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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. 2/36 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 earnings. These types of dividends account for 3.25%, 71.67%, and 25.08% of the 5/36 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. 6/36 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( 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. 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Financial Analysts Journal 62, 58-69. 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. 2/36 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. 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Financial Analysts Journal 62, 58-69. 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%. 36/36