/36
6.5. Investment growth opportunities
Miller and Modigliani’s (1961) dividend irrelevance argument asserts that
corporate value is determined by investment opportunities, and is therefore
irrelevant to dividend policy. Conventional wisdom indicates that the higher
retained earnings lead to higher investment opportunities for firms.
Consequently, an increasing dividend may hinder the accumulation of retained
earnings. Gordon’s (1962) fixed dividend growth model holds a similar view,
stating that under the assumption of fixed expected return, a high dividend
payout entails low future growth. Therefore, this study uses Eq. (7) and (8) to
examine whether investment opportunities are more relevant to future
profitability and weaken the linkage between dividend changes and future
profitability.
ROACHGt 1   0  1 DIVUPt   2 DIVDNt
  3 M / At   4 ROAt   5 ROAt 1   t 1
(7)
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt
  3 M / At   4 ROAt   5 ROAt 1   t 1
(8)
Where M/At represents investment growth opportunities ((book value of debt +
market value of equity)/(book value of total asset)), and other variables are defined
as those in Eq. (1) and (6). The empirical results from Eq. (7) and (8) are similar to
those in previous sections, indicating that investment growth opportunities are
irrelevant to the linkage between dividend changes and future profitability.
6.6. Effect of business cycles
Changes in economic growth might affect the corporate dividend policy,
particularly for the emerging Taiwan stock market. Specifically, if the subsequent
economic growth rate continuously increases, ceteris paribus, the company might be
more optimistic about future profitability, and distribute more dividends. To identify
the influence of business cycles, this study employs the GDP growth rate as a proxy
for business cycles (see Bekaert et al., 2006; Furceri and Karras, 2007) and examines
the association between dividend changes and future profitability in the following
regressions.
20/36
ROACH t 1   0  1 DIVUPt   2 DIVDN t
(9)
  3GDPGRt   4 ROAt   5 ROAt 1   t 1
ROACH t 1   0  1 EXPDIVUPt   2 EXPDIVDN t
(10)
  3GDPGRt   4 ROAt   5 ROAt 1   t 1
Where GDPGRt represents the domestic gross product growth rate, and other
variables are defined as those in Eq. (1) and (6). Empirical results show that the
main findings remain largely unchanged in the context of business cycles. This study
adds investment growth opportunity to Eq. (9) and (10), and empirical results
indicate that the main results regarding the association between dividend changes
and future profitability are generally robust to controlling both internal and external
growth factors.
6.7. Year effect
This study uses pooled cross-sectional data for regression analysis. However, to
address concerns about the stability of the empirical results across different years and
investigate the possible year effect on the empirical results, this study employs the
year dummy variable into Eq. (1) and (6). Results show that the main explanatory
variables exhibit the same results as before. Moreover, the year dummy variables are
all insignificant, revealing no year effects in the empirical data.
6.8. Industry effect
The industry effect is the final variable to be checked on in the association
between dividend changes and future profitability. This study considers the industry
classification, and specifies the relevant empirical models as follows:
ROACHGt 1   0  1 DIVUPt   2 DIVDNt
n
  3 ROAt   4 ROAt 1   i INDi   t 1
(11)
i
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt
n
  3 ROAt   4 ROAt 1   i INDi   t 1
(12)
i
Where INDi is an industry dummy, defined as INDi=1 when sample firm belongs to
the i-industry, and INDi=0 otherwise. This study adopts the industry classification of
21/36
the Taiwan Stock Exchange Corporation. Empirical results indicate that the main
conclusions remain largely unchanged. Further, the industry dummies are all
insignificant, ruling out the possible industry effect in the association between
dividend changes and future profitability.
7. Conclusions and Remarks
This study investigates a unique dual dividend dataset to identify the association
between dividend changes and subsequent profitability. Existing finance literature
reports this issue in terms of the information content of cash dividend samples. In
contrast, the data in this study primarily consists of dual dividend firms. Specifically,
the Taiwan stock market exhibits the market weights of 5.58% and 56.94% for the
dividend payouts of cash dividends and dual dividends, respectively, from
1997-2006. Therefore, this study addresses the issue of the linkage between dividend
changes and future profitability in a more complete complexity of dividend policy,
namely, a whole spectrum of dividend payout patterns.
Moreover, this study employs a variant of the Bivariate-Ordered Probit model
to clarify the dividend signals emitted from cash dividends and stock dividends in
the dual dividend sample. Specifically, the Bivariate-Ordered Probit model is a
vehicle to screen for the firms with informative dividend signals in this empirical
analysis. The empirical results in this study generally support the hypothesis that
dividend changes link up with future profitability in the samples of cash dividends
and stock dividends; further, this linkage is most significant in the context of a dual
dividend sample. Cross-sectional results also indicate that, in the dual dividend
sample, the proportion of supporting years that support the hypothesis reaches
66.67%.
The main findings of this study remain largely unchanged with respect to
several factors: a variety of profitability measurements, a set of testing procedures,
abnormal dividend payout ratio samples, stock repurchase programs, investment
growth opportunity, business cycles, year effects, and industry characteristics.
Moreover, the main findings of this study generally agree with the balanced dividend
hypothesis of Huang et al. (2009) that optimal dividend payouts can take advantage
of future investment opportunities by restricting excessive cash dividend payouts,
and, in the other way, mitigate the agent problem by paying more cash dividends
instead of issuing more stock dividends. The balanced dividend hypothesis thus
implies a strong positive linkage between dividend changes and future profitability.
22/36
In summary, this study provides new evidence regarding the association
between dividend changes and future profitability using a unique dual dividend
sample. This new evidence may supplement the existing results of finance literature,
which are based on cash dividend samples, with a few stock dividend samples. This
study employs the balanced dividend hypothesis to interpret the positive association
between dividend changes and future profitability in the context of dual dividends.
The balanced dividend hypothesis may be an alternative to the dividend signal
hypothesis or/and retained earning hypothesis, which are frequently used in the
literature as samples of cash dividends or/and stock dividends.
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26/36
Table1
Sample distribution of firms with two consecutive years of dividend payout patterns
year
#
of
sample
Cash
Stock
Dual
No
Other
dividends
dividends
dividends
dividends
dividends
No.
%
No.
%
No.
%
No.
%
No.
%
1997
310
3
0.97
181
58.39
32
10.32
20
6.45
74
23.87
1998
357
2
0.56
150
42.02
32
8.96
22
6.16
151
42.30
1999
420
10
2.38
134
31.90
77
18.33
55
13.10
144
34.29
2000
475
16
3.37
70
14.74
103
21.68
88
18.53
198
41.68
2001
517
32
6.19
45
8.70
140
27.08
122
23.60
178
34.43
2002
578
57
9.86
24
4.15
171
29.58
147
25.43
179
30.98
2003
608
55
9.05
19
3.13
221
36.35
140
23.02
173
28.45
2004
620
65
10.48
8
1.29
244
39.35
124
20.00
179
28.88
2005
634
90
14.20
11
1.74
253
39.91
130
20.50
150
23.65
2006
646
110
17.03
6
0.93
242
37.46
141
21.83
147
22.75
total
5165
440
8.52
648
12.55
1515
29.33
989
19.15
1573
30.45
Dual dividends denote firms with both cash dividends and stock dividends in the same accounting
years. Other dividends denote firms with other dividend payout patterns in two consecutive years.
27/36
Table 2
Dividend payout patterns of two consecutive years: Dividend payout weight
Dual dividends
Cash
Stock
year
dividends dividends
Other
Cash
Stock
Total
Stock
dividends repurchase
dividends dividends dividends
1997
0.18
59.45
12.02
14.31
26.33
14.04
0.00
1998
0.24
36.08
20.84
8.38
29.22
34.46
0.00
1999
2.61
34.76
23.16
19.03
42.19
20.44
0.00
2000
1.22
33.03
19.82
18.07
37.89
23.47
4.39
2001
2.80
18.60
25.68
24.74
50.42
22.17
6.01
2002
5.06
8.16
38.75
20.57
59.32
21.07
6.39
2003
4.27
4.00
44.03
16.58
60.61
27.52
3.60
2004
5.72
0.31
52.92
17.79
70.71
16.81
6.45
2005
9.81
0.29
61.15
12.82
73.97
12.11
3.82
2006
9.74
0.27
46.76
8.45
55.21
29.10
5.68
total
5.85
11.14
41.94
15.00
56.94
21.68
4.39
Unit: %; dividend payout weight represents the ratio of dividend payouts for each individual
dividend payout pattern category (including stock repurchase) to the total market dividends
payouts. The practice of stock repurchase began in the year of 2000. Therefore, no stock
repurchase sample exists during the period 1997-1999.
28/36
Table 3
Sample description of dividend changes
year
Cash dividends
Stock dividends
Dual dividends
No.: 440
No.: 648
No.: 1515
increase decrease constant increase decrease constant increase decrease constant
1997
2
0
1
87
48
46
5
10
17
1998
0
1
1
32
88
30
2
15
15
1999
4
5
1
45
56
33
17
23
37
2000
4
9
3
21
37
12
17
50
36
2001
9
16
7
8
29
8
20
60
60
2002
29
15
13
6
13
5
39
38
94
2003
29
11
15
7
10
2
81
40
100
2004
40
19
6
3
5
0
77
73
94
2005
43
30
17
5
3
3
73
69
111
2006
62
28
20
3
2
1
74
58
110
total
222
134
84
217
291
140
405
436
674
In the dual dividend stocks, the dividend increase sample represents firms in which both cash
dividends and stock dividends increase, or one dividend increases and the other remains constant;
the dividend decrease sample represents firms in which both cash dividends and stock dividends
decrease or one dividend decreases and the other remains constant; the dividend constant sample
represents firms in which both cash dividends and stock dividends remain constant, or both change
equally in the opposite direction.
29/36
Table 4
Matrices of Variable Correlation Coefficients
Panel A: Cash Dividend Sample
Variables
Divchgt
Divchgt
1.0000
Diveqtyt-1
e
Diveqtyt-1 ROAchgt ROAt
Ln(REt)
SalesGRt M/At
Ln(MVt)
-0.0731
0.5227
0.2638
0.1005
0.1647
0.3016
0.1075
1.0000
–0.2293
0.5266
0.3555
0.0648
0.6909
0.2555
1.0000
0.1892
0.1002
0.1728
0.0496
0.0877
1.0000
0.2748
0.0219
0.5468
0.2516
1.0000
0.0788
0.2171
0.7903
1.0000
0.0065
0.0688
1.0000
0.3566
ROAchgt
e
ROAt
Ln(REt)
SalesGRt
M/At
Ln(MVt)
1.0000
Panel B: Stock Dividend Sample
variables
Divchgt
Diveqtyt-1
ROAchgt
e
ROAt
Divchgt
1.0000
e
Diveqtyt-1 ROAchgt ROAt
Ln(REt)
AGRt
Betat
Ln(At)
-0.3269
0.5705
0.1886
0.0675
0.2397
-0.1447
-0.1104
1.0000
–0.3236
0.3580
0.2924
0.4051
0.0840
–0.0460
1.0000
0.2185
0.1303
–0.1195
-0.1110
–0.0431
1.0000
0.2535
0.2317
-0.0408
–0.1248
1.0000
0.1911
0.1879
0.3115
1.0000
0.1374
0.0478
1.0000
0.4840
Ln(REt)
AGRt
Betat
Ln(At)
1.0000
Panel A: Divchgt for cash dividend changes in current period: Diveqtyt-1 for cash payout ratios in
previous period (cash dividend /book value of equity): ROAchgt for asset return changes in current
period: ROAte for expected ROA in current period, the ROA of the first quarter in the next period is
used as proxy for ROAte: Ln(REt) for the natural log of retained earnings: SalesGRt for sale growth rate
in current period: M/At for investment growth opportunity（book value of debt + market value of
equity）/ book value of total asset)；Ln(MVt) for the natural log of corporate market value in current
period. Panel B: Divchgt for stock dividend changes in current period；AGRt for asset growth rate in
current period: Betat for market risk and defined as one year systematic risk for individual stock: Ln(At)
for the natural log of total asset: other variables are defined as those in Panel A.
30/36
Table 5
The association between actual dividend changes and subsequent ROA changes by
actual observations
Cash dividend
Model 1
**
Model 2
***
Intercept
0.004
(0.042)
0.012
(0.000)
CASHDIVCHGt
0.001
(0.866)
0.010***
(0.000)
Stock dividend
Dual dividend
Model 1
Model 2
***
-0.025
(0.000)
-0.005
(0.262)
STOCKDIVCHGt
Model 2
-0.005
(0.289)
0.001
(0.890)
***
Model 1
-0.007
(0.000)
0.013***
(0.000)
-0.000
(0.962)
0.009***
(0.006)
0.007***
(0.001)
0.010***
(0.001)
ROAt
-0.388***
(0.000)
-0.387***
(0.000)
-0.286***
(0.000)
ROAt-1
0.263***
(0.001)
0.124
(0.122)
0.104*
(0.061)
Sample size
440
440
648
648
1515
1515
Adjusted R2
0.000
0.071
0.001
0.082
0.012
0.070
F value
0.03
7.63
***
1.26
14.67
***
6.16
***
22.18***
The numbers in parentheses represent P-VALUEs. The dependent variable is the ROA changes in
the next period.The explanatory variables: CASHDIVCHGt and STOCKDIVCHGt are respectively
for cash dividend changes and stock dividend changes; ROAt and ROAt-1 are respectively for current
and previous total asset returns. This study employs the generalized least-squares estimator to adjust
for the non-spherical disturbances on heterogeneity and autocorrelation of covariance matrices that
frequently appear in pooled cross-sectional data. *,**,*** respectively represent significance levels
of 10%, 5%, and 1%.
31/36
Table 6
The association between actual dividend changes and subsequent ROA changes by
dummy variables
Cash dividend
Stock dividend
Dual dividend
Model 1
Model 1
Model 2
Model 2
Model 2
***
Model 1
***
Intercept
-0.002
(0.722)
0.004
(0.396)
-0.022
(0.000)
-0.002
(0.797)
-0.012
(0.000)
0.010***
(0.001)
DIVUP
0.005
(0.317)
0.012**
(0.034)
-0.010
(0.155)
0.001
(0.924)
0.009***
(0.005)
0.012***
(0.001)
DIVDN
0.010*
(0.096)
0.005
(0.418)
0.001
(0.920)
-0.007
(0.249)
0.001
(0.687)
- 0.007**
(0.040)
ROAt
-0.332***
(0.000)
-0.420***
(0.000)
-0.207***
(0.000)
ROAt-1
0.226**
(0.012)
0.149**
(0.045)
0.034
(0.507)
Sample size
440
440
648
648
1515
1515
Adjusted R
0.007
0.051
0.006
0.079
0.006
0.056
F value
1.41
3.66***
1.66
11.34***
4.09**
22.02***
2
The Model 2 is specified as Eq. (1), the numbers in parentheses represent P-VALUEs. The dependent
variable is the ROA change in the next period. The explanatory variables: DIVUP(DIVDN) is the
dummy and DIVUP(DIVDN)=1, if the dividend increase (decrease), otherwise=0. ROAt and ROAt-1
are respectively for current and previous total asset returns. This study employs the generalized
least-squares estimator to adjust for the non-spherical disturbances on heterogeneity and
autocorrelation of covariance matrices that frequently appear in pooled cross-sectional data. *,**,***
respectively represent significance levels of 10%, 5%, and 1%.
32/36
Table 7
Ordered Probit Model of Expected Dividend Changes
Cash dividend
Stock
Dual dividend
dividend
Cash dividend
Stock dividend
Model 1
Model 2
Diveqtyt-1
-18.656***
(0.000)
-8.952***
(0.000)
-2.014**
(0.011)
-5.755***
(0.000)
ROAchgt
21.790***
(0.000)
15.802***
(0.000)
11.995***
(0.000)
11.013***
(0.000)
ROAt
21.791***
(0.000)
11.667***
(0.000)
11.250***
(0.000)
4.341**
(0.033)
Ln(REt)
0.322***
(0.003)
0.292***
(0.000)
0.276***
(0.000)
0.079
(0.215)
SalesGRt
0.735***
(0.005)
0.008***
(0.000)
M/At
1.344***
(0.001)
0.238***
(0.000)
Ln(MVt)
-0.235**
(0.043)
-0.261***
(0.000)
e
Model 3
AGRt
1.681***
(0.000)
0.510***
(0.000)
Betat
-0.256
(0.118)
-0.269***
(0.001)
Ln(At)
-0.391***
(0.000)
-0.105
(0.128)
Thresholds of Expected Dividend Changes
Between dividend decrease and
constant
0.647
-2.919
-0.511
-1.056
Between dividend constant and
increase
1.427
-2.109
0.007
-0.566
440
648
1515
-323.11
-489.44
-2468.27
Sample size
Log pseudo likelihood
Model 1 and 2 are the Ordered Probit Model of Eq. (2) and Eq. (3), Model 3 is the Bivariate-Ordered
Probit Model of eq. (4). The numbers in parentheses represent P-VALUEs. Model 1: Dependent
variable DIVCHGt is the dividend cash changes at time t and specified as 0, 1, and 2 corresponding
respectively to the cases of dividend decrease, constant, and dividend increase. The explanatory
variables: DIVEQTYt-1 represents the dividend payout ratio at time t-1(by dividend/book value of
e
stockholders equity); ROAchgt represents total asset changes in current period; ROAt signifies
manager’s expected ROA at time t and this study adopts the ROA in the first quarter at time t+1 as the
proxy; Ln(REt) is the natural log of the retained earnings at time t; SalesGRt is the sale growth rate at
time t; M/At is the proxy for investment growth opportunity at time t (( book value of debt + market
value of equity)/book value of total asset )；Ln(MVt) is the natural log of the market value at time t.
Model 2: Dependent variable Divchgt is the stock dividend changes in current period. Explanatory
variables: AGRt for asset growth rate in current period；Betat for market risk and defined as one-year
systematic risk for individual stock；Ln(At) for the natural log of total asset；other variables are defined
as those in Model 1. Model 3: Variables are the same as those in Model 1 and Model 2. *,**,***
respectively represent significance levels of 10%, 5%, and 1%.
33/36
Table 8
The association between expected dividend changes and subsequent ROA changes
Cash dividend
Stock dividend
Dual dividend
Model 1
Model 1
Model 1
Model 2
Intercept
0.004
(0.396)
*
DIVUP
0.012**
(0.034)
0.001
(0.924)
0.012***
(0.001)
DIVDN
0.005
(0.418)
-0.007
(0.249)
- 0.007**
(0.040)
0.007
(0.057)
-0.002
(0.797)
Model 2
-0.005
(0.302)
***
0.010
(0.001)
Model 2
0.009***
(0.002)
EXPDIVUP
0.023***
(0.000)
0.011*
(0.063)
0.016***
(0.001)
EXPDIVDN
-0.010
(0.187)
-0.015**
(0.039)
-0.019***
(0.000)
ROAt
-0.332***
(0.000)
-0.524***
(0.000)
-0.420***
(0.000)
-0.534***
(0.000)
-0.207***
(0.000)
-0.268***
(0.000)
ROAt-1
0.226**
(0.012)
0.396***
(0.000)
0.149**
(0.045)
0.248***
(0.004)
0.034
(0.507)
0.110**
(0.079)
0.060
440
440
648
648
1515
1515
Adjusted R
0.051
0.089
0.079
0.091
0.056
0.061
Fvalue
3.66***
8.14***
11.34***
12.90***
22.02***
26.04***
Sample size
2
Model 1 and Model 2 correspond to Eq. (1) and Eq. (6). The numbers in parenthesis represent
P-VALUEs. Dependent variable is ROA changes in the next period. Explanatory variable:
DIVUP(DIVDN) is the dummy and DIVUP(DIVDN)=1, if the dividend increase (decrease);
otherwise=0. EXPDIVUP (EXPDIVDN) is the dummy and EXPDIVUP (EXPDIVDN)=1 if
expected dividend increase (decrease); otherwise EXPDIVUP(EXPDIVDN)=0; ROAt and ROAt-1
are respectively as the total asset returns of current and previous period. This study employs the
generalized least-squares estimator to adjust for the non-spherical disturbances on heterogeneity
and autocorrelation of covariance matrices that frequently appear in pooled cross-sectional data.
*,**,*** respectively represent significance levels of 10%, 5%, and 1%.
34/36
Table 9
The association between dividend changes and subsequent ROA changes:
An examination of balanced dividend hypothesis
Low dividend ratio
Balanced dividend
High dividend ratio
ratio
Model 1
***
Model 2
*
0.008
(0.099)
Model 1
Model 2
Model 1
0.008
(0.119)
**
**
Intercept
0.018
(0.001)
0.009
(0.036)
0.013
(0.022)
DIVUP
0.000
(0.988)
0.021***
(0.000)
0.015**
(0.040)
DIVDN
-0.010*
(0.060)
0.002
(0.757)
-0.014**
(0.037)
Model 2
0.008
(0.170)
EXPDIVUP
0.011
(0.142)
0.021***
(0.000)
0.014**
(0.044)
EXPDIVDN
0.003
(0.631)
-0.013**
(0.022)
-0.007
(0.357)
ROAt
-0.181
(0.103)
-0.190
(0.200)
-0.269***
(0.000)
-0.403***
(0.000)
-0.228**
(0.020)
-0.255**
(0.047)
ROAt-1
-0.025
(0.820)
-0.023
(0.871)
0.050
(0.417)
0.182**
(0.026)
0.097
(0.355)
0.124
(0.355)
493
493
601
601
421
421
Adjusted R
0.064
0.063
0.095
0.102
0.057
0.045
F value
8.3***
7.5***
12.29***
15.36***
5.9***
4.59***
Sample size
2
Model 1 and Model 2 correspond to Eq. (1) and Eq. (6), respectively. The numbers in
parenthesis represent P-VALUEs. This study follows Huang et al. (2009), and classifies
companies with a cash/stock dividend ratio smaller than 1 as low cash/stock dividend ratio
sample, the ratio larger than 2.33 as high cash/stock dividend ratio sample, and others as the
balanced dividend sample. Dependent variable is ROA changes in next period. Explanatory
variables: DIVUP(DIVDN) is the dummy and DIVUP(DIVDN)=1, if dividend increase
(decrease);
otherwise=0.
EXPDIVUP(EXPDIVDN)
is
the
dummy
and
EXPDIVUP(EXPDIVDN)=1if
expected
dividend
increase
(decrease);
otherwise
EXPDIVUP(EXPDIVDN)=0; ROAt and ROAt-1 respectively represent the total asset returns in
current and previous periods. This study employs the generalized least-squares estimator to
adjust for the non-spherical disturbances on heterogeneity and autocorrelation of covariance
matrices that frequently appear in pooled cross-sectional data. *,**,*** respectively represent
significance levels of 10%, 5%, and 1%.
35/36
Table 10
Dividend changes and subsequent ROA changes: cross-sectional analysis
year
Cash dividend
Model 1
Dual dividend
Model 2
Model 1
Model 2
Panel A：dividend increase
2001
-
-
-
-
2002
-
*
***
***
2003
***
**
***
*
2004
-
***
***
***
2005
-
-
***
***
2006
-
***
*
-
Panel B：dividend decrease
2001
-
***
***
***
2002
-
*
***
***
2003
-
-
-
-
2004
-
-
-
-
2005
-
-
***
**
2006
-
-
**
**
Model 1 and Model 2, respectively, are the actual dividend change model of Eq. (1) and the
expected dividend change model of Eq. (6). This table re-examines the empirical results using
annual cross-sectional data. *,**,*** respectively represent significance levels of 10%, 5%,
and 1%.
36/36
Dividends and Subsequent Profitability: An
Examination of a Dual Dividend Stock Market
Abstract
For decades, studies on dividend signal hypotheses have focused on cash
dividend markets, with a handful of researchers discussing stock dividends. Utilizing
a unique set of data from a dual dividend stock market, this study identifies the
correlation between dividend changes and future profitability. A fundamental
characteristic of dual dividend payouts is that both components, cash dividends and
stock dividends emit separate dividend signals for subsequent profitability. The ratio
of cash to stock dividends may have a similar impact. Therefore, this study employs
a variant of the Bivariate-Ordered Probit model to screen for the dividend signal
sample used in the hypotheses tests. To analyze dividend signal theories, this study
partitions the sample into three sub-samples according to the ratio of cash to stock
dividends. Empirical evidence strongly indicates that dual dividend changes are
positively associated with future profitability in the balanced dividend subsample.
The results of this study are generally robust in terms of accommodating the factors
of stock repurchases, investment growth opportunities, and the business cycles.
JEL classification: G35
Keywords：Dividend, Dividend Change, Dual Dividend, Dividend Signal
1/36
1. Introduction
Bhattacharya (1979), Miller and Rock (1985), and John and Williams (1985), among
others, are the main originators of dividend signal theories. The basic argument of
these theories is based on information asymmetry between corporate managers and
market investors about the firm’s future profitability. To help investors accurately
evaluating the firm’s fundamental value, corporate managers convey the firm’s
future operating performance, profitability, and cash flow information to the market
through a variety channels. Dividend policy is one of the most effective methods of
conveying this information. However, a necessary condition for this argument is that
the message sent must be reliable and informative. If such is not the case, Spence
(1973) argued that false information is costly to the organization.
Cash dividends are costly signals because the distribution of cash immediately
reduces corporate retained earnings, or even worsens them by creating external debt.
Most managers hesitate to promote dividends, even if current earnings are high, due
to the possibility of future profitability uncertainty. On the contrary, few managers
reduce dividends for the fear of disturbing market prices, even when current
earnings are low. Brav et al. (2005) called this phenomenon dividend policy rigidity.
Therefore, market investors can form rational opinions on the peculiar information
content of dividend increases or decreases.
Dividend data from the Taiwan stock exchange shows that cash dividend
payouts only account for 9.74% of the total market, compared to the dual dividend
payout of 55.21% in 2006. Therefore, research on the dividend signal hypothesis in
the Taiwan stock market is necessary to examine a variety of dividend payout
patterns, and dual dividend payouts in particular.
The stock dividend component of dual dividends is not, technically speaking, a
costly signal, nor does the stock dividend component account for the rigidity of
dividend changes. In fact, the stock dividend only affects the transfer of retained
earnings into common stocks, and is therefore irrelevant to corporate value.
However, Grinblatt et al. (1984) and Rankine and Stice (1997a、1997b) argued that if
companies cannot generate sufficient future earnings growth to recoup retained
earnings, then cash dividend distribution is necessarily restricted.1 Moreover, future
stock splits will lose their attractiveness to market investors. Hence the stock
dividend is still expensive though may be not a highly cost signal. Previous authors
presumed that, in the presence of information asymmetry, the distribution of stock
dividends is a signal of optimism for future profitability. This is particularly true
when stock dividends are distributed from retained earnings.2
In the Taiwan stock market, stock dividends are usually transferred from
1
For the protection of debt holders or bona fide third parties in the US, debt covenants or state
incorporation laws often utilize the retained earnings item in the balance sheet to restrict the
distribution of cash dividends.
2
Crawford et al. (2005) duplicated the empirical method of Rankine and Stice (1997a, 1997b) and
found that adverse evidence for retained earnings hypothesis when adding the relevant missing
variables. However, the authors’ results remain largely consistent with those in the literature for
sample firms issuing 20% or 25% stock dividends and the firms within the states imposing cash
dividend restrictions.
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retained earnings; in contrast, the allocation of stock dividends in America depends
on the size of the dividends. According to American accounting principles (AICPA,
1953, Ch. 7B, par. 10), small stock dividends (less than 20%) must issue new shares
at market prices in addition to the common stocks transferred from retained earnings.
This amendment caused large stock dividends3 (25% with par values) to replace
small stock dividends, which were popular from 1920 to 1930. These new large
stock dividends are issued either by transferring additional paid-in capital,
transferring retained earnings, or by a pure stock split.
In contrast, there are few stock splits in Taiwan because stock dividends can be
issued in par by transferring cumulative capital surplus and/or current after-tax
earnings into common stocks. However, the dual dividends of Taiwan stock listed
firms still share the same essential of total dividends, even though they bear no
resemblance to the cash dividends and stock dividends in US markets. In their
empirical studies on dividend signal hypotheses, Allen and Michaely (2003), Zhou
and Ruland (2006), and Skinner (2008) pointed out the increasingly visible trend of
utilizing total dividends instead of cash dividends4.
Before 1998, stock dividends constituted the primary dividend payout method
in the Taiwan stock market and cash dividends appeared only rarely. Rapid earnings
growth has mitigated the potential problem of earnings dilution caused by stock
dividends in the period. However, the income tax amendment of 1998, which
initiated a new 10% tax on corporate retained earnings, has created a positive
motivation for the optimal distribution of current earnings. First, corporate managers
must determine how much of the earnings to hold for future investment, and then
consider the dividend payout patterns for the remainder in terms of cash dividends,
stock dividends or a mix of both5. Traditional mature firms generally prefer cash
dividends or a mix of large cash dividends with small stock dividends. On the
contrary, high-tech firms with future investment opportunities often choose stock
dividends or a mix of large stock dividends with small cash dividends. After year
2000, the economic growth of Taiwan initiated its decline, investors began their
pursuit of stocks that generate large sums of cash dividend. This has changed the
dividend policy from stock dividend orientation to more cash dividends or a mix of
high cash dividends and stock dividends. The results of this study show more
samples of cash dividend firms and fewer stock dividend firms appearing in the
3
For stock dividends between 20-25%, managers, following standard accounting principles, can
decide to use market prices or par values for the new issues at their discretion. However, most firms
adopt the accounting principles similar to those in large size stock dividends.
4
The practices of implementing stock repurchases to replace dividend distribution have been more
visible in US markets since 1980. In 2004, according to Skinner (2008), the amount of stock
repurchases was larger than that of cash dividends. Skinner further classified dividend payout patterns
into five groups: cash-only dividends, cash dividends and regular stock repurchases, only regular
stock repurchases, only irregular stock repurchases, and no dividends. Among these groups, the
cash-only dividends and regular stock repurchases groups account for 61.6% of total dividends. This
implies that research should use the total dividends, by including stock dividends into cash dividends,
to investigate the dividend signal hypotheses.
5
The highest corporate income tax rate in Taiwan is 25%, while the highest personal income tax rate
is 40%. If a company holds all the current earnings, then the corporate income tax rate will increase to
32.5%. Taiwanese income tax codes allow corporate income tax as an exemption from personal
income tax, and there is no capital gain tax in the market. Therefore, large shareholders with personal
income tax exceeding corporate income tax will select a higher after-tax retained earnings ratio and
reduce cash payout.
3/36
market since 2000.
In summary, dual dividends constitute the primary dividend payout method in
the Taiwan stock market. Consequently, a sample consisting of only cash dividends
cannot provide an adequate picture of market dividend information for investigating
dividend signal hypotheses. However, mixing cash dividends with stock dividends
usually obscures the dividend signals of dual dividends. Grinblatt and Titman (1998)
pointed out that market investors might exhibit heterogeneous responses for
companies with less cash dividends accompanied by more stock dividend payouts.
Moreover, Ghosh, and Woolridge (1988) and Michaely et al. (1995) found out that
the stock dividend sample can mitigate the negative impacts of a decline in, or
termination of, cash dividends. However, most conclusions on the dividend signal
hypotheses in the literature are drawn from cash dividend samples. Therefore, this
study employs a unique set of dual dividends data to reflect the various dividend
payout patterns in the market. This study also adopts a variant of the
Bivariate-Ordered Probit model to screen for the effect of the dividend signal sample
used in dividend signal hypotheses tests. The issue of dividend signals is directed
into a unique context in terms of the positive linkage from the changes of dual
dividends into positive future profitability.
The remainder of the paper is organized as follows. Section 2 surveys literature
on dividend payout theories and dividend signal hypotheses. Section 3 describes the
study data. Section 4 describes the research design and model specifications.
Sections 5 and 6 report the main empirical findings and the relevant robustness tests,
respectively. Finally, Section 7 draws conclusions and provides final remarks.
2. Literature
This literature survey on dividend payout theories and dividend signal hypotheses
first covers cash dividend markets, and then stock dividend markets. Miller and
Modigliani (1961) claimed that in perfect capital markets, dividend policy,
especially cash dividend, is irrelevant to corporate value. However, they observed
that the dividend announcements around markets do indeed affect stock price
changes. They then attributed the relevance of dividend policy to information
asymmetry between corporate insiders and market investors, and showed that
dividend changes are an efficient way for managers to reveal the fundamental values
of the corporation. Bhattacharya (1979) and other researchers further developed
asymmetric information models to delineate the role of costly dividend signals in
providing more transparent fundamental value for equity transactions. Laub (1972)
and other researches empirically supported that dividend changes include
information about future profitability6.
6
Some examples of earlier literature include Pettit (1976), Penman (1983), Brickley (1983) and
Healy and Palepu (1988); for the literature of 1990s, Bajaj and Vijh (1990), Aharony and Dotan
(1994) and Yoon and Starks (1995).
4/36
However, some influential studies clearly indicate that dividend changes are
associated with negative subsequent profitability. Jensen and Johnson (1995), and
Michaely et al. (1995) reported the phenomenon of increasing subsequent future
earnings when companies stop paying cash dividends. DeAngelo, DeAngelo, and
Skinner (1996) found similar results using a sample of corporations with at least
nine years of consecutive earnings growth that ended in shrinking: two thirds of the
companies switched from the original earnings growth into the stage of zero growth
in years when dividends increased. Benartzi et al. (1997) discovered that dividend
changes are only significantly associated with previous earning changes, and lack
significant connections with future earning changes. Finally, in Japanese markets,
Fukuda (2000) obtained similar conclusions and attributed the adverse evidence of
dividend signal hypothesis to the over-reactions of corporate managers regarding the
firm’s future prospects.
Contrary to the evidence above, Nissim and Ziv (2001) argued that both
measurement errors and model misspecifications might account for adverse effects
of dividend signal hypotheses. Firstly, they observed that most studies falsely use the
previous market value of equity, which can reflect future earnings too early, as a
deflator of subsequent earning changes, and instead employ the previous book value
of common stocks in their empirical analysis. Secondly, as reported in the literature
they defined return on equity (ROE) as a key predicator for earning changes. In
particular, the mean reversion of ROE implies decreased future earnings when the
current ROE level is higher than its long-term average, and vice versa. Moreover,
Nissim and Ziv (2001) assumed that current earnings follow the data generating
mechanism of first order autocorrelation. Accordingly, they specified current ROE as
a proxy for omitted correlated variables for future profitability and found robust
evidence for the dividend signal hypotheses regardless of the dependent variable of
future earning changes, future earnings, or future abnormal earnings.
Following similar logic, Harada and Nguyen (2005) presented another
argument that the diversity of motivations adopted by managers in dividend
adjustments makes the actual dividend changes data easily fall into adverse dividend
signal hypotheses. Therefore, they believed that expected dividend increases are
only informative when corroborative with current profit increases and brighter
financial measures; otherwise, they might only represent managers’ optimisms
regarding future prospects. Accordingly, Harada and Nguyen (2005) employed the
Logit Model to screen the sample of firms with consistent prospects, and discovered
the validity of dividend signal hypotheses in terms of expected dividend change
models.
This literature survey next turns to the issue of dividend signal content
regarding stock dividends. For the stock dividend practices in American stock
markets, Rankine and Stice (1997b) indicated that the sources of stock dividends,
taking the example of 2-for-1 distribution, consist of pure stock split, additional
paid-in capital, retained earnings, and a mix of additional paid-in capital and retained
earnings. These dividends account for 23.15%, 54.60%, 15.73%, and 6.52% of the
total, respectively. However, Huang et al. (2009) pointed out that the stock dividends
of dual dividend payouts in Taiwan stock markets are always distributed via addition
paid-in capital, retained earnings, and a mix of additional paid-in capital and retained
5/36
earnings. These types of dividends account for 3.25%, 71.67%, and 25.08% of the
total, respectively. The salient discrepancy is the retained earnings source for stock
dividends only accounts for 22.25% in US markets, but reaches 96.75% in Taiwan7.
The main point of this study hinges on the proposal for linking dual dividend
changes and subsequent profitability. The common free cash flow hypothesis and
retained earnings hypothesis can be employed in either cash dividend payout or
stock dividend payout samples. However, the literature development is still in the
infancy for the dual dividend payout markets. Huang et al. (2009) illustrated that a
dual dividend payout firm adopting a balanced dividend payout ratio is significantly
associated with positive subsequent profitability 8 . Fundamentally, a firm is a
going-concern profit-motivated organization that must maintain an optimal cash
level for both current operations and future capital expenditures. Therefore, the
over-distribution of cash dividends might cause a shortage of funds; on the contrary,
too much stock dividend payout aggravates the agency problem, and may cause the
firm to fall victim to acquisition by market competitors (Amit et al., 1989; Smith and
Kim, 1994; Guo et al., 1995). Moreover, companies experiencing either slow growth
or high stock dividend payouts must face strict market pressures from investor
clienteles demanding higher cash dividends, particularly from aged investors and
annuity fund managers (Baker and Wurgler, 2004; Graham and Kumar, 2006; Eun
and Huang, 2007).
Finally, some caveats on the dividend signal hypotheses in the literature deserve
special attention. Firstly, Grullon et al. (2005) re-examined the results of Nissim and
Ziv (2001) using thirty-five years of cross-sectional data, and found that only 29% of
the sample years supported the dividend signal hypothesis for the following years
after dividend payouts. Therefore, this study employs cross-sectional data to
supplement the main pooled cross-sectional data, and examines the association
between dividend changes and subsequent profitability. Secondly, Grullon and
Michaely (2004) indicated that dividend changes did not suggest positive future
profitability based on a sample of stock repurchases. Therefore, the current study
investigates the dividend signal hypothesis by excluding the stock repurchases
sample as a sensitivity check for the main results.
3. Data description
The study uses data from the Taiwan Economic Journal (TEJ) that includes variables
of dividends, financial statements, equity prices, corporate governance, and stock
repurchases. The basic data was gathered annually, with the exception of the profit
data, which was reported from annual first quarters. The lengths of data periods in
previous studies vary greatly. Studies on American markets generally adopt longer
study horizons. For example, Nissim and Ziv (20001) researched the period of
7
One caveat is that this study draws on a sample of stock dividends from additional paid-in capital.
This might affect the empirical results regarding the association between dual dividends and future
profitability. Therefore, this study executes the robustness test based on this concern in section 5.4.
8
The authors presume that the managers adopt balanced dividends based on two considerations.
Firstly, distributing optimal cash dividends convey positive signals of self-discipline and solvent
financial prospects. Secondly, adopting optimal stock dividends might indicate optimism about future
profitability. The authors find, through trial-and-error, that ratios of cash dividends to stock dividends
for dual dividend sample ranging between 1 and 2.33 can generate a positive association between
dual dividends and future profitability.
6/36
1963-1998, while Grullon et al. (2005) covered a thirty-five year period. In contrast,
related studies in Japanese markets typically involve shorter horizons. Kato et al.
(2002) and Harada and Nguyen (2005) used ten-year data, for instance. Due to the
lack of cash dividend data before 1997, the current study sets up the ten-year
research horizon of 1997-2006. However, the necessary empirical data should
include future profits, future returns, and some lagged variables. As a result the
processing data actually covers a 14-year period, from 1995-2008. This study applies
the following sample selection criteria.
1. The sample is consisted of firms listed on the Taiwan Stock Exchange.
2. This study excludes samples of preferred stocks, TDR, or firms with incomplete
financial data.
3. This study excludes firms in the financial sectors as financial firms have
different financial structures than non-financial firms.
4. The sample firms used to test the dividend signal hypotheses must generate
dividends in two consecutive years. The research sample was divided into three
sub-samples according to dividend payout patterns: cash dividends, stock
dividends, and dual dividends. Finally, the sample of dividend changes was
partitioned into three sub-samples: dividend increase, dividend decrease, and
dividend constant.
Table 1 presents the sample distribution of firms with two consecutive years of
dividend payout patterns following the above sample selection criterions. The total
sample includes 5165 firms. Of this total, there are 440 firms with cash dividends,
648 with stock dividends, and 1515 with dual dividends. The remaining firms belong
to the categories of no dividends and other dividends. In 1997, the total sample firms
reached 310, where firms with cash dividends and dual dividends accounted for 3
and 32, respectively. In 2006, however, the whole sample doubled to 646, and both
cash dividend and dual dividend samples increased to 110 and 242, respectively.
However, the stock dividend sample significantly decreased from 181 in 1997 to
only 6 in 2006. In general, the dual dividend sample exhibits a steady increase from
the first year of the research up to 2005, while the cash dividend sample surges in
2002, followed by a steady growth trend thereafter.
<insert Table 1 here>
Next, this study examines the sample distribution of firms with two consecutive
years of dividend payout patterns in terms of market payout weights. As Table 2
illustrates, the market dividend payout weights of cash dividends, stock dividends,
and dual dividends in 1997 respectively accounted for 0.18%, 59.45%, and 26.33%
of the total. However, these ratios changed to 9.74%, 0.27%, and 55.21% in 2006.
Similar to Table 1, the payout weight of stock dividends significantly decreased
during the period, while the proportions of cash dividends and dual dividends soared.
After partitioning dual dividends into cash components and stock components, these
figures exhibit the phenomenon of increasing cash components versus decreasing
stock components. However, there is a surprising twist from 2005-2006: the
dividend payout ratio of the other dividend category increased from 12.11% to
29.10% while the ratio for dual dividends decreased from 73.975% to 55.21%. A
7/36
closer inspection of the other dividends firms in 2006 reveals that the switch of dual
dividends into cash dividends and the newly increasing cash dividends accounted for
24.35% of the entire market. Compatible with the trend of the changes in dividend
payout patterns above, the market weight of cash dividends reached 31.00% in the
extrapolative year of 2007, and the total sample firms increased to 148.
<insert Table 2 here>
DeAngelo et al. (2004) reported the phenomenon that large companies in
American markets are the primary distributors of cash dividends. In contrast, only
five of the top 20 in Taiwan firms paid out cash dividends in 2007; the other 15 firms
employed a dual dividend policy. The dividend payout patterns in Taiwan apparently
bear little resemblance to those in American markets. However, even the grand
blue-chip stocks in Taiwan classified as dual dividend payout firms generated huge
cash dividend components compared to their stock dividend components. Taiwan
Semiconducting Company, the highest dividend payout firm in the Taiwan stock
market, is a notable example. This company distributed a cash dividend component
of up to US$ 2.37 billion, but only US$0.02 billion for the stock dividend
component. A similar phenomenon appears in the other 14 top dual dividend payouts
companies. Moreover, cash dividends from the top 20 firms account for 54.10% of
all cash dividend payouts in the market. In short, with regard to the real content of
dividend payouts in Taiwan, the concentration of cash dividends in large companies
mimics the behaviors observed in American markets.
Next, this study examines the details in the sample of dividend changes. In the
cash dividends category, firms with increasing, decreasing, and constant dividends
respectively account for 222, 134, and 84 firms. In contrast, Table 1 of Nissim and
Ziv (2001) shows that the samples of corporate accounting years with dividend
constants reached 19004 from 1963-1997, with the next category being the dividend
increase sample at 12105, and finally the dividend decrease sample at 697. A similar
pattern appears in Table 1 of Harada and Nguyen (2006), indicating that the samples
of firms with constant, increasing, and decreasing dividends respectively account for
6564, 4002, and 3142 firms. These figures indicate that the sample of firms with
constant dividends is the primary pattern in both American markets and Japanese
markets, while increasing dividends accounts for the most firms in Taiwanese
markets. However, after adding the cash dividend and dual dividend samples, the
number of firms with constant, increasing, and decreasing dividends in Taiwan
becomes 758, 627, and 570, respectively. The relative size of dividend changes in
the Taiwanese market agrees with the results reported in the literature.
The previous figures of dividend changes indicate that the dividend policy is
most rigid in American markets, followed by Japanese markets, and finally
Taiwanese markets. Even through several business cycles from 1963-1997,
American markets exhibit a huge size constant dividend sample compared to the
decreasing dividend sample: the former is 27.27 times the size of the latter. The
number of firms with constant dividends in Japanese markets and Taiwanese markets
is much smaller. The following rationales may be ascribed to this dichotomy. Firstly,
American markets distribute dividend payouts on a quarterly basis, and the corporate
8/36
profitability apparently exhibits less volatility on a quarterly frequency. Therefore,
firms tend to maintain constant dividends unless there are strong signs indicating
future profitability changes. Secondly, American companies strive for global
diversification, and are therefore less susceptible to the impacts of regional business
cycles than firms in Japan or Taiwan are. This may partially explain the more stable
dividend payouts in American firms compared to those in Japan or Taiwan. Thirdly,
as Zeff (1982) pointed out, the statutes of accounting principles have discouraged the
practice of stock dividend payouts since 1953. Due to an insufficient stock dividend
buffer, the practice of cash dividends changes diminished thereafter. On the contrary,
according to Kato and Tsay (2002), unpaid stock dividends were popular in Japanese
markets from the end of the war to the economic recession of the 1990s. Stock
dividends also played a major role in Taiwanese markets until the year 2000.
Based on the observations above, the practice of dividend payouts in American
markets might long data-horizon research better suited to examining the association
between dividend changes with subsequent profitability. However, merging quarterly
dividend data into annual data to match annual financial data has drawbacks. First,
merging data might obscure the seasonal patterns of dividend changes, and therefore
weaken the association between dividend policy information and future profitability.
On the contrary, the dividend payout practices in Taiwan are generally on annual
basis, and may help reveal the association between dividend changes and subsequent
profitability.
<insert Table 3 here>
4. Research Design
Finance literature contains two common methodologies for dividend signal
research. The first method is event study, which is typically used to evaluate the
short-run stock market reactions of dividend announcements. Examples of this
approach include, among others, Pettit (1972), Charest (1978), Aharony and Swary
(1980), Michaely et al. (1995), Fukuda (2000), and Lee and Yan (2003). The other
method involves using multiple regressions to examine the association between
future profitability and dividend changes; Nissim and Ziv (2001), Harada and
Nguyen (2005), and Grullon et al. (2005) adopt this approach. Using the former
method, financial academics generally agree that market reactions follow the
directions of dividend changes. However, there still controversies surrounding the
latter method. Therefore, this study presents a novel three-stage approach to revisit
the issue of dividend signal hypothesis.
4.1. Model of actual dividend changes
A quick way to estimate the association between future profitability and
dividend change is to employ dividend changes as the explanatory variable, and then
9/36
observe the signs of the estimated coefficients. Nevertheless, a more elaborate model
is necessary if investors prefer to look at how dividend increases or decreases
individually affect future profitability. Harada and Nguyen (2005) used dummy
variables to represent the observations of dividend increases and dividend decreases
separately in two estimators. Nissim and Ziv (2001) combined these two variables
into one estimator. For parsimony, this study adopts the latter method and establishes
the association of future profitability with dividend changes as follows.
ROACHGt 1   0  1 DIVUPt   2 DIVDNt   3 ROAt   4 ROAt 1   t 1
(1)
Where ROACHGt+1 represents the ROA changes in the next period；DIVUPt
(DIVDNt) is the dummy for dividend increase(decrease), in the case of dividend
increase (decrease), DIVUPt (DIVDNt) =1; otherwise, DIVUPt (DIVDNt) =0；ROAt
and ROAt-1 respectively represent the asset return for the current and previous
periods, and are calculated by the earnings before interest and tax divided by total
asset；εt+1 represents the disturbance term. In general, DIVUPt (DIVDNt) should have
a positive (negative) association with ROACHGt+1.
Equation (1) must consider the data generating process of the ROAt+1 change.
Therefore, this equation incorporates a dynamic time series model generated by the
first order auto-regression,9 which fits well in the data, along with the proxy for
ROAt change,10 to mitigate the possible bias due to corporate earnings management
behavior and other omitted correlated variables.
In addition to the ROA in Eq. (1), the literature commonly uses equity return
(ROE), earning per share (EPS), and continuing earnings per share (Cont_EPS) to
measure future profitability. ROE is defined by the earnings before interest and tax
divided by stockholders’ equity, and Conti_EPS represents the manager’s expected
normal EPS. However, this study ultimately adopts ROACHGt+1 as the measure of
future profitability due to the following considerations. Firstly, ROA is more robust
to the changes of capital structure than other measures, such as EPS, CEPS, and
ROE. Secondly, ROA is mostly unaffected by the before tax non-recurring items as
well as non-cyclic items. Thirdly, managers are used to manipulating earning
managements for window dressing on operating performance. Fourthly, Barber and
Lyon (1996) pointed out that under most circumstances, ROA is the most efficient
measure for measuring future operating performance. Finally, for empirical
considerations, this study examines the explanatory power of the ROA change and
9
This study employs ARMA model estimation to find the appropriate data generating process of
ROACHGt+1 as AR (1).
10
This study employs Q statistics to examine the residual of ROACHGt+1 . Empirical evidence shows
that the past 36 periods exhibit white noise and then form a dynamic model. Meanwhile, this study
decomposes the ROACHGt into ROAt and ROAt-1 in Eq. (1) for better model fitness.
10/36
ROA growth rate in early working stages. Results indicate that the former is superior
to the latter.
4.2. Screening method on dividend signal sample
Harada and Nguyen (2005) recently proposed a Logit Model that is able to both
reflect corporate financial status and capture potential dividend changes. The present
study extends Harada and Nguyen’s (2005) approach. Firstly, this study implements
a three-dimension Ordered Probit Model instead of the two-dimension Logit Model
to capture the information hidden in dividend constant firms, which account for the
majority of dual dividend payouts. Firms with constant dividends might simply be
firms with increasing or decreasing dividends, but whose corporate managers are
ignorant of future prospects. In the two-dimension Logit Model, similar situations
can occur in firms with dividend increases or decreases. Secondly, this study
estimates the effects of the changes on cash dividends, stock dividends, and dual
dividends using three separate models. The first Ordered Logit model of cash
dividend changes is specified as follows.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 SalesGR t   6 M At   7 Ln ( MV t )   t
(2)
Where DIVCHGt represents the cash dividend changes at time t. This term is
specified respectively as 0,1, and 2 for the cases of decreasing dividends, constant
dividends, and increasing dividends; DIVEQTYt-1 represents the dividend payout
ratios at time t-1(total dividends/book value of stockholder equity); ROAte represents
the manager’s expected ROA at time t, and is defined by the proxy of ROA in the
first quarter at time t+111; Ln(REt) is the natural log of the retained earnings at time t;
SalesGRt is the sale growth rate at time t; M/At is the proxy for investment growth
opportunity at time t, and is calculated as the sum of the book value of debts and
market value of stockholder equity divided by the book value of total assets (Fama
and French, 2002; Zhou and Ruland, 2006)；Ln(MVt) is the natural log of the market
value at time t; and εt represents the disturbance term.
The stock dividend change specified by the second Ordered Probit Model is as
follows.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 AGR t   6 Beta t   7 Ln ( At )   t
(3)
Where Divchgt represents the stock dividend changes at time t. For the explanatory
variables, AGRt is the growth rate of total asset at time t; Betat stands for the
11
Most dividend announcements in Taiwan are made after the first quarter of the subsequent year.
This phenomenon justifies the specification of Eq. (1) because corporate insiders possess information
about company earnings in the first quarter of the next year.
11/36
systematic risk of individual stocks; Ln(At) is the natural log of total asset at time t;
and the other variables are the same as those in Eq. (2).
Since dual dividend changes consists of both the cash dividend changes
component and the stock dividend changes component, the specification of Eq. (2)
or Eq. (3) alone assumes that any missing information is embedded in the dual
dividend payout sample. This study further employs a Bivariate-Ordered Probit
Model to capture the effects of cash dividend changes and stock dividend changes as
follows12.
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 SalesGR t   6 M At   7 Ln ( MV t )   t
DIVCHG t   0   1 DIVEQTY t 1   2 ROACHG t   3 ROAte   4 Ln ( RE t )
  5 AGR t   6 Beta t   7 Ln ( At )   t
(4)
These variables are defined as those in Eq. (2) and Eq. (3).
The estimated parameters of Eq. (2) through (4) and the expected dividend
change thresholds are used to compute the probabilities of decreasing dividends,
constant dividends, and increasing dividends for the individual firms, according to
Eq. (5).
Pr( y t  0 xt ,  ,  )  F ( 1  xt  )
Pr( y t  1 xt ,  ,  )  F ( 2  xt  )  F ( 1  xt  )
Pr( yt  2 xt ,  ,  )  1  F ( 2  xt  )
(5)
Where the terms γ1 and γ2 represent the expected dividend change thresholds, and F
(‧) is the cumulative distribution of the disturbance term. The dual dividend sample
is classified into three types (expected dividend increase, expected dividend decrease,
and expected dividend constant) according to the expected cash dividend changes
and the expected stock dividend changes calculated above.
Finally, this study considers the empirical implications of the dividend payout
practices in Taiwan. Specifically, corporate managers prefer the rigidity of cash
dividend payouts and the trend of upturn instead of downturn in stock dividend
payouts. Accordingly, the probabilities of cash dividend increase, cash dividend
decrease, and stock dividend decrease are adjusted upwards. Ultimately, the process
of dividing the dividend changes sample into three distinct categories is as follows:
Expected Dividend Decrease
Expected Dividend Constant
γ1
Expected Dividend Increase
γ2
12
For estimation efficiency, this study employs a two-dimensional Bivariate-Ordered Probit Model
to screen the sample of dual dividend firms. For details on the Bivariate-Ordered Probit Model, refer
to Yamamoto and Shankar (2004) and Zayeri and Kazemnejad (2006).
12/36
4.3. Model of Expected Dividend Changes
In the final step, this study replaces the model of dividend changes with the model of
expected dividend changes to screen for the effective dividend signal sample. The
expected dividend change model presumably provides more informative content of
subsequent profitability than the dividend change model. The model of expected
dividend changes is specified as follows.
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt   3 ROAt   4 ROAt 1   t 1 (6)
Where EXPDIVUP(EXPDIVDN) is a dummy variable that takes the value of 1 in the
case of expected dividend increase (decrease); otherwise 0; the other variables are
defined as in Eq. (1).
4.4. Description of research variables
This study next explores the effect of the explanatory variables in Eq. (2) and
Eq. (3) on the associations with dividend changes and hypothesizes the theoretical
expectations.
According to investment intuition, the first factor might influence the dividend
changes would be the previous dividend levels. However, after screening for the
dividend signal sample using Eq. (2) to (5), this study employs DIVEQTYt-1 instead
of dividend levels since the latter shows no explanatory power on future earnings.
The adoption of DIVEQTYt-1 can be attributed to Miller and Modigliani (1961).
These authors argued that, in the presence of target payout ratios and an
unwillingness to cut dividends, investors are much more likely to interpret a change
in dividends as a change in managements’ view of the future prospects of the firm.
Harada and Nguyen (2005) conjectured a negative association of DIVEQTYt-1 with
future earnings. The following rationales support this negative association. Firstly,
the lower dividend payout ratio is, the more room for dividend increase will be and
the less the pressure for subsequent profitability. Secondly, lower dividend payout
ratios, according to conventional wisdom, represent higher investment opportunities
and better prospects.
Next, this study postulates that past profitability has a major affect on dividend
changes. Brav et al. (2005) argued that managers try hard to maintain a fixed
dividend policy until corporate earnings have significantly changed for several
consecutive years. Fukuda (2000) provided similar results, indicating that dividend
increases usually accompany increases in current and past earnings, and particularly
for current earnings. On the contrary, negative current and past earnings often appear
before dividend decreases. Therefore, this study employs changes in asset return,
ROACHGt , as a proxy for current and past earnings. This approach captures the
positive association between ROACHGt and dividend changes.
The dividend decisions that mangers make depend primarily on the prospects of
corporate future profitability (Lintner, 1956). On the timing of dividend
announcements, most companies release current dividends in the second quarter.
Consequently, first quarter earnings are related to the content of expected dividends.
Therefore, this study adopts the total asset return of the first quarter in the
13/36
subsequent period, ROAte , as a proxy for future profitability and anticipates a
positive association between ROAte and dividend changes.
For institutional consideration, corporate dividend changes exhibit a close
relationship with retained earnings (Ln(REt)). In the US, for the protection of
bondholders and other claimers, bond contracts and state legislation usually imposes
restrictions on the retained earnings distributed in cash dividends. Similarly,
corporate laws in Taiwan prohibit companies with negative retained earnings from
distributing cash dividends. However, companies with high-retained earnings
generally possess high free cash flows, and readily fall to the acquisitions of
competitors. Therefore, managers often use high dividend payouts as an
entrenchment tool to prevent potential threats from the competition (Amit et al.,
1989; Smith and Kim, 1994; Guo et al., 1995). Following the argument above,
companies with higher retained earnings tend to issue more cash dividends.
Next, sales growth (SalesGRt), which acts as a proxy for corporate operating
performance may exert a significant influence on current profitability, and therefore
influence corporate dividend changes. In particular, sales growth remains the major
factor affecting the real profitability of Taiwanese firms. This study postulates a
positive association of the sale growth with dividend changes.
Investment growth opportunity (M/At) generally reflects corporate future
profitability, and hence affects dividend policy. Most market investors do not foresee
high future profitability and high cash dividends in a company with low investment
growth. When market expectation is consistent with corporate profitability prospects,
then dividend changes can be associated with investor forecasts. Therefore, this
study predicts a positive relationship between investment growth opportunity and
corporate dividend changes.
The size of a firm may be a determining factor for dividend changes, and has
little to do with the profitability. Since large firms usually have more retained
earnings, their current earnings have a lesser impact on dividend policy. In addition,
the managers of large firm usually believe that a stable dividend policy will benefit
the corporate stock prices in the markets. In contrast, the managers of small firms
tend to adjust dividend payouts more often due the insufficiency of accumulated
retained earnings. This study employs the market value (Ln(MVt)) and total
asset(Ln(At)) as explanatory variables for cash dividend changes and stock dividend
changes, and postulates a negative relationship between firm size and dividend
changes.
Besides financing through equity and debt, the growth of profitability is a major
factor in sustaining total asset growth (AGRt). In general, high profitability growth
implies a high level of positive cash flow for the firm. Therefore, this study
hypothesizes a positive association between total asset growth and dividend changes.
In addition to the performance factors above, market risk is the final factor
influencing dividend policy. This study employs the systematic risk Betat to
represent the associated market risk that firms face. A high Betat implies that firms’
performance may be more vulnerable to the external economy, and the ties between
14/36
customers and the firms’ products and services are loose. Accordingly, managers
attempt to avoid distribute dividends when there is high uncertainty in future
markets. Therefore, this study conjectures a negative relationship between market
risk and dividend changes.
Finally, this study explores the potential multicollinearity among explanatory
variables in the regression analysis above in terms of the covariance matrix reported
in Table 4. Panel A in Table 4 shows that all the coefficients of correlation in the
cash dividend sample are well below 0.7, except for the retained earnings and
market value, with a coefficient of 0.7903. For the stock dividend sample, reported
in Panel B of Table 4, the coefficients of correlation are all smaller than 0.6. In
addition, the diagnostics of the regression analysis indicate that the average VIF
coefficients are well below 2.52 for both samples. Accordingly, this study ignores
the potential multicollinearity problem when estimates Eq. (2),(3), and (4).
<Table 4 is inserted here>
5. Empirical results and analysis
This study investigates the dividend signal hypothesis using a unique pooled
cross-sectional dataset supplemented with cross-sectional data. This study compares
empirical evidence with the results of Nissim and Ziv (2000) and Narada and
Nguyen (2005) to determine the commonalities and unique factors in different
markets.
5.1. Model of Actual Dividend Changes
Conventional wisdom hypothesizes that dividend changes are positively
associated with subsequent profitability. The empirical results in Model 1 of Table 5
show that, in the absence of control variables (ROAt and ROAt-1), the postulated
association only holds for the dual stock dividend sample at the 1% significance
level. In contrast, adding the control variables in the Model 2 of Table 5 shows that,
except for the stock dividend sample, there is a significantly positive association in
both cash dividend and dual dividend samples. These findings agree with those of
Nissim and Ziv (2001, P2119), who stated that dividend changes are followed by a
significant positive future profitability. However, this conclusion comes with the
caveat that instead of using dividend changes, Nissim and Ziv employed the rate of
change in dividend per share in their analysis.
<insert Table 5 here>
Next, to clarify the linkage between the direction of dividend changes and
15/36
future profitability, this study employs the dummies of dividend increase and
dividend decrease to replace the dividend changes in the regression analysis above.
Model 1 of Table 6 shows that in the absence of the control variables, the dividend
dummy is the only significant explanatory variable in the cash dividend and dual
dividend samples. Similar to the results of Table 5, after adding the control variables,
all the explanatory variables, except the dividend decrease dummy in the cash
dividend sample, exhibit the hypothesized associations. Moreover, the dividend
increase dummy in both cash dividend and dual dividend samples indicates a
significantly positive association with subsequent profitability. The evidence in Table
6 agrees with Nissim and Ziv (2001, P2119) and Harada and Nguyen (2005, P512),
indicating that dividend increase is often followed by positive future profitability.
However, the association between dividend decrease and future profitability still
lacks statistical support.
<insert Table 6 here>
5.2. Screening for dividend signal samples
To explore the evidence supporting the hypothesis made by the decreasing
dividend sample, this study employs the Ordered Probit Model to screen for the
dividend signal samples. The empirical results of the Ordered Probit Model of
expected dividend changes are as follows. Firstly, Model 1 in Table 7 shows that all
explanatory variables display a significant influence on the expected dividend
changes in the context of the cash dividend sample. Secondly, in the stock dividend
model, all explanatory variables except Betat are significantly associated with
expected dividend changes. Finally, in the Bivariate-Ordered-Probit model for the
dual dividend sample, there is a dichotomy between cash dividends and stock
dividends: all explanatory variables are significant in the former, whereas retained
earnings (Ln(REt)) and total assets (Ln(At)) do not show any significant influence
upon expected dividend changes in the latter. Moreover, the signs of all estimated
coefficients agree with the hypothesized associations across all dividend payout
e
patterns. These empirical results imply that higher ROAchgt, ROAt , Ln(REt),
SalesGRt, M/At, and AGRt; and lower Diveqtyt-1, Ln (MVt), Betat, and Ln(A t ) create
a higher tendency for dividend increase announcements. The opposite is true for
dividend decrease announcements.
Finally, this study uses the sample of cash dividend to provide details on the
procedure of transforming dividend changes into the version of expected dividend
16/36
changes. Before this procedure, the samples of dividend increase, constant, and
decrease included 222, 84, and 134 firms, respectively. After the estimation on Eq.
(2), two threshold values were incorporated into Eq. (5) to calculate the probabilities
of three dividend changes for each sample firm. Moreover, by considering the
rigidity of dividend policy in the related literature, this study adopts a trail-and-error
approach to adjust the probabilities for both dividend increase and dividend decrease
until the best-expected profitability is reached. This adjusting process eventually
results in the three sub-samples of expected increasing dividend, constant dividend,
and decreasing dividend, with 154, 224, and 62 firms, respectively.
<insert Table 7 here>
5.3. Models of Expected Dividend Changes
This study further tests the dividend signal hypothesis by examining the
information content of the expected dividend change sample instead of the actual
dividend change data on future profitability. Table 8 reports the empirical results for
both actual dividend changes (illustrated by Model 1) and expected dividend
changes (illustrated by Model 2). The evidence strongly indicates that the expected
dividend change model creates a more significant linkage between dividend changes
and future profitability across three dividend payout patterns. Model 2 exhibits
superior model fitness than Model 1 in terms of R2 and F statistics. Ultimately, the
empirical evidence reveals expected dividend changes, which strongly suggest a
significant association between expected dividend changes and subsequent
profitability, particularly for the dual dividend sample13.
<insert Table 8 here>
5.4. An Examination of Balanced Dividend Hypothesis
This study further analyzes why the dividend signal hypothesis gains firm
support in the dual dividend sample in terms of the balanced dividend hypothesis.
Following Huang et al. (2009), this study decomposes the dual dividend sample into
three sub-samples (low cash/stock dividend ratio, balanced dividend ratio, and high
cash/stock dividend ratio) based on the proportions of cash dividends to stock
13
Interestingly, this study conducts an analysis using return data instead of ROA in Eq. (6). The
empirical results show that there exists strong association between expected dividend change and
future return in the dual dividend-paying sample. For saving space, these results are available upon
request.
17/36
dividends. Table 9 indicates that the expected dividend model in the sample of
balanced dividends strongly suggests the dummy variables of expected dividend
increase and decrease are significantly associated the subsequent ROA changes.
Moreover, the balanced sample exhibits superior model fitness in terms of R 2 and F
value compared to those in the other two sub-samples. This evidence remains largely
unchanged after excluding data for firms with stock dividends accrued from paid-in
capitals.
<insert Table 9 here>
5.5. Evidence on annual cross-sectional data
The empirical evidence on the association between dividend changes and future
profitability above was drawn from the pooled cross-sectional data. However, the
issue of the stability of the association in cross-sectional annual data might be a
concern for market practitioners. This study addresses this concern by re-examining
the dividend signal hypothesis using cross-sectional data. The empirical data are
only available for the samples of cash dividends and dual dividends during the
period 2001-2006 because, prior to 2001, the practice of cash dividends was
relatively rare in Taiwan, as were stock dividends after 2003. The empirical results
of the case of dividend increase in the cash dividend sample, as Panel A of Table 10
indicates, show that the proportion of years with significant association for dividend
change model (Model 1) and expected dividend change model (Model 2) reach
16.67% and 66.67%, respectively, while the figures decline to zero and 33.33% in
the case of dividend decrease. Moreover, the linkage between dividend changes and
subsequent profitability is rather strong in the dual dividend sample, with at least
66.67% significant years uniformly across both cases of dividend increase and
dividend decrease. Ultimately, the empirical evidence drawn on the proportion of the
significant association predicted by our expected dividend change model in the case
of dividend increase is far larger than the 29% found in Grullon et al. (2005,
Page1665-1666).
<insert Table 10 here>
6. Robustness Tests
This section presents, reports the results of robustness tests to investigate
the sensitivity of the empirical results above in terms of the following eight
18/36
potential factors that might exert an influence on the nature of dividend signal
hypothesis14.
6.1. Alternative measures of future profitability
Finance literature commonly uses equity return, earnings per share, and
continuing earnings per share to measure future profitability. This study adopts
the criterion of the model fitness in terms of R2 among the dividend signal
hypothesis tests and finds out the ROA serves best.
6.2. Excluding irregular dividend sample
When companies incur deficits and then distribute dividend payouts using
non-surplus items, the sample of dividend changes may be less informative
regarding the content of dividend signals. However, a normal company would
not pay out more than its current surplus. After empirically retesting the
dividend signal hypothesis using data that excludes companies incurring a
negative current surplus or a dividend payout ratio larger than 1, the main
findings of this study remain largely unchanged.
6.3. Alternative estimation procedures
This study employs the generalized least-squares estimator (GLS) to adjust for
the non-spherical disturbances on heterogeneity and autocorrelation of
covariance matrices that frequently appear in pooled cross-sectional data.
Moreover, this study applies the Fama and MacBeth (1973) procedure for cross
validation. The evidence from this procedure largely supports the main findings
of the GLS method.
6.4. Effect of stock repurchases
To clearly delineate the linkage between dividend changes and future
profitability, this study re-tests the dividend signal hypothesis using a database
that exclude companies that carry out stock repurchases. The main findings
from this new data largely agree with those from the original data.
14
For the sake of brevity, this section only reports the main results of the related robustness tests.
Details are available from the authors upon request.
19/36
6.5. Investment growth opportunities
Miller and Modigliani’s (1961) dividend irrelevance argument asserts that
corporate value is determined by investment opportunities, and is therefore
irrelevant to dividend policy. Conventional wisdom indicates that the higher
retained earnings lead to higher investment opportunities for firms.
Consequently, an increasing dividend may hinder the accumulation of retained
earnings. Gordon’s (1962) fixed dividend growth model holds a similar view,
stating that under the assumption of fixed expected return, a high dividend
payout entails low future growth. Therefore, this study uses Eq. (7) and (8) to
examine whether investment opportunities are more relevant to future
profitability and weaken the linkage between dividend changes and future
profitability.
ROACHGt 1   0  1 DIVUPt   2 DIVDNt
  3 M / At   4 ROAt   5 ROAt 1   t 1
(7)
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt
  3 M / At   4 ROAt   5 ROAt 1   t 1
(8)
Where M/At represents investment growth opportunities ((book value of debt +
market value of equity)/(book value of total asset)), and other variables are defined
as those in Eq. (1) and (6). The empirical results from Eq. (7) and (8) are similar to
those in previous sections, indicating that investment growth opportunities are
irrelevant to the linkage between dividend changes and future profitability.
6.6. Effect of business cycles
Changes in economic growth might affect the corporate dividend policy,
particularly for the emerging Taiwan stock market. Specifically, if the subsequent
economic growth rate continuously increases, ceteris paribus, the company might be
more optimistic about future profitability, and distribute more dividends. To identify
the influence of business cycles, this study employs the GDP growth rate as a proxy
for business cycles (see Bekaert et al., 2006; Furceri and Karras, 2007) and examines
the association between dividend changes and future profitability in the following
20/36
regressions.
ROACH t 1   0   1 DIVUPt   2 DIVDN t
(9)
  3GDPGRt   4 ROAt   5 ROAt 1   t 1
ROACH t 1   0   1 EXPDIVUPt   2 EXPDIVDN t
(10)
  3GDPGRt   4 ROAt   5 ROAt 1   t 1
Where GDPGRt represents the domestic gross product growth rate, and other
variables are defined as those in Eq. (1) and (6). Empirical results show that the
main findings remain largely unchanged in the context of business cycles. This study
adds investment growth opportunity to Eq. (9) and (10), and empirical results
indicate that the main results regarding the association between dividend changes
and future profitability are generally robust to controlling both internal and external
growth factors.
6.7. Year effect
This study uses pooled cross-sectional data for regression analysis. However, to
address concerns about the stability of the empirical results across different years and
investigate the possible year effect on the empirical results, this study employs the
year dummy variable into Eq. (1) and (6). Results show that the main explanatory
variables exhibit the same results as before. Moreover, the year dummy variables are
all insignificant, revealing no year effects in the empirical data.
6.8. Industry effect
The industry effect is the final variable to be checked on in the association
between dividend changes and future profitability. This study considers the industry
classification, and specifies the relevant empirical models as follows:
ROACHGt 1   0  1 DIVUPt   2 DIVDNt
n
  3 ROAt   4 ROAt 1   i INDi   t 1
i
ROACHGt 1   0  1 EXPDIVUPt   2 EXPDIVDNt
21/36
(11)
n
  3 ROAt   4 ROAt 1   i INDi   t 1
(12)
i
Where INDi is an industry dummy, defined as INDi=1 when sample firm belongs to
the i-industry, and INDi=0 otherwise. This study adopts the industry classification of
the Taiwan Stock Exchange Corporation. Empirical results indicate that the main
conclusions remain largely unchanged. Further, the industry dummies are all
insignificant, ruling out the possible industry effect in the association between
dividend changes and future profitability.
7. Conclusions and Remarks
This study investigates a unique dual dividend dataset to identify the association
between dividend changes and subsequent profitability. Existing finance literature
reports this issue in terms of the information content of cash dividend samples. In
contrast, the data in this study primarily consists of dual dividend firms. Specifically,
the Taiwan stock market exhibits the market weights of 5.58% and 56.94% for the
dividend payouts of cash dividends and dual dividends, respectively, from
1997-2006. Therefore, this study addresses the issue of the linkage between dividend
changes and future profitability in a more complete complexity of dividend policy,
namely, a whole spectrum of dividend payout patterns.
Moreover, this study employs a variant of the Bivariate-Ordered Probit model
to clarify the dividend signals emitted from cash dividends and stock dividends in
the dual dividend sample. Specifically, the Bivariate-Ordered Probit model is a
vehicle to screen for the firms with informative dividend signals in this empirical
analysis. The empirical results in this study generally support the hypothesis that
dividend changes link up with future profitability in the samples of cash dividends
and stock dividends; further, this linkage is most significant in the context of a dual
dividend sample. Cross-sectional results also indicate that, in the dual dividend
sample, the proportion of supporting years that support the hypothesis reaches
66.67%.
The main findings of this study remain largely unchanged with respect to
several factors: a variety of profitability measurements, a set of testing procedures,
abnormal dividend payout ratio samples, stock repurchase programs, investment
growth opportunity, business cycles, year effects, and industry characteristics.
Moreover, the main findings of this study generally agree with the balanced dividend
hypothesis of Huang et al. (2009) that optimal dividend payouts can take advantage
22/36
of future investment opportunities by restricting excessive cash dividend payouts,
and, in the other way, mitigate the agent problem by paying more cash dividends
instead of issuing more stock dividends. The balanced dividend hypothesis thus
implies a strong positive linkage between dividend changes and future profitability.
In summary, this study provides new evidence regarding the association
between dividend changes and future profitability using a unique dual dividend
sample. This new evidence may supplement the existing results of finance literature,
which are based on cash dividend samples, with a few stock dividend samples. This
study employs the balanced dividend hypothesis to interpret the positive association
between dividend changes and future profitability in the context of dual dividends.
The balanced dividend hypothesis may be an alternative to the dividend signal
hypothesis or/and retained earning hypothesis, which are frequently used in the
literature as samples of cash dividends or/and stock dividends.
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26/36
Table1
Sample distribution of firms with two consecutive years of dividend payout patterns
year
#
of
sample
Cash
Stock
Dual
No
Other
dividends
dividends
dividends
dividends
dividends
No.
%
No.
%
No.
%
No.
%
No.
%
1997
310
3
0.97
181
58.39
32
10.32
20
6.45
74
23.87
1998
357
2
0.56
150
42.02
32
8.96
22
6.16
151
42.30
1999
420
10
2.38
134
31.90
77
18.33
55
13.10
144
34.29
2000
475
16
3.37
70
14.74
103
21.68
88
18.53
198
41.68
2001
517
32
6.19
45
8.70
140
27.08
122
23.60
178
34.43
2002
578
57
9.86
24
4.15
171
29.58
147
25.43
179
30.98
2003
608
55
9.05
19
3.13
221
36.35
140
23.02
173
28.45
2004
620
65
10.48
8
1.29
244
39.35
124
20.00
179
28.88
2005
634
90
14.20
11
1.74
253
39.91
130
20.50
150
23.65
2006
646
110
17.03
6
0.93
242
37.46
141
21.83
147
22.75
total
5165
440
8.52
648
12.55
1515
29.33
989
19.15
1573
30.45
Dual dividends denote firms with both cash dividends and stock dividends in the same accounting
years. Other dividends denote firms with other dividend payout patterns in two consecutive years.
27/36
Table 2
Dividend payout patterns of two consecutive years: Dividend payout weight
Dual dividends
Cash
Stock
year
dividends dividends
Other
Cash
Stock
Total
Stock
dividends repurchase
dividends dividends dividends
1997
0.18
59.45
12.02
14.31
26.33
14.04
0.00
1998
0.24
36.08
20.84
8.38
29.22
34.46
0.00
1999
2.61
34.76
23.16
19.03
42.19
20.44
0.00
2000
1.22
33.03
19.82
18.07
37.89
23.47
4.39
2001
2.80
18.60
25.68
24.74
50.42
22.17
6.01
2002
5.06
8.16
38.75
20.57
59.32
21.07
6.39
2003
4.27
4.00
44.03
16.58
60.61
27.52
3.60
2004
5.72
0.31
52.92
17.79
70.71
16.81
6.45
2005
9.81
0.29
61.15
12.82
73.97
12.11
3.82
2006
9.74
0.27
46.76
8.45
55.21
29.10
5.68
total
5.85
11.14
41.94
15.00
56.94
21.68
4.39
Unit: %; dividend payout weight represents the ratio of dividend payouts for each individual
dividend payout pattern category (including stock repurchase) to the total market dividends
payouts. The practice of stock repurchase began in the year of 2000. Therefore, no stock
repurchase sample exists during the period 1997-1999.
28/36
year
Cash dividends
Stock dividends
Dual dividends
No.: 440
No.: 648
No.: 1515
increase decrease constant increase decrease constant increase decrease constant
1997
2
0
1
87
48
46
5
10
17
1998
0
1
1
32
88
30
2
15
15
1999
4
5
1
45
56
33
17
23
37
2000
4
9
3
21
37
12
17
50
36
2001
9
16
7
8
29
8
20
60
60
2002
29
15
13
6
13
5
39
38
94
2003
29
11
15
7
10
2
81
40
100
2004
40
19
6
3
5
0
77
73
94
2005
43
30
17
5
3
3
73
69
111
2006
62
28
20
3
2
1
74
58
110
total
222
134
84
217
291
140
405
436
674
Table 3
Sample description of dividend changes
In the dual dividend stocks, the dividend increase sample represents firms in which both cash
dividends and stock dividends increase, or one dividend increases and the other remains constant;
the dividend decrease sample represents firms in which both cash dividends and stock dividends
decrease or one dividend decreases and the other remains constant; the dividend constant sample
represents firms in which both cash dividends and stock dividends remain constant, or both change
equally in the opposite direction.
29/36
Table 4
Matrices of Variable Correlation Coefficients
Panel A: Cash Dividend Sample
Variables
Divchgt
Divchgt
1.0000
Diveqtyt-1
e
Diveqtyt-1 ROAchgt ROAt
Ln(REt)
SalesGRt M/At
Ln(MVt)
-0.0731
0.5227
0.2638
0.1005
0.1647
0.3016
0.1075
1.0000
–0.2293
0.5266
0.3555
0.0648
0.6909
0.2555
1.0000
0.1892
0.1002
0.1728
0.0496
0.0877
1.0000
0.2748
0.0219
0.5468
0.2516
1.0000
0.0788
0.2171
0.7903
1.0000
0.0065
0.0688
1.0000
0.3566
ROAchgt
e
ROAt
Ln(REt)
SalesGRt
M/At
Ln(MVt)
1.0000
Panel B: Stock Dividend Sample
variables
Divchgt
Diveqtyt-1
ROAchgt
e
ROAt
Divchgt
1.0000
e
Diveqtyt-1 ROAchgt ROAt
Ln(REt)
AGRt
Betat
Ln(At)
-0.3269
0.5705
0.1886
0.0675
0.2397
-0.1447
-0.1104
1.0000
–0.3236
0.3580
0.2924
0.4051
0.0840
–0.0460
1.0000
0.2185
0.1303
–0.1195
-0.1110
–0.0431
1.0000
0.2535
0.2317
-0.0408
–0.1248
1.0000
0.1911
0.1879
0.3115
1.0000
0.1374
0.0478
1.0000
0.4840
Ln(REt)
AGRt
Betat
Ln(At)
1.0000
Panel A: Divchgt for cash dividend changes in current period: Diveqtyt-1 for cash payout ratios in
previous period (cash dividend /book value of equity): ROAchgt for asset return changes in current
period: ROAte for expected ROA in current period, the ROA of the first quarter in the next period is
used as proxy for ROAte: Ln(REt) for the natural log of retained earnings: SalesGRt for sale growth rate
in current period: M/At for investment growth opportunity（book value of debt + market value of
equity）/ book value of total asset)；Ln(MVt) for the natural log of corporate market value in current
period. Panel B: Divchgt for stock dividend changes in current period；AGRt for asset growth rate in
current period: Betat for market risk and defined as one year systematic risk for individual stock: Ln(At)
for the natural log of total asset: other variables are defined as those in Panel A.
30/36
Table 5
The association between actual dividend changes and subsequent ROA changes by
actual observations
Cash dividend
Model 1
**
Model 2
***
Intercept
0.004
(0.042)
0.012
(0.000)
CASHDIVCHGt
0.001
(0.866)
0.010***
(0.000)
Stock dividend
Dual dividend
Model 1
Model 2
***
-0.025
(0.000)
-0.005
(0.262)
STOCKDIVCHGt
Model 2
-0.005
(0.289)
0.001
(0.890)
***
Model 1
-0.007
(0.000)
0.013***
(0.000)
-0.000
(0.962)
0.009***
(0.006)
0.007***
(0.001)
0.010***
(0.001)
ROAt
-0.388***
(0.000)
-0.387***
(0.000)
-0.286***
(0.000)
ROAt-1
0.263***
(0.001)
0.124
(0.122)
0.104*
(0.061)
Sample size
440
440
648
648
1515
1515
Adjusted R2
0.000
0.071
0.001
0.082
0.012
0.070
F value
0.03
7.63
***
1.26
14.67
***
6.16
***
22.18***
The numbers in parentheses represent P-VALUEs. The dependent variable is the ROA changes in
the next period.The explanatory variables: CASHDIVCHGt and STOCKDIVCHGt are respectively
for cash dividend changes and stock dividend changes; ROAt and ROAt-1 are respectively for current
and previous total asset returns. This study employs the generalized least-squares estimator to adjust
for the non-spherical disturbances on heterogeneity and autocorrelation of covariance matrices that
frequently appear in pooled cross-sectional data. *,**,*** respectively represent significance levels
of 10%, 5%, and 1%.
31/36
Table 6
The association between actual dividend changes and subsequent ROA changes by
dummy variables
Cash dividend
Stock dividend
Dual dividend
Model 1
Model 1
Model 2
Model 2
Model 2
***
Model 1
***
Intercept
-0.002
(0.722)
0.004
(0.396)
-0.022
(0.000)
-0.002
(0.797)
-0.012
(0.000)
0.010***
(0.001)
DIVUP
0.005
(0.317)
0.012**
(0.034)
-0.010
(0.155)
0.001
(0.924)
0.009***
(0.005)
0.012***
(0.001)
DIVDN
0.010*
(0.096)
0.005
(0.418)
0.001
(0.920)
-0.007
(0.249)
0.001
(0.687)
- 0.007**
(0.040)
ROAt
-0.332***
(0.000)
-0.420***
(0.000)
-0.207***
(0.000)
ROAt-1
0.226**
(0.012)
0.149**
(0.045)
0.034
(0.507)
Sample size
440
440
648
648
1515
1515
Adjusted R2
0.007
0.051
0.006
0.079
0.006
0.056
F value
1.41
3.66
***
1.66
11.34
***
4.09
**
22.02***
The Model 2 is specified as Eq. (1), the numbers in parentheses represent P-VALUEs. The dependent
variable is the ROA change in the next period. The explanatory variables: DIVUP(DIVDN) is the
dummy and DIVUP(DIVDN)=1, if the dividend increase (decrease), otherwise=0. ROAt and ROAt-1
are respectively for current and previous total asset returns. This study employs the generalized
least-squares estimator to adjust for the non-spherical disturbances on heterogeneity and
autocorrelation of covariance matrices that frequently appear in pooled cross-sectional data. *,**,***
respectively represent significance levels of 10%, 5%, and 1%.
32/36
Table 7
Ordered Probit Model of Expected Dividend Changes
Cash dividend
Stock
Dual dividend
dividend
Cash dividend
Stock dividend
Model 1
Model 2
Diveqtyt-1
-18.656***
(0.000)
-8.952***
(0.000)
-2.014**
(0.011)
-5.755***
(0.000)
ROAchgt
21.790***
(0.000)
15.802***
(0.000)
11.995***
(0.000)
11.013***
(0.000)
ROAt
21.791***
(0.000)
11.667***
(0.000)
11.250***
(0.000)
4.341**
(0.033)
Ln(REt)
0.322***
(0.003)
0.292***
(0.000)
0.276***
(0.000)
0.079
(0.215)
SalesGRt
0.735***
(0.005)
0.008***
(0.000)
M/At
1.344***
(0.001)
0.238***
(0.000)
Ln(MVt)
-0.235**
(0.043)
-0.261***
(0.000)
e
Model 3
AGRt
1.681***
(0.000)
0.510***
(0.000)
Betat
-0.256
(0.118)
-0.269***
(0.001)
Ln(At)
-0.391***
(0.000)
-0.105
(0.128)
Thresholds of Expected Dividend Changes
Between dividend decrease and
constant
0.647
-2.919
-0.511
-1.056
Between dividend constant and
increase
1.427
-2.109
0.007
-0.566
440
648
1515
-323.11
-489.44
-2468.27
Sample size
Log pseudo likelihood
Model 1 and 2 are the Ordered Probit Model of Eq. (2) and Eq. (3), Model 3 is the Bivariate-Ordered
Probit Model of eq. (4). The numbers in parentheses represent P-VALUEs. Model 1: Dependent
variable DIVCHGt is the dividend cash changes at time t and specified as 0, 1, and 2 corresponding
respectively to the cases of dividend decrease, constant, and dividend increase. The explanatory
variables: DIVEQTYt-1 represents the dividend payout ratio at time t-1(by dividend/book value of
e
stockholders equity); ROAchgt represents total asset changes in current period; ROAt signifies
manager’s expected ROA at time t and this study adopts the ROA in the first quarter at time t+1 as the
proxy; Ln(REt) is the natural log of the retained earnings at time t; SalesGRt is the sale growth rate at
time t; M/At is the proxy for investment growth opportunity at time t (( book value of debt + market
value of equity)/book value of total asset )；Ln(MVt) is the natural log of the market value at time t.
Model 2: Dependent variable Divchgt is the stock dividend changes in current period. Explanatory
variables: AGRt for asset growth rate in current period；Betat for market risk and defined as one-year
systematic risk for individual stock；Ln(At) for the natural log of total asset；other variables are defined
33/36
as those in Model 1. Model 3: Variables are the same as those in Model 1 and Model 2. *,**,***
respectively represent significance levels of 10%, 5%, and 1%.
Table 8
The association between expected dividend changes and subsequent ROA changes
Cash dividend
Stock dividend
Dual dividend
Model 1
Model 1
Model 1
Model 2
Intercept
0.004
(0.396)
*
DIVUP
0.012**
(0.034)
0.001
(0.924)
0.012***
(0.001)
DIVDN
0.005
(0.418)
-0.007
(0.249)
- 0.007**
(0.040)
0.007
(0.057)
-0.002
(0.797)
Model 2
-0.005
(0.302)
***
0.010
(0.001)
Model 2
0.009***
(0.002)
EXPDIVUP
0.023***
(0.000)
0.011*
(0.063)
0.016***
(0.001)
EXPDIVDN
-0.010
(0.187)
-0.015**
(0.039)
-0.019***
(0.000)
ROAt
-0.332***
(0.000)
-0.524***
(0.000)
-0.420***
(0.000)
-0.534***
(0.000)
-0.207***
(0.000)
-0.268***
(0.000)
ROAt-1
0.226**
(0.012)
0.396***
(0.000)
0.149**
(0.045)
0.248***
(0.004)
0.034
(0.507)
0.110**
(0.079)
0.060
440
440
648
648
1515
1515
Adjusted R
0.051
0.089
0.079
0.091
0.056
0.061
Fvalue
3.66***
8.14***
11.34***
12.90***
22.02***
26.04***
Sample size
2
Model 1 and Model 2 correspond to Eq. (1) and Eq. (6). The numbers in parenthesis represent
P-VALUEs. Dependent variable is ROA changes in the next period. Explanatory variable:
DIVUP(DIVDN) is the dummy and DIVUP(DIVDN)=1, if the dividend increase (decrease);
otherwise=0. EXPDIVUP (EXPDIVDN) is the dummy and EXPDIVUP (EXPDIVDN)=1 if
expected dividend increase (decrease); otherwise EXPDIVUP(EXPDIVDN)=0; ROAt and ROAt-1
are respectively as the total asset returns of current and previous period. This study employs the
generalized least-squares estimator to adjust for the non-spherical disturbances on heterogeneity
and autocorrelation of covariance matrices that frequently appear in pooled cross-sectional data.
*,**,*** respectively represent significance levels of 10%, 5%, and 1%.
34/36
Table 9
The association between dividend changes and subsequent ROA changes:
An examination of balanced dividend hypothesis
Low dividend ratio
Balanced dividend
High dividend ratio
ratio
Model 1
***
Model 2
*
0.008
(0.099)
Model 1
Model 2
Model 1
0.008
(0.119)
**
**
Intercept
0.018
(0.001)
0.009
(0.036)
0.013
(0.022)
DIVUP
0.000
(0.988)
0.021***
(0.000)
0.015**
(0.040)
DIVDN
-0.010*
(0.060)
0.002
(0.757)
-0.014**
(0.037)
Model 2
0.008
(0.170)
EXPDIVUP
0.011
(0.142)
0.021***
(0.000)
0.014**
(0.044)
EXPDIVDN
0.003
(0.631)
-0.013**
(0.022)
-0.007
(0.357)
ROAt
-0.181
(0.103)
-0.190
(0.200)
-0.269***
(0.000)
-0.403***
(0.000)
-0.228**
(0.020)
-0.255**
(0.047)
ROAt-1
-0.025
(0.820)
-0.023
(0.871)
0.050
(0.417)
0.182**
(0.026)
0.097
(0.355)
0.124
(0.355)
493
493
601
601
421
421
Adjusted R
0.064
0.063
0.095
0.102
0.057
0.045
F value
8.3***
7.5***
12.29***
15.36***
5.9***
4.59***
Sample size
2
Model 1 and Model 2 correspond to Eq. (1) and Eq. (6), respectively. The numbers in
parenthesis represent P-VALUEs. This study follows Huang et al. (2009), and classifies
companies with a cash/stock dividend ratio smaller than 1 as low cash/stock dividend ratio
sample, the ratio larger than 2.33 as high cash/stock dividend ratio sample, and others as the
balanced dividend sample. Dependent variable is ROA changes in next period. Explanatory
variables: DIVUP(DIVDN) is the dummy and DIVUP(DIVDN)=1, if dividend increase
(decrease);
otherwise=0.
EXPDIVUP(EXPDIVDN)
is
the
dummy
and
EXPDIVUP(EXPDIVDN)=1if
expected
dividend
increase
(decrease);
otherwise
EXPDIVUP(EXPDIVDN)=0; ROAt and ROAt-1 respectively represent the total asset returns in
current and previous periods. This study employs the generalized least-squares estimator to
adjust for the non-spherical disturbances on heterogeneity and autocorrelation of covariance
matrices that frequently appear in pooled cross-sectional data. *,**,*** respectively represent
significance levels of 10%, 5%, and 1%.
35/36
Table 10
Dividend changes and subsequent ROA changes: cross-sectional analysis
year
Cash dividend
Model 1
Dual dividend
Model 2
Model 1
Model 2
Panel A：dividend increase
2001
-
-
-
-
2002
-
*
***
***
2003
***
**
***
*
2004
-
***
***
***
2005
-
-
***
***
2006
-
***
*
-
Panel B：dividend decrease
2001
-
***
***
***
2002
-
*
***
***
2003
-
-
-
-
2004
-
-
-
-
2005
-
-
***
**
2006
-
-
**
**
Model 1 and Model 2, respectively, are the actual dividend change model of Eq. (1) and the
expected dividend change model of Eq. (6). This table re-examines the empirical results using
annual cross-sectional data. *,**,*** respectively represent significance levels of 10%, 5%,
and 1%.
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