The answer as to why firms pay dividends has focused on relaxing the M&M assumptions ... investment, rendering questionable one of M&M=s key assumptions.
Do Firms in Emerging Markets Follow Different Dividend Policies From Those in the US: Evidence From Firms in Eight Emerging Countries
October, 2001
Varouj Aivazian and Laurence Booth (University of Toronto) Sean Cleary (York University)*
Abstract We examine the dividend policy of a sample of companies from eight emerging markets, and compare them to a sample of 99 US companies. The comparison is motivated by the observation that much of dividend policy theory is implicitly based on a capital market perspective. This perspective assumes arms length financing and generates dividend policy implications from models of signalling and information asymmetries. In contrast, financial systems in emerging markets tend to be more bankoriented while firms tend to be more closely held. Nevertheless, our results indicate that emerging market firms exhibit similar dividend behaviour to firms in the US, in the sense that they are affected by profitability, the amount of debt, and the market to book ratio. However, the empirical dividend policy equations are structurally different, indicating different sensitivities to these financial variables. Additionally, these emerging market firms seem to be more affected by their asset mix, that is the proportion of long term to total assets. This seems to be due to their greater reliance on bank debt. Overall, country factors are as important in dividend policies as Booth et al (2001) found them to be in capital structure decisions. What exactly are Acountry@ factors remains to be determined.
JEL Classification Codes: G35, G32
Keywords: Dividends, information asymmetries, signalling, emerging markets, * The authors thank the Social Sciences and Humanities Research Council of Canada (SSHRC) for financial support provided for this project. We would also like to thank participants at the 1999 Annual FMA meetings and at the Queen’s University seminar series.
Abstract
We examine the dividend policy of a sample of companies from eight emerging markets, and compare them to a sample of 99 US companies. The comparison is motivated by the observation that much of dividend policy theory is implicitly based on a capital market perspective. This perspective assumes arms length financing and generates dividend policy implications from models of signalling and information asymmetries. In contrast, financial systems in emerging markets tend to be more bankoriented while firms tend to be more closely held. Nevertheless, our results indicate that emerging market firms exhibit similar dividend behaviour to firms in the US, in the sense that they are affected by profitability, the amount of debt, and the market to book ratio. However, the empirical dividend policy equations are structurally different, indicating different sensitivities to these financial variables. Additionally, these emerging market firms seem to be more affected by their asset mix, that is the proportion of long term to total assets. This seems to be due to their greater reliance on bank debt. Overall, country factors are as important in dividend policies as Booth et al (2001) found them to be in capital structure decisions. What exactly are Acountry@ factors remains to be determined.
Do Firms in Emerging Markets Follow Different Dividend Policies From Those in the US: Evidence From Firms in Eight Emerging Countries Section I:
Introduction
Miller and Modigliani (1961) (M&M), showed that under certain assumptions the payment of a cash dividend should have no impact on a firm=s share price. The firm=s free cash flow is then paid out as a residual dividend. However, there is no empirical support for the residual theory of dividends. In pathbreaking work, Lintner (1956) showed that his sample of US firms followed an adaptive process, where the dividend was set each period based on the existing dividend and a slow movement towards a target dividend. However, Lintner did not answer the question of what determines the level of the dividend, which is the focus of this paper. This is an important question, since even though Fama and French (2001) have recently documented an overall decline in dividend paying NYSE firms; about 60% still pay dividends.1
The answer as to why firms pay dividends has focused on relaxing the M&M assumptions, which inevitably brings out the institutional environment in which firms operate. Fazzari, Hubbard and Petersen (1988), for example, document that investment in the US is sensitive to cash flow constraints. As a result, a firm=s dividend decision, which directly affects its free cash flow would potentially affect its investment, rendering questionable one of M&M=s key assumptions. Fama and French (1997) have also looked at the dividend and debt decisions of US firms concluding that; "debt seems to be the residual variable in financing decisions.@ If debt, investment and dividend policies are all inter-related it points to a model of empirical dividend policy based on real and financial variables.
Higgins (1981) showed that there is a direct link between growth and financing needs: rapidly growing firms have external financing needs, since working capital needs normally exceed the incremental cash 1
Most of the decline in the proportion of dividend paying US firms is a result of increased Nasdaq and AMEX listings of technology and relatively immature firms.
1
flows from new sales. Consequently, profitable, slow growing firms will be cash rich, while rapid growth firms will be cash poor. Higgins work is important in separating out firms likely to have financing problems from those that won't. However, it begs the question of why pay out excess cash as a dividend, or conversely why not meet an external funding need through new financing?
The two key models addressing these issues are signaling and cash flow or agency models.2 M&M pointed out that dividends can have information content. This conjecture has found empirical support in the work of Watts (1973) and Asquith and Mullins (1986), with Bhattacharya (1979) developing the first formal model. The intuition is simple; with costs attached to cutting a dividend due to the transaction costs of issuing new common equity, as well as regulatory considerations, only the "good" quality firms expecting high cash flows will pay a dividend.3 The poor quality firms cannot afford to match the dividend payments, since they will be faced with high transaction costs when the cash flow does not materialize. Knowing this, investors take the firm=s dividend payment as a signal of their future free cash flows.4
Similarly, Jensen (1986) showed that there are agency costs attached to free cash flow. Essentially free cash flow can be squandered through excessive perquisite consumption, or by undertaking poor investments simply due to the available cash. Easterbrooke (1984) argues that a commitment to a high dividend policy may attenuate managerial opportunism by forcing the firm to interact with the capital market more frequently, thereby imposing market discipline on the manager. Jung et al (1996) shows that these agency costs of managerial discretion are important in corporate financing decisions. Christie and Nanda (1994) also document that stock prices actually went up after the imposition of a retained earnings tax in the US: the increased value from reducing poor investment decisions outweighed the cost of the tax. 2
Brennan (1970) has shown that taxes are also important, but tax models also tend to show that firms should not pay dividends, when they do! Poterba (1987) has pointed out that dividend policy of US firms has been remarkably insensitive to changes in US tax policy. 3
Smith (1977) showed that for small underwritten equity issues the issue costs could easily run to 10-15% of the issue. These costs then decline with issue size to the 5% level. 4
See Thakor (1989) for an excellent review.
2
Both the signaling and agency cost models assume that there is a separation of ownership and control and that financing is raised externally through capital markets. For example, in the signaling model it is assumed that but for the dividend external investors would not be aware of the firm=s future free cash flow. This argument applies to the both the shareholders as well as the bondholders who use the dividend payments as a loose proxy for credit risk.5 However, the financial systems in emerging markets are usually characterized by closely held bank-financed firms. In this case, direct communication with shareholders and regular site visits from corporate lenders, who have access to confidential information, would reduce the need to use the dividend as a signal. Similarly, the agency cost argument assumes that there is poor monitoring of management, so that high dividend payments substitute for direct communication between shareholders and managers and forces them to interact with investors. Again this argument is weaker for closely held bank-financed firms.6
The above comments highlight the importance of institutional features of the financial system and points to the advantages of studying dividend policy in different institutional environments. We chose to look at a sample of firms from eight emerging markets: India, South Korea (Korea), Jordan, Malaysia, Thailand, Turkey and Zimbabwe, where financial systems are significantly different from those in the US and compare them with a sample of 99 US firms. The choice of these eight countries was dictated by their inclusion in a relatively new data-base developed by the World Bank.7
Section II: Some Key Institutional Data
Some key institutional features for the nine countries are developed in Tables 1-3. The objective is to provide a broad classification of their financial systems relative to the US, as background to judge their dividend policies. Table 1 has some aggregate corporate financial data, along with some broad 5
Investment criteria for many institutions, for example insurance companies, require dividend payments. Hence the dividend payments signal the credit quality of the firm's debt as well as the firm's equity value. 6
Rajan (1992) and Diamond (1991) have both looked at the implications of arm=s length versus non-arm=s length
(e.g., bank) financing and how this affects the firm=s financial decisions. 7 The original data-base included firms from 10 emerging countries; two countries, Brazil and Mexico, were dropped since there is no stock market data.
3
macroeconomic data, to assess the importance of the growth rates emphasized by Higgins. This allows a broad analysis of the type of financing problems faced by typical firms in these emerging market countries. Table 2 then looks at the state of development of the financial systems in all nine countries. This allows an analysis of the type of financing that is available, whether it is predominantly arms length or bank financing. Table 3 then adds some qualitative data on governance and ownership structures to indicate the types of agency problems that might exist in these countries as well as some basic tax data.
For each country Table 1 gives the average real and nominal GDP growth rates as well as the average inflation rate for the period 1981-90. Note that except for Jordan (at 1.37) real economic growth rates between 1981-1990 for these countries were all well above the US average of 2.73%, ranging from a low of about twice that of the US in the case of Turkey (5.15%) to a high of over three times for South Korea at 9.85%. Further the average inflation rates were generally above that in the US, with only Malaysia and Thailand lower than in the US.
The reason why aggregate growth rates are important is that economic growth, from the GNP identity, drives aggregate expenditure. Assuming that the firms in the sample are representative of economic activity in each country means that companies in high growth economies will be faced with high sales growth rates and the financial constraints discussed by Higgins.8 How does the sales growth affect firms? Gordon (1962) showed that each firm=s sustainable growth rate can be approximated as the product of the firm=s return on equity and its retention rate (one minus the dividend payout). If firms grow faster than this sustainable growth rate, their financial policies have to change, or they have to raise external equity.
For our sample of firms, the sustainable growth rate is below the nominal GDP growth rate for the median firm in every emerging market country except Pakistan, where the median firm retained 100% of earnings. In contrast, in the US the median firm's sustainable growth rate of 8.97% was above the 8
The data base-contains the biggest firms in each country. The primary reason for a difference between GDP growth rates and corporate growth rates would be differential growth rates between public and private firms.
4
nominal GDP growth rate of 7.60%. For seven of these eight emerging market countries there seem to be growth pressures on the median firm. This implies that these companies have greater external financing needs than equivalent US firms. The next question is how developed are the capital markets in these countries in providing this financing?
Table 2 provides some data on the state of capital markets in these eight countries. The aggregate stock market value is interesting, but needs to be deflated relative to economic activity. The market capitalization to GDP ratio gives an idea of how much economic activity is traded in the capital market. For the US the average for the period 1986-1989 was 56%.9 This is well above that of any country except Malaysia. For five of these countries the equity markets are relatively poorly developed with less than 20% of economic activity valued in the stock market. Although equity markets seem to have developed in all markets, except Jordan, the only pronounced changes have been in Korea and Malaysia.
Having the economic activity Ain@ the stock market is valuable, since it indicates that the public markets can be used to raise new financing. However, this is of little use if the markets lack liquidity. Table 2 also provides annual turnover data relative to market capitalization. For the US, annual stock market trading value increased from 38% to 68% of total market value. This is a similar level to India, with Korea and Thailand having higher turnover rates. The other countries have turnover ratios below 20% (with two below 10%). This indicates that both Thailand and India have a relatively small amount of economic activity listed in the stock market, which is actively traded, while Korea by the end of the period has a relatively rich equity market that is closest to the US. For the other countries, there is a combination of illiquid poorly developed equity markets, which indicates that the costs of raising new equity capital are probably high.
9
As a broad rule of thumb aggregate net income is about 10% of GDP, implying that if all firms are traded at a market capitalization to GDP of 100% there will be a price earnings ratio of 10. A market value to GDP ratio of less than 1.0 implies either a lower PE multiple or less economic activity being available in the stock market.
5
Table 2 also provides liquid liabilities to GDP ratios. This data is taken from King and Levine (1993) and is a commonly used measure of the development of the banking system, since short term bank liabilities are simply checking and equivalent accounts. For the US the average of 64% was exceeded by both Malaysia and Jordan, indicating relatively well developed bank markets in these countries. In contrast, the other six emerging market economies all seem to have less developed bank markets.
One reason why financial markets are frequently under-developed in emerging markets is the absence of the institutional infrastructure necessary to enforce the contractual rights of security holders. In Table 3 are some qualitative factors drawn from a variety of sources that indicate the risks attached to making equity investments in these markets. Accounting standards, for example, were judged to be adequate in six countries and good for Korea and Malaysia. Similarly, both Korea and Malaysia have good investor protection, whereas in the other six they are judged adequate. Good accounting standards and investor protection rules would seem to be pre-requisite to well functioning equity markets and confirm Korea and Malaysia=s position as Aclosest to the US.@
Having the accounting and legal system in place, however, is only part of the story: having a good governance structure to enforce contractual rights is also critical for the development of the financial system. According to the measures in Table 3 the countries closest to the US are Zimbabwe and Malaysia, for the others the evidence is mixed. At one extreme is Turkey with better creditor protection than the US and average governance structures, but very poor enforcement of stockholder rights. In contrast, Pakistan and Thailand score well on shareholder and creditor rights, but very poorly (particularly Thailand) on governance.
Table 3 also includes ownership concentration measures reported in La Porta et al (1998) for firms in emerging markets as well as the US. The estimate is the average ownership share of the three largest shareholders for the ten largest publicly held firms in each country. This measure indicates that ownership is more concentrated in these emerging markets than it is in the US. In the US the three
6
largest shareholders owned an average of 20%, while in India the number is 40%, Malaysia 54%, Thailand 47%, Zimbabwe 55%, Pakistan 37% and Turkey 59%. The only country that seems to have similar ownership patterns to the US is Korea.
The importance of bank and creditor rights relative to stockholder rights follows the bank versus market organizational issue recently examined by a number of authors. We would classify our eight countries as follows:
Financial Orientation
Developed
Bank
Market
Jordan
South Korea
Financial Development
Malaysia Undeveloped
Pakistan, Zimbabwe,
Thailand
India, Turkey
This is the same classification as Demirguc-Kunt and Levine (1999), except that we classify Turkey as an under developed bank and Thailand as an under developed market orientation.
Jordan, Pakistan, Zimbabwe, and India are classified as bank oriented, since their equity markets were poorly developed during this period. Similarly, Korea and Malaysia seem to be market oriented; an observation supported by the stronger development of accounting and investor protection regulations in those countries. According to the market development indicators alone, Turkey would rank as undeveloped on any criteria. However, the very strong enforcement of creditor rights would seem to be consistent with an under-developed bank orientation, rather than the Dimirguc-Kunt and Levine classification of Turkey as under-developed market orientation. Thailand is classified as under-
7
developed market, since even though it scores quite poorly on equity market indicators, it has strong enforcement of shareholder rights.
The data indicates that we would expect firms from Korea and Malaysia (developed market) to follow dividend policies more closely aligned with those of firms in the US; although, their higher growth rates would indicate lower overall dividend levels. In contrast, Jordanian firms and those in Pakistan, Zimbabwe, India and Turkey we would expect to pay even lower dividends. This is due to the greater bank orientation in these countries and thus the limited role of dividends as either a signalling or a precommitment device.
Table 3 also has some basic tax rate data for these countries. In six out of the eight countries the corporate tax rate is less than the highest personal tax rate. Further the ratio of the after tax dividend income to after tax capital gains income, assuming accrual taxation, is less than or equal to one for every country (including the US). The exception is Thailand. When the deferral advantage to capital gains is factored in, it would seem that in most of these countries, even possibly in Thailand, there are similar incentives as in the US to avoid paying dividends for tax reasons.10 Consequently, we would not expect to see tax distortions playing a significant role in differentiating the dividend policies of these emerging market firms from their US counterparts.
These tax and institutional factors indicate that there are high costs attached to paying dividends for firms in all eight emerging market countries, relative to the US. This is due to both the extra taxes imposed on investors (except in Thailand) as well as the greater difficulty in replacing equity lost through dividend payments with new issues. These difficulties appear to be most acute in the bank-oriented countries and least severe for firms in Malaysia and Korea, particularly towards the end of the period. For these reasons, we would expect to see dividend policies in the Amarket@ oriented financial systems
10
Note that there is a big difference between examining tax rates and actual taxes paid, which depends on inclusion
rules and the integrity of the tax system. Thailand scores poorly on most corruption indices, for example.
8
of Korea and Malaysia to be “most like” that of US firms. Conversely, firms in the bank centred systems of Turkey, Zimbabwe, Pakistan and India to be “least like” the US, with Jordan and Thailand in a gray zone. We will use these “institutional groupings” along with the country identifiers to test the importance of dividend policy.
Section III: The World Bank Data Base
The World Bank (International Finance Corporation or IFC) data-base is described in Glen et al (1994) and Booth et al (2001). The IFC deliberately chose large publicly traded firms with the objective of creating a sample of firms with Ahigh quality@ financial statements from the following countries: South Korea, Pakistan, Jordan, India, Zimbabwe, Malaysia, Thailand and Turkey. In each case, the firms in the data-base are the largest firms listed on the local stock exchange. This is important since in some countries, such as Korea for example, the dividend tax rate is lower for listed companies, while in India and Turkey the corporate tax rate is lower for listed companies.
However, for some countries to create a viable sample data from a larger proportion of listed companies had to be collected. Table 4 gives the basic source data and indicates for example that whereas the Indian sample consists of 99 firms out of the 6,200 listed companies in 1990, for Zimbabwe it consists of 48 out of the 57. As is to be expected, although the Zimbabwe sample is about half the size of the Indian sample, there are greater problems with the quality of the data. The data itself consists largely of abbreviated balance sheet and income statements with limited cash flow and market data. The data was collected by the IFC over various periods from 1980-1990 for companies in each country. The great advantage of the data base is that it covers a large number of years (varying according to country) and has the largest coverage of companies for these countries available in any data set. The cost of this coverage is that the data is neither uniform across countries or time as well as being limited in terms of non-financial statement data.11 11
There are no SIC codes or significant industry data. For some there is a brief description, for others nothing except guessing from the firm's name, which is sometimes not in English. It is known that regulated industries in the US
9
Table 5 provides some basic data to assess the financial health of these firms. Since all the values except for the log size variable are ratios, they are sometimes skewed because of division by small numbers.To compensate for this we do two things: first following Booth et al (2001) for each variable in each country we remove the tails of the distribution by removing each observation that is more than 3 standard deviations from the mean; second in the descriptive statistics we report the median as well as the mean, along with the standard deviation.
The key ratios were in part dictated by the availability of data, but there are three Aoperating@ measures, three debt measures and two summary measures. The first of the three operating measures is the tangibility of the firm=s assets defined as the total assets minus current assets divided by total assets. This ratio is designed to measure the proportion of long-term, Ahard@ assets in the firms=s asset structure. The firm=s business risk is measured by the standard deviation of its return on investment, and the scale of the firm=s operations is measured by the natural logarithm of sales. Financial policy is measured by the debt ratio, defined as total liabilities minus stockholder's equity divided by total liabilities, the times interest earned ratio (coverage) and the current ratio. The two summary measures are the firm=s return on equity and the firm=s market to book ratio defined as the average common stock price divided by the book value per share.
The median asset tangibility for the US firms was 31%, the variability of their ROI was 3.0% and the natural logarithm of sales was 7.0%. The median debt ratio was 41%. The median interest coverage ratio was 5.85. The median current ratio was 2.23 and the median return on equity 13.0% with a market to book ratio of 1.53. Overall, these US firms can be described as reasonably high quality, profitable firms.
The median return on equity varied from 7% in Malaysia and 8% in South Korea and Jordan, up to have definite dividend policies, but there seem to be few regulated industries in the sample, since they tend to be state owned enterprises.
10
19% in Pakistan and 22% in Turkey. 12 The median market to book ratio ranged from discounts at 0.58 in South Korea and 0.39 in Zimbabwe, up to 1.85 and 1.82 in Malaysia and Thailand. In comparison, the US firms have higher market values for about the same level of profitability. Broadly defined median debt ratios varied from 42% in Malaysia up to 75% in the case of South Korea with coverage ratios (times interest earned) similarly as low as 1.48 for South Korea and 1.16 for Pakistan. The median current ratio, where available, has very little variation at just over one. In contrast, for the US firms the median debt ratio was 41%, the interest coverage ratio 5.85 and the current ratio 2.23. This indicates that except for firms from Zimbabwe and Jordan, these firms in general are more highly indebted than in the US, and judging from the current ratios much of this debt is short term. Somewhat surprisingly, median tangibility ratios were higher on average for firms in these emerging markets with median values ranging from 0.36 in Turkey up to 0.56 for Malaysian firms, as compared to 0.31 for the US firms. The business risk variable varied from 3% for Korea and Thailand to 7% for Jordan.
For our firms from emerging markets, the data in Table 5 indicates that the financial health of these firms is poorer than the sample of US firms. Fazzari et al.(1988) argued that financially constrained US firms are less likely to maintain high dividends. In general, it would seem that these firms were more financially constrained than the sample of US firms and, all else constant, less likely to pay dividends. This observation is consistent with the data in Tables 1- 3 where it is apparent that these firms from emerging markets are in relatively high growth economies with relatively undeveloped capital markets. When firms grow faster than their sustainable growth rate, we expect deterioration in their financial health unless they raise new equity. This is what we see in Table 5. Generally these firms in emerging markets have relatively more (short term) debt and poorer coverage ratios, indicating that they have limited debt capacity and have been unable or unwilling to raise additional equity.
Table 6 provides critical information for different definitions of dividend policy. The standard ratios for
12
GAAP in these countries follow two different approaches with Turkey and South Korea following a GermanJapanese strict historic cost accounting, approach; the others have policies similar to the US.
11
analyzing dividend policy are the dividend yield, which in this case is the annual dividend divided by the average of the year=s high and low stock price, and the dividend payout, which is the ratio of the dividend paid to the earnings per share.13 In addition, we also deflate aggregate dividends by dividing by both total assets and stockholders= equity. These measures are calculated to avoid @pricing@ problems that may exist with the dividend yield and the instability of the payout ratio when earnings are low.
For our Acontrol@ sample of 99 US firms over the period 1981-1990 the average dividend payout was 33% with a median payout of 31%. Recall from Table 5, that the average and median debt ratios were both 41%. And the average and median return on equity were 12% and 13% respectively.
For our eight developing countries the median dividend payout ratios are similar to those of the US, averaging 36% across all eight countries. The significant outliers are Turkey with a median payout of 62% and Pakistan with a median payout of 0%. The observation for Turkey is attributable to the fact that firms are constrained to provide dividends equal to the larger of 50 percent of earnings or 20 percent of paid-in-capital, up to 75 percent of earnings. This obviously tends to increase the payout ratio and strengthen the association between dividend policy and profitability. In contrast, the large number of non-dividend paying Pakistani firms points to the usefulness of looking at dividend policy for the subset of dividend paying firms. In between the extremes, for Korea, Malaysia, Zimbabwe, Jordan and Thailand the median dividend payout ratios are higher than for the US, while for India it is slightly lower.
Except for Turkey and Zimbabwe, median dividend yields are very similar to those in the US. For the former this is due to high payouts, whereas for the latter it is due to low market values as indicated by the low median market to book value of 0.39 in Table 5. The only country for which the average dividend yield seems to be distorted by outliers is Korea, where the equity market as a whole was
13
The only available data is annual.
12
moribund at the beginning of our period and then developed dramatically throughout the period. The same general picture emerges for dividends divided by total assets and by stockholders= equity; again Turkish firms seem to be the only outliers. Overall, the dividend data would indicate that dividend policy is of importance for these firms in emerging markets just as it is for firms in the US.
One question that arises from the data in Table 6 is whether there are systematic differences across countries. Table 7 allows us to look at this by comparing each measure of dividend policy for each country against successively: the US; the whole sample minus that country, and the whole sample minus that country and the US. For example, for Korea the first observation tests whether the average payout ratio in Korea of 42% is significantly different from that of the US sample of 33%. The t statistic of the difference in means of 3.3 indicates that this is a significant difference. Every difference that is significant at the 5% level is Astarred.@
The immediate reaction to the data in Table 7 is that most of the differences are significant. For example, for Korea both the payout rate and the dividend yield are significantly higher than for the US sample, while aggregate dividends deflated by either total assets or the book value of equity are lower. This would indicate that the Korean firms in this sample paid out lower levels of dividends, relative to their book equity and total assets than the control sample of US firms, and yet this was a higher proportion of both their earnings and stock market value. Essentially this would indicate that Korean firms were simply not as profitable as those in the US, which was recognized by the stock market.
Going down the AUS column@ indicates that these measures of dividend policy are significantly different from those in the US for every country except India. This would indicate that US firms are different from these firms from emerging markets. However, a similar message emerges when comparing each country in turn to the overall sample both with and without the US. For example, the values for Korea are significantly different from the sample averages obtained by including all other firms from emerging markets, indicating that dividend policy for Korean firms differs significantly both from that of US firms,
13
as well as from firms in other emerging markets. A similar result emerges in pairwise comparisons. Part of this Asignificance@ is due to the relatively large sample size, but this also indicates that there is significant heterogeneity both within the sample of emerging market firms as well as between them and the sample of US firms14.
The four dividend variables were reported since they are standard measures of dividend policy. However, in the future we will focus on aggregate dividends deflated by total assets, which we will refer to generically as Adividend policy.@ There are several reasons for focusing on this measure. First, the dividend payout rate is highly unstable and non-normal as earnings get close to zero, consequently the payout rate is not useful as a dependent variable in cross sectional regression analysis. Second, the dividend yield reflects pricing effects that are beyond the control of management. This is particularly evident in some countries, for example Zimbabwe, where political risk concerns drove the market value to a deep discount to book value, driving the dividend yield up. Third, deflating by the book value of equity makes the estimates more sensitive to outliers than dividends deflated by total assets. Finally, dividends deflated by earnings or the book value of equity are both more sensitive to accounting distortions than deflating by total assets..
What is interesting about this measure of dividend policy is that for six out of the eight countries the average dividend payments is higher for these firms in emerging markets than it is for the sample of US firms.15 The only exceptions are Korea, which as we noted before is “most like the US” and pays out less, and India. Why these emerging market firms tend to have higher dividend payments, than their US counterparts, while facing greater external growth pressures is a puzzle. We have already shown that firms in emerging markets have poorer access to funds, particularly equity, while their overall financial health is much poorer. We would have expected that their close reliance on short term bank debt 14
Grouping the firms into “most like the US,” “least like the US,” and “other” produced similar results in the sense that the dividend policy measures for the “most like the US” group were as different from the US as those for the “least like the US”group . 15 This also holds for dividends deflated by the book value of equity, except for Malaysia, which again was Amostlike A the US in terms of a developed market orientation..
14
would have reduced both monitoring and signalling problems leading to lower dividend payments. One potential answer lies in the different characteristics of these firms; perhaps their dividend policies simply reflect different firm characteristics?
Section IV:
Dividend Hypotheses
Dividend signaling models explain why dividends are more stable than earnings: with a temporary, cyclical, earnings downturn a dividend cut misleadingly indicates that the earnings decline is permanent. However, maintaining the dividend comes at a cost since the equity paid out as a dividend has to be replaced. It follows that a firm=s dividend policy should be inversely related to its business risk.16 The IFC data-base does not provide the data to estimate betas, while the available cash flow data is inadequate. Consequently, we use as a business risk proxy the standard deviation of the firm=s return on investment (ROI) over the complete time period. Unfortunately, this means that there is only one business risk proxy for each firm, rather than an estimate that varies year by year.
We have already noted that the work of Fama and French (1997) emphasizes the role of debt as a residual, rather than dividend policy, which implies that financial constraints are important. We expect that more long- term debt is used as the tangibility of the firm=s assets increases and there is more collateral.17 Therefore, we use the tangibility of a firm=s assets, along with the firm=s debt ratio, as an empirical proxy for the existence of long-term debt. The tangibility of a firm=s assets is proxied by total assets minus current assets as a percentage of total assets. We hypothesize that firms with relatively less debt and more tangible assets have greater financial slack and are more able to pay and maintain their dividends. Conversely highly indebted firms with mostly current assets are more financially constrained and will be less inclined to make significant dividend payments. 16
Similar reasoning by Rozeff (1982) led him to test the relationship between dividend payouts and various measures of risk, including cash flow uncertainty and beta. 17
This is especially true in developing countries where transaction costs of enforcing (unsecured) long-term financial contracts tend to be high.
15
The nature of a firms=s assets and its access to financial markets is also critical for dividend policy. The penalty (as for example in Rozeff=s work) is the extra transactions costs of accessing financial markets. This costly contracting approach means that these costs are higher for smaller firms. For this reason we measure financial market access by the natural logarithm of the firm=s sales level. Larger firms with better market access should be able to pay higher dividends. We therefore expect to see a positive relationship between size and dividend payments.18
Finally, the importance of the investment opportunity set is measured by the market to book ratio, which serves as a proxy for the present value of growth options. Plausibly higher growth opportunities should mean lower dividend payments as greater investments are made to exploit these opportunities and it is more difficult to raise financing from this component of market value. However, high market values could also result for Acash cows@ that have very high present value from existing opportunities with few growth opportunities. To control for this, the return on equity is used to measure the present value from existing opportunities.
We expect that high growth options are reflected in lower dividends. This is implied by both the costly contracting hypothesis and is consistent with the signaling hypothesis, since a firm is unlikely to signal strong cash flows anticipated far in the future by the payment of significant current dividends. We expect these firms to have low current returns on equity, but high market to book ratios. Conversely, firms with a low proportion of growth opportunities, but high short-term cash flows will maximize their dividend payments to signal the high quality of their current earnings. We would expect these firms to have high returns on equity and relatively low market to book ratios
The IFC data represents an unbalanced panel: there are varying numbers of firms in each country with the numbers varying across both time and available ratios. For example, although there are a maximum
18
The size variable is specific to each country being estimated as the natural logarithm of (local currency) sales.
16
of 890 firm-year observations for Pakistan, there are only 196 which have market value data allowing the calculation of market to book ratios. For Zimbabwe there are only 54 firm-year observations when the tangibility ratio is included. To make maximum use of the data, panel data techniques are used to pool both cross sectional and times series data. Consequently, all observations are in terms of firm-year observations.
The empirical model is expressed as,
D n i, t = α + ∑ j = 1β X +ε i j i, j ,t i, t A i, t where Xi,j,t is the j th explanatory variable for the ith firm at time t, ,i,t is the random error term for firm i at time t, Di,t/Ai,t is one of the four dividend ratios subscripted for the ith firm at time t and " is the intercept. Note that the coefficients on the independent variables for each country are assumed to be the same, but the intercept can either be constant (" i=" ), or can vary across firms.
This empirical dividend policy model is estimated in three different ways. First, it is estimated on each individual country data set. The results can then be scanned to see whether the models are broadly consistent or whether there are differences between each country and the US control sample. However, a better way of analyzing differences across these emerging market firms and the US is to run a pooled regression model with the US sample. Consequently, the second estimation approach includes a pooled US-country sample with a country dummy to estimate the differences in the intercept, as well as country dummies for each independent variable to test for interactive effects. Finally, the model is estimated using the complete pooled sample with four different sets of independent variables. First, we use the independent financial variables. Second, we use a simple pooling with only country dummies. Third, we use the complete model. Finally, we differentiate between the emerging market countries based on our previous comparisons of "most like the US," "least like the US," and other.
17
Econometrically, the simplest model to estimate is the pooled ordinary least squares model, estmated over all firm-year observations. This is parsimonious in estimation, since only one set of coefficients needs to be estimated. However, it forces equal coefficients for all firms across all points in time for all countries with a single intercept. With an unbalanced panel, this assumption is difficult to justify. Consequently, we also estimate the fixed effects model. We do this indirectly by using individual year dummies and by de-meaning each observation using firm averages.19 This is equivalent to the standard individual dummy variable model, where the firm specific dummy variable capture the effect of omitted variables. Both models offer advantages, the fixed effects model crudely accounts for omitted variables, yet as Hsiao (1986) points out, in the presence of measurement error it can produce more biased estimators than simple pooling. The reason for this is that fixed effects models essentially estimate deviations from individual means, which can then be biased (and are always magnified) by measurement error. Although fixed effect models appear to be more general, they are sometimes unreliable. Consequently, we report the results from both models.
Finally, we estimate the models both with and without the market to book ratio, since in some countries the absence of market values severely limits sample size.
Section V:
Empirical results
Table 8 provides the pooled time series cross sectional estimates for each country. For the US control sample, the overall explanatory power is good for a cross-sectional model with an adjusted R square of 30.0%. The results provide some confirmation to our prior theories. The strong results are that the more debt the lower the dividend, the higher the ROE the higher the dividend and the larger the market to book the higher the dividend. This supports the importance of the firm=s opportunity set: mature high ROE firms with debt capacity (lower debt ratios) have higher dividends. Unfortunately, we expected that once the ROE controlled for current profitability, the influence of the market to book ratio would
19
The business risk variable is not demeaned, since it is a constant for each firm.
18
be negative, indicating the reluctance to pay dividends from growth opportunities. However, the marginal impact of the market to book ratio is positive. There is weak support for the idea that larger firms with more tangible assets pay higher dividends, but the coefficients on the business risk proxy are generally not significant. When the market to book ratio is dropped, the impact of debt and the ROE is even stronger, while the other three variables remain insignificant.
The US results clearly demonstrate the impact of profitability and financial slack on dividend policy. Profitable firms with low debt that have relatively high market values seem to pay out larger amounts of dividends. This is consistent with Higgins=s sustainable growth model and the absence of financial constraints for these firms, leading them to pay out surplus funds. The other variables related to size, the nature of the firms assets and the business risk proxy are not significant. A viable empirical dividend policy equation for the US firms thus includes the ROE, debt ratio and market to book ratio. It is interesting to see whether this empirical dividend policy equation or the full model is supported for the emerging market firms.
In comparing the US results with those for the eight emerging markets, we can first look at the adjusted R square, which seems reasonable for most countries. For Pakistan and India once the market to book ratio is removed the explanatory power drops enormously, even though in the case of Pakistan this causes a huge increase in the sample size. For the individual variables, the debt ratio shows the same significant impact in every country: the bigger the debt ratio the less the dividend. The market to book ratio also has a positive sign for every country, although for Turkey and Pakistan, the limited sample size contributes to insignificant coefficients. Finally, for each country, the return on equity also has a positive influence; the only qualification is the result for the non-market to book constrained Pakistani sample.
For the other variables, as in the US case, the message is mixed. The only difference is that unlike the US firms, it seems that firms with more tangible assets tend to have lower dividends. For six of the
19
countries this is significant; only for Thailand and Turkey is the relationship either insignificant or positive. One possible explanation for this is that the more tangible the assets (ie., long-term) the fewer the short-term assets, like inventory and receivables. As a result, there would be fewer short-term assets for banks to lend against.20 In more primitive financial systems, where the main source of debt is short-term bank financing, this may constrain the firms= borrowing levels and increase their financial constraints. On the other hand, neither the size nor the business risk proxies have consistent signs; while they may be important in one country, their importance is the opposite or insignificant in another.
Overall, these results mirror those for the US in that debt, the market to book ratio and the return on equity all affect dividend policy. The main difference is that the tangibility of a firm's assets seems to be more important in these emerging markets than it is for US firms. However, what is interesting about the results in Table 8 is that if we inter-change the US equation with that for any of the other countries, apart from the role of the firm=s asset mix, the discussion would largely be the same.
Table 9 repeats the analysis while allowing for firm specific effects..21 Once firm specific markers are added it becomes more difficult to pick up the marginal impact of the independent variables. However, for the US the results are substantially the same as before. Highly indebted firms with low market to book ratios have low dividends with the effect of the size and business risk variables largely indeterminate as before. The only changes are that the tangibility variable becomes marginally positive, while the return on equity ceases to be significant, having no explanatory power (and the “wrong” sign) when the market to book ratio is included and the “right sign” (with low significance) when it is excluded.
20
Note that in most countries banks do not lend against long-term assets, except through mortgages, which are often offered by specialized non-bank institutions. Formula lending by banks are usually based on variants of 100% of cash and marketable securities, 80% of receivables and 50% of inventory. 21 The results for positive dividend payment observations only are substantially the same, since most of the firms do pay dividends.
20
The results for the emerging market firms are also similar to the simple pooling results with some notable exceptions. While high debt ratios and low market to book ratios continue to be associated with low dividends, the sign on the debt ratio reverses sign for Zimbabwe and Malaysia, while for Pakistan and India the sign on the market to book ratio turns negative or is insignificant. In contrast to the US results, the sign on the ROE continues to be positive, except for the small number of firms from Zimbabwe and Turkey, where the coefficient on the ROE is now insignificant and Pakistan, where in the restricted sample the coefficient is now significantly negative. Finally, the significantly negative relationship between dividend policy and the tangibility of assets remains, except in Pakistan, Thailand and Turkey, where the coefficents are insignificant or mixed..
The addition of firm specific effects makes it more difficult to determine the influence of the independent variables, since the values for the financial variables are not scattered randomly across the sample of companies. However, what comes through quite strongly is the interaction between debt and dividend policy. In practically every country, with every estimation method, more debt means lower dividends. Moreover, it also seems that higher profitability (ROE) and market values also imply higher dividend payments, while the higher the proportion of short term debt (less tangibility), the higher the dividends for emerging market firms. Together it seems that there are some common general factors that influence dividend policy in these emerging markets in a similar way to firms in the US. However, this does not mean to say that the effects are of the same order of magnitude.
One way to measure whether the effects are of a similar order of magnitude is through a pairwise regression, where firms from multiple countries are combined. For example, Korean firms can be added to the US firms and the following regression run D i, t = A i, t
n n + ∑ j = 1β X + ∑ j = 1γ X D+ D+ ε i j i, j ,t j i, j, t i ,t
21
This is identical to the previous regression except that all the Korean firms are identified with a dummy variable set to 1 (D) and the coefficient (gamma) then measures the significance of the interactive term that indicates whether each independent variable has a different impact depending on whether the firm is Korean or from the US. If the empirical dividend policy is identical in each country, these interactive terms will all be insignificant.
Table 10 reports the results a similar manner to Table 7, where each country is compared to the US, and then to the whole sample, excluding itself, both with and without the US firms. This is similar to the analysis of the different measures of dividend policy. For example, for Korean firms there is a significantly different reaction to size, tangibility, ROE and the market to book ratio, even after the Korean firms have been separately identified as Korean (through the Korean dummy variable). This indicates that the marginal impact of profitability, for example, on Korean firms’ dividend policy is more severe. That is, profitability as measured by the ROE tends to increase dividend payments for both Korean and US firms, but it tends to increase dividend payments by Korean firms significantly more. If we scan down the column it seems that profitablity has more of an impact on dividend payments for firms in emerging markets than the US for all countries except Jordan, although for some the difference is not significant.22
If we look at the impact of the other variables we get similar results. Increased debt reduces dividend payments for these emerging market firms, and except for firms in Korea and Jordan the impact of the increased debt is significantly more pronounced than in the US. Similarly as the asset mix moves more towards long term tangible assets, the dividend payments for the emerging market firms are reduced significantly compared with the sample of US firms, except for firms from Thailand and Jordan. For the other values the evidence is mixed. However, although it seems that firms in these emerging markets
22
This would indicate that in a standard Lintner type analysis the coefficient of the current dividend on current earnings would be higher for these emerging market firms than for the similar US firms. A separate paper analyzing the Lintner model confirms this implication.
22
respond to the same factors as firms in the US, their sensitivity to these factors seems to be greater indicating greater financial constraints.
Are these firms from emerging markets closer to each other than they are to firms in the US? One way to examine this is to look at the number of significantly different coefficients. For example, for the Korean firms there are four coefficients that are significantly different from the sample of US firms. However, in the second to last column is the test to see whether the coefficients are significantly different from all the other firms from emerging markets. In this case, three of the coefficients are significantly different. This is shown as 4-3 in the final column. If we scan down this last column, we see that in all cases, except Malaysia and Pakistan, these emerging market firms seem to have more in common with each other than the sample of US firms. However, again there is a great deal of heterogeneity across all the countries.23
Overall the empirical dividend policy has a basic message that debt, profitability and market to book ratios affect most firms, and that firms in emerging markets are also affected by their asset mix, probably through their use of short term debt. However, although these are relatively common effects, there is evidence that the responsiveness of dividend policy to these factors differs across these emerging market firms, although they seem to have more in common with themselves than the US firms. The final questions are how much is due to country or institutional factors and how similar are the “most like the US” countries to the US?
Following Booth et al’s (2001) analysis of capital structure we can consider the null hypothesis that all differences in dividend policy are due to country factors. We can do this by running a simple pooled regression, where dividend policy is run against a set of country dummies. In this case the US is the reference point, so the coefficients on the dummy variables measure the significance of dividend policy differences relative to the US. These results are in the first column of Table 11. Note that the Adjusted 23
The significantly different variables vary from country to country. This is also evident in “pairwise” comparisons not reported here.
23
R square of the regression is 18.0% and all the dummies are significant except that on India. Clearly, this supports our earlier analysis in Table 7 that there are significant differences across these countries in terms of their dividend policies.
The second column in Table 11 gives the simple empirical dividend policy model with no country dummies. This model is clearly “wrong,” since by the data in Table 10 we have already shown that the coefficients are significantly different in some of these countries, while this model forces them all to be the same. However, it is a measure of the effectiveness of the financial variables alone in understanding dividend policy. In this case the adjusted R square is 13.5%. This is somewhat discouraging, but not surprising, given that we have already shown that there is significant heterogeneity across these countries. Clearly, country factors are at least as important as the independent variables used to examine dividend policy in these countries, and much needs to be done to determine what exactly constitutes these country factors.
However, does this mean that financial theory is of no aid to understanding dividend policy in these countries? The answer to this is clearly no. The third column gives the expanded model that includes the six financial variables and the country dummies. Similar to Booth et al there is considerable incremental explanatory power in the additional financial variables. First, in terms of the independent variables we get the same general results: increased ROE and market to book ratios tend to be associated with increased dividend payments, whereas increased debt and the tangibility of assets tend to be associated with decreased debt. Despite the increased sample size, the size and business risk proxies continue to be insignificant. Second, all of the dummy variables continue to be significant. However, the signs on the Korean and Indian dummy variables are now positive and significant, indicating that after taking into account firm specific factors, like profitability etc, firms from these emerging markets all pay higher dividends than their US counterparts. The fact that these firms from emerging markets pay higher dividends in the face of more severe financing constraints than the US control sample remains a puzzle.
24
Finally we can look at the last column in Table 11. In this case, we have used our taxonomy of financial systems to categorize the eight emerging market countries in comparison to the US. Several conclusions are apparent. First the adjusted R square declines relative to the individual country dummies indicating that we are loosing information with this coarser grouping. Second, the sign on the significant independent variables remains much the same, so that the market to book, ROE and tangibility variables are quite robust. Finally, the group dummies are significant showing some homogeneity in our groupings, particularly with the “least like the US” having the largest sign on the dummy variable, indicating the biggest difference with the US.24 However, they still have larger dividends than the US even after the independent variables control for differences in profitability and debt.
Section VI:
Conclusions
Our empirical results offer several conclusions:
1)
In almost all cases, profitability affects dividend payments: high ROE tends to mean high dividend payments. This provides strong support for the residual cash flow theory of dividends.
2)
Almost universally high debt ratios mean low dividend payments. The central message is that financial constraints seem to affect dividend policy and neither is a reidual.
3)
The market to book ratio affects dividend payments. A higher market to book ratio means a higher level of dividend payments. Clearly, the expectation of future growth opportunities is important in dividend policy, but contrary to expectations it tends to lead to increased dividend payments.
4)
For emerging market firms we find that the greater the proportion of long term assets, (tangibility variable) the smaller the dividend payments. This is probably due to the
24
However, with the interactive regression, the signs on five of the six independent variables indicate significant diferences in the coefficients between firms in the “most like the US” group and the US firms.
25
corresponding drop in short term assets to use as collateral for short term bank debt. In bank dominated markets this would reduce short term borrowing capacity. 5)
There is little evidence indicating that either the business risk or size proxies affect dividend policy in a significant or consistent way. For the business risk variable, it could be due to the fact that it is a poor empirical proxy.
6)
Although the same factors are important for these emerging market firms as for the US firms, we find that emerging market firms are more sensitive to some of the variables, indicating the greater financial constraints under which they operate.
7)
Overall the simple country dummies have as much explanatory power as the six independent financial variables. Country and institutional factors are clearly iimportant and more work needs to be done in identifying exactly what these are.
8)
In the full model country dummies are significant, indicating that after adjusting for known differences in profitability, debt, tangibility of assets etc, firms in these emerging markets pay out more in dividends than do similar US firms.
9)
Finally, our taxonomy of countries based on the structure of their financial systems has some validity, but the overall explanatory power of the “grouped” model is less than with the individual country dummies. This indicates significant heterogeneity across countries, even after adjusting for differences in their financial systems.
The regression models confirm that emerging market firms tend to exhibit similar behavior to firms in the US. However, the puzzle is why they pay such large dividends, when they clearly operate under more significant financial constraints. As yet, we have no answer to this puzzle, but it is clearly a topic for future research.
26
REFERENCES F. Allen and R. Michaely, “Dividend Policy,” in R. A Jarrow, V. Maksimovic and W. Ziemba (eds), Handbooks in Operations Research and Management Science: Finance, 1995, P. Asquith and D. Mullins, “Signaling with Dividends, Stock Repurchases and Equity Issues,” Financial Management, (Autumn 1986), A. Auerbach, and K. Hassett, 1998, “On the Marginal Source of Investment Funds,” Working Paper, University of California, Berkeley, M. Barclay, C. Smith and R. Watts, 1995, “The Determinants of Corporate leverage and Dividend Policies,” Journal of Applied Corporate Finance, 7-4, P. Bardhan, “Corruption and Development: A Review of Issues,” Journal of Economic Literature,(1997),1320-1346. F. Black, “The Dividend Puzzle,” Journal of Portfolio Management, (Winter, 1976), L. Booth, V. Aivazian, A. Demirguc-Kunt, and V. Maksimovic, “Capital Structure in Developing Countries,” Journal of Finance, (February, 2001), 87-131. Brennan, M.J., 1970, Taxes, market valuation and corporate financial policy, National Tax Journal 23, 417-427. A. Christie and V. Nanda, “Free Cash Flow, Shareholder Value and the Undistributed Profits tax of 1936 and 1937, Journal of Finance (December 1994), A. Demirguc-Kunt and R. Levine, June 1999, “Bank Based and Market-Based Financial Systems: Cross-Country Comparisons,” World Bank working paper. D. Diamond, 1991, “Monitoring and Reputation: the Choice Between Bank Loans and Directly Placed Debt,” Journal of Political Economy, F. Easterbrooke, “Two Agency-Cost Explanation of Dividends,” American Economic Review, September 1984, 74(4), Fama, E and K. French, 1997 “Dividends, Debt, Investment and Earnings, “Working paper. Fazzari, Hubbard and Petersen (1988), “Financing Constraints and Corporate Investment,” Brookings Papers for Economic Activity, 1988,
J. Glen and B. Pinto, "Debt and Equity? How Firms in Developing Countries Choose," International Finance Corporation, Discussion Paper #22, 1994, J. Glen, Y. Karmokolias, R. Miller, S. Shah, "Dividend Policy and Behavior in Emerging Markets," International Finance Corporation, Discussion Paper #2, 1994, M. Gordon, “The Savings Investment and Valuation of a Corporation,” Review of Economics and Statistics (February 1962), R. C. Higgins, “Sustainable Growth under Inflation,” Financial Management, (August 1981), C. Hsiao, 1986, Analysis of Panel Data (Cambridge University Press, Cambridge, England). C. James, “Some Evidence on the Uniqueness of Bank Loans,” Journal of Financial Economics 19, (1987), M. Jensen, “Agency Costs of Free Cash Flow, Corporate Finance and Takeovers,” American Economic Review (May 1986), K. Jung, Y. Kim and R. Stulz, “Timing, investment opportunities, managerial discretion and the security design decision,” Journal of Financial Economics 42 (1996), 159-185, La Porta, R., F. Lopez de Silanes, A. Shleifer and R. Vishny, “Law and finance,” Journal of Political Economy 106, (1998), 1113-1155. J. Lintner, “Distribution of Incomes of Corporations Among Dividends, Retained Earnings and Taxes,” American Economic Review, (May 1956), Litzenberger, R. and K. Ramaswamy, 1979, The effect of personal taxes and dividends on capital asset prices: Theory and empirical evidence, Journal of Financial Economics 7, 163-195. S. Lummer and J. McConnell, “Further Evidence on the Bank Lending Process and the Capital Market Response to Bank Loan Announcements,” Journal of Financial Economics, ( December 1989), P. Mauro, “Corruption and Growth,” Quarterly Journal of Economics 110, (1998), 681- 712. M. Miller and F. Modigliani, “Dividend Policy Growth and the Valuation of Shares,” Journal of Business, (October, 1961), J. Poterba, 1987, Tax policy and corporate savings, Brookings Papers on Economic Activity 18, 455503.
R. Rajan, “Insiders and Outsiders: the Choice Between Informed and Arm’s Length Debt,” Journal of Finance, (September 1992), R. Rajan, and L Zingales, 1995, What do we know about capital structure? Some evidence from international data, Journal of Finance 50, 1421-1460. Price Waterhouse, various issues, Doing Business In....., Price Waterhouse, New York. M. Rozeff, “Growth, Beta and Agency costs as Determinants of Dividend Payout Ratios,’ Journal of Financial Research,”1982, C. Smith, “Alternative Methods for Raising Capital: Rights versus Underwritten Offerings,” Journal of Financial Economics, (1977). A. Thakor, “Strategic Issues in Financial Contracting: An Overview,” Financial Management (Summer 1989), R. Watts, The Information Component of Dividends,” Journal of Business (April 1973). T, Whited, “Debt, liquidity constraints and corporate investment: evidence from panel data,” Journal of Finance 67-4, (September 1992), 1425-1459.
Table 1
Sustainable Growth Rates
Retention rate 1,3
Return on Equity1 %
Sustainable growth2 %
Real GDP 1981-90 %4
Inflation rate % 198119905
Nominal growth % 19811990
South Korea
0.67
0.08
5.4
9.85
6.39
16.88
India
0.70
0.15
10.5
6.05
8.87
15.46
Malaysia
0.60
0.07
4.2
5.21
3.24
8.62
Thailand
0.56
0.15
8.4
7.98
4.43
12.77
Zimbabwe
0.64
0.13
8.32
5.77
14.00
20.58
Jordan
0.56
0.08
4.48
1.37
7.52
8.99
Pakistan
1.00
0.19
19
6.45
6.97
13.87
Turkey
0.38
0.22
8.36
5.15
46.28
53.81
US
0.69
0.13
8.97
2.73
4.74
7.60
1. Using medians from Table 5 & 6. 2. Gordon sustainable growth rate calculated as the retention rate times the return on equity. 3. The retention rate is the earnings per share minus the dividend per share divided by the earnings per share. 4. Estimated from the nominal growth rate and the inflation rate. 5. As measured by consumer prices. .
Table 2
Capital Market Development
Stock Market Value (MM local currency) Turnover
Market Cap/GDP Liquid Liabilities/GDP
Time
India
Korea
Jordan
Malaysi a
Pakistan
Thailand
Turkey
Zimbab we
US
1982
7058
4408
2845
13903
877
1260
N/A
355
1520167
1986
13588
13924
2839
18531
1710
2878
935
410
2636598
1990
38567
11059 4
2001
48611
2985
23896
19065
2395
3072303
81-85
64
68
10
16
N/A
23
N/A
6
38
86-90
63
100
17
18
9
82
18
4
68
81-85
4.2
6.7
66.3
59.7
3.8
3.9
N/A
5.2
52.8
86-89
7.8
39.6
44.5
78.5
3.1
17.4
4.2
13.5
56.2
1990
0.4
0.37
1.14
0.94
0.4
0.54
0.24
0.39
0.64
1. US data is average for 1981-1990 Data is from the IFC Emerging Stock Market fact Book (1995)Trends in Developing Economies: Extracts, Emerging Capital Markets, Volume 2, World Bank (1993). IMF, International Financial Statistics: The World Bank, World Development Record (1992). Turnover ratio is the value of the stocks actually traded as a percentage of the average total value of listed stocks. The number and value of stocks pertain to stocks in the IFC Emerging Markets Data Base. US data from Rajan and Zingales (1995). Liabilities/GDP is liquid liabilities comes from King and Levine (1993).
Table 3
Qualitative Factors in Capital Markets India
Korea
Jordan
Malaysia
Pakistan
Thailand
Turkey
Zimbabwe
US
Accounting standards
A
G
A
G
A
A
A
A
Investor protection
AS
GS
AS
GS
AS
AS
AS
AS
Governance
5.25
5.75
8.33
6
4
1.5
6
8.75
10
Shareholder rights
2
1
1
2
3
3
0
2
3
Creditor rights
2
3
-
2
2
2
4
2
3
Average ownership concentration2
0.4
0.23
NA
0.54
0.37
0.47
0.59
0.55
0.2
Corporate tax rate 3
0.45
0.37
0.38
0.35
0.46
0.30
0.25
0.50
0.46
Individual tax rate
0.40
0.50
0.45
0.40
0.35
0.37
0.55
0.60
0.36
Dividend/capital gain4
0.75
0.91
1.00
1.00
0.91
1.46
1.00
0.89
1.00
Accounting standards and investor protection are rated according to the following key: G=good, of internationally acceptable quality, A=Adequate, P=Poor, requires reform. S=Functioning securities commission/government agency regulating market activity. Contractual rights are rated on a 1-4 and governance on a 1-10 scale with a higher number being better. 1. Source, Mauro (1995), Bardhan (1997) and Laporta et al (1998). 2. The largest three shareholders in ten largest public companies, source LaPorta et al (1998) 3. Tax data is from Price-Waterhouse and Ernst and Young’s “doing Business in..” series, except for the US, which is from Rajan and Zingales (1995). 4. Indicates the after tax dividend to the after tax capital gain assuming accrual taxation
Table 4
Composition of IFC Sample of Firms
Years
#Firms in Sample
Total listed # firms in 19901
Maximum # observations
Korea
1980-1990
93
669
1,031
India
1980-1990
99
6,200
1,188
Malaysia
1983-1990
96
282
733
Thailand
1983-1990
64
214
503
Zimbabwe
1980-1988
48
57
431
Jordan
1983-1990
38
105
391
Pakistan
1980-1987
96
487
948
Turkey
1983-1990
45
110
387
1. From IFC, Emerging Market Fact Book, 1995.
Table 5
Basic Financial Data
Korea
India
Malaysia
Thailand
Zimbabwe
Jordan
Pakistan
Turkey
USA
Tang.
Busrisk
Size
Debt
Coverag Current
0.49 0.50 0.15
0.03 0.03 0.02
0.12 0.12 0.01
0.73 0.75 0.12
2.46 1.48 5.44
0.40 0.38 0.17 0.57 0.56 0.22 0.38 0.37 0.18 0.44 0.41 0.13 0.51 0.50 0.24 0.38 0.36 0.20 0.41 0.39 0.19 0.35 0.31 0.15
0.05 0.04 0.03 0.05 0.04 0.04 0.04 0.03 0.04 0.08 0.05 0.14 0.08 0.07 0.05 0.06 0.06 0.04 0.05 0.05 0.03 0.04 0.03 0.03
0.14 0.14 0.01 0.12 0.11 0.01 0.13 0.13 0.01 0.10 0.10 0.01 0.08 0.07 0.02 0.06 0.06 0.01 0.10 0.10 0.02 0.07 0.07 0.01
0.67 0.69 0.13 0.42 0.42 0.21 0.58 0.59 0.20 0.42 0.42 0.13 0.46 0.45 0.19 0.66 0.66 0.19 0.59 0.61 0.17 0.41 0.41 0.12
5.77 2.27 15.38 20.96 6.11 31.47 13.36 5.60 20.03 20.33 7.27 29.51 N/a N/a N/a 5.25 1.16 13.32 11.21 2.49 23.48 12.90 5.85 28.74
ROE
M/B
1.16 1.07 0.50
0.08 0.08 0.11
0.75 0.58 0.67
1.23 1.18 0.37 1.66 1.36 1.18 N/a N/a N/a N/a N/a N/a 1.80 1.34 1.84 1.28 1.15 0.68 1.44 1.27 0.76 2.36 2.23 0.98
0.16 0.15 0.11 0.06 0.07 0.19 0.16 0.15 0.26 0.13 0.13 0.13 0.07 0.08 0.31 0.21 0.19 0.48 0.23 0.22 0.18 0.12 0.13 0.16
1.42 1.13 1.17 2.32 1.85 1.81 2.47 1.82 2.07 0.58 0.39 0.62 1.42 1.19 0.68 0.92 0.86 0.75 1.90 1.44 1.25 1.86 1.53 1.33
The individual ratios for each country are successively the average, the median and the standard deviation of each value across all the firms in the sample. Tang is the tangibility of assets: total assets minus current assets dividend by total assets. Busrisk is the standard deviation of the return on investment. Size is the natural logarithm of sales in local currency. The debt ratio is total liabilities minus stockholder’s equity divided by total liabilities. The current ratio is current assets divided by current liabilities. ROE is the net income divided by stockholder’s equity. M/B is the market value of the common stock divided by its book value. N/a is not available. Coverage is the interest coverage ratio, EBIT/I.
Table 6
Measures of Dividend Policy
Dividend Payout
Dividend Yield
Div/TA
Div/BV
South Korea 1981-90 (n=1,031)
0.42 0.33 0.42
0.13 0.04 0.25
0.01 0.01 0.01
0.03 0.03 0.02
India 1981-90 (n=1,188)
0.35 0.30 0.41
0.04 0.04 0.04
0.02 0.02 0.05
0.05 0.05 0.05
Malaysia 1984-90 (n=733)
0.50 0.40 0.86
0.02 0.02 0.02
0.04 0.03 0.07
0.04 0.03 0.05
Thailand 1981-90 (n=503)
0.43 0.44 0.40
0.04 0.03 0.04
0.06 0.05 0.04
0.08 0.07 0.10
Zimbabwe 1981-88 (n=431)
0.35 0.36 0.33
0.10 0.10 0.08
0.05 0.04 0.04
0.05 0.04 0.05
Jordan 1981-90 (n=391)
0.40 0.44 0.39
0.04 0.04 0.04
0.04 0.04 0.05
0.06 0.06 0.07
Pakistan 1981-88 (n=948)
0.27 0.00 0.88
0.06 0.06 0.05
0.03 0.00 0.09
0.05 0.00 0.18
Turkey 1983-90 (n=387)
0.60 0.62 0.41
0.15 0.13 0.13
0.06 0.06 0.06
0.16 0.14 0.14
USA 1981-90 (n=988)
0.33 0.31 0.84
0.05 0.04 0.04
0.02 0.02 0.02
0.05 0.04 0.03
For the individual ratios each entry is successively the average, the median and the standard deviation of each value across all the firms in the sample. Payout is the divided per share divided by the earnings per share. Yield is the dividend per share divided by the average of the high and low price for the year. Div/TA is the aggregate dividends divided by the total assets. Div/BVis the aggregate dividends divided by the book value of stockholder’s equity.
Table 7
Differences in Dividend Policy The t statistics are reported for differences in the average value for each country from the average value for three other samples: the sample of US firms; all other firms minus firms from that country and the US; and all other firms minus firms from that coutnry, but including the US firms. * denotes that the difference in means is significant at the 5% level.
Korea
India
Malaysia
Thailand
Zimbabwe
Jordan
Pakistan
Turkey
Variables
U.S.
All + US.
All - US.
Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE
3.3* 11.4* -15.0* -11.7* 0.9 1.7 -0.1 0.6 4.2* -10.9* 6.8* -3.3* 6.2* -6.5* 13.3* 11.9*
-1.0 11.4* -23.6* -17.1* -5.9* -8.4* -9.1* -5.5* 2.2* -16.4* 3.9* -8.0* 4.3* -13.2* 10.6* 9.7*
-6.2* 11.4* -18.1* -12.5* -8.3* -9.2* -10.2* -6.2* 1.1 -15.6* 2.8* -8.6* 2.6* -13.0* 9.6* 8.7*
Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE Payout Yield Div/TA Div/BE
1.5 5.8* 5.9* 3.2* 2.6* -2.2* 7.6* 4.4* 7.1* 4.3* 8.1* 8.3* 6.4* 8.1* 6.5* 8.3*
-0.8 1.9 4.7 2.0 -1.0 -10.2* 4.6* 2.4* 6.6* -0.3 7.7* 8.2* 5.0* 6.2* 5.1* 7.8*
-1.6 0.8 4.4* 1.7 -2.5* -10.7* 3.6* 1.7 6.3* -1.6 7.5* 8.2* 4.3* 5.5* 4.7* 7.6*
Table 8
Cross Sectional Regression Model Regression coefficients estimated using pooled OLS with and without the market to book ratio.Dividends divided by total assets is the dependent variable. The first number is the coefficient and the second is the t statistic.
Observations
Cons
Busrisk
Logsize
Tangibility
ROE
M/ B
Korea 951 965
0.068 (13.92) 0.061 (12.25) 0.109 (11.56) 0.118 (4.52) 0.045 (1.77) 0.052 (2.14) 0.056 (2.06) 0.031 (1.10) 0.149 (1.12) 0.355 (2.99) 0.047 (2.99) 0.091 (7.09) 0.583 (6.32) 0.055 (1.92) 0.216 (5.55) 0.115 (5.44) 0.028 (7.86) 0.043 (12.44)
-0.067 (-3.73) -0.074 (-3.99) 0.034 (1.52) 0.143 (2.32) -0.130 (-1.66) -0.092 (-1.26) 0.049 (0.63) 0.089 (1.03) 0.481 (1.72) 0.423 (1.42) -0.030 (-0.56) -0.073 (-1.46) 0.466 (1.69) 0.175 (1.89) -0.180 (-1.31) 0.064 (0.69) -0.012 (-0.64) -0.028 (-1.38)
-0.201 (-5.23) -0.107 (-2.84) -0.145 (-2.40) -0.157 (-0.97) 0.516 (2.60) 0.527 (2.78) 0.086 (0.43) 0.365 (1.78) 0.260 (0.25) -1.129 (-1.15) 0.356 (1.64) -0.007 (-0.04) -4.041 (-3.46) 0.682 (1.95) -1.171 (-3.38) -0.361 (-2.44) 0.051 (1.26) 0.032 (0.73)
-0.005 (-2.45) -0.004 (-1.76) -0.038 (-11.78) -0.044 (-4.94) -0.031 (-2.41) -0.038 (-3.15) 0.012 (0.96) 0.022 (1.67) -0.227 (-4.58) -0.294 (-6.41) -0.045 (-3.91) -0.050 (-4.34) -0.222 (-4.57) -0.035 (-2.15) -0.001 (-0.03) 0.016 (1.28) 0.005 (1.48) 0.000 (0.08)
0.029 (9.75) 0.027 (8.94) 0.050 (9.34) 0.069 (4.74) 0.029 (1.67) 0.029 (2.11) 0.195 (7.78) 0.109 (5.17) 0.073 (1.02) 0.141 (1.97) 0.058 (5.09) 0.076 (7.02) 0.018 (0.62) -0.003 (-0.50) 0.174 (8.67) 0.204 (15.67) 0.012 (3.51) 0.024 (6.85)
0.003 (5.60)
India 841 931 Malaysia 687 710 Thailand 192 210 Zimbabwe 54 54 Jordan 316 334 Pakistan 196 890 Turkey 57 363 US 988 988
0.003 (5.02)
0.003 (1.81)
0.003 (2.87)
0.026 (2.78)
0.021 (6.19)
0.008 (0.54)
0.002 (0.55)
0.005 (11.98)
Debt Ratio -0.043 (-15.42) -0.046 (-16.07) -0.094 (-21.11) -0.104 (-8.18) -0.114 (-7.66) -0.111 (-7.95) -0.114 (-9.25) -0.098 (-7.61) -0.170 (-3.14) -0.222 (-4.10) -0.086 (-4.57) -0.048 (-2.68) -0.257 (-5.54) -0.097 (-5.68) -0.107 (-3.69) -0.123 (-8.45) -0.048 (-10.3) -0.057 (-11.72)
Adj R2 31.6% 28.8% 49.4% 11.8% 11.7% 11.6% 48.1% 35.9% 55.6% 49.3% 41.5% 33.7% 28.9% 4.4% 71.1% 52.7% 30.0% 19.9%
Table 9
Cross Sectional Regression Model (Fixed Effects Estimates) Regression coefficients estimated using annual data and estimated using fixed effects. Dividend divided by total asset the dependent variable. The first number is the coefficient and the second is the T statistic.
Observation s Korea 951 965 India 841 931 Malaysia 687 710 Thailand 192 210 Zimbabwe 54 54 Jordan 316 334 Pakistan 196 890 Turkey 57 363 US 988 988
Cons
Busrisk
Logsize
Tangibility
ROE
M/ B
0.009 (10.72) -0.005 (-5.62) 0.009 (5.27) -0.004 (-0.77) -0.004 (-0.67) 0.002 (0.32) -0.001 (-0.45) 0.009 (0.37) -0.002 (-0.12) 0.014 (0.67) 0.004 (0.49) 0.002 (0.10) -0.001 (-0.05) -0.028 (-3.24) -0.003 (-0.48) -0.013 (-1.37) 0.002 (3.06) 0.002 (2.83)
-0.000 (-0.02) 0.002 (0.12) 0.002 (0.17) 0.002 (0.04) -0.002 (-0.03) -0.003 (-0.05) 0.001 (0.12) 0.004 (0.08) -0.001 (-0.00) -0.000 (-0.00) 0.009 (0.17) 0.005 (0.12) -0.006 (-0.06) 0.004 (0.06) 0.003 (0.04) -0.006 (-0.08) -0.000 (-0.12) -0.000 (-0.02)
0.008 (0.27) 0.162 (2.27) -0.007 (-0.26) 0.002 (0.00) -0.017 (-0.15) 0.754 (1.72) -0.023 (-0.32) 1.75 (2.63) 0.011 (0.13) 1.314 (0.83) -0.015 (-0.17) -0.992 (-1.25) 0.021 (0.16) -0.224 (-0.26) -0.029 (-0.18) -0.553 (-0.96) 0.103 (1.15) 0.165 (1.81)
-0.007 (-2.31) -0.007 (-2.17) -0.046 (-8.87) -0.085 (-4.47) -0.032 (-1.14) -0.032 (-1.22) 0.006 (0.39) -0.015 (-0.70) -0.215 (-5.59) -0.226 (-5.79) -0.113 (-5.40) -0.120 (-5.76) 0.052 (0.66) -0.034 (-1.08) 0.169 (2.91) 0.031 (1.51) 0.012 (2.60) 0.012 (2.44)
0.030 (11.73) 0.028 (10.54) 0.034 (8.26) 0.015 (0.95) 0.016 (1.03) 0.011 (0.794) 0.174 (8.11) 0.052 (2.78) 0.007 (0.11) -0.005 (-0.07) 0.051 (4.60) 0.052 (4.54) -0.043 (-2.29) -0.002 (-0.39) -0.017 (-0.51) 0.175 (10.95) -0.000 (-0.05) 0.002 (1.22)
0.003 (4.92)
-0.000 (-0.68)
0.003 (1.60)
0.001 (1.15)
0.011 (1.34)
0.015 (3.44)
-0.024 (-1.79)
0.007 (1.57)
0.002 (7.20)
Debt Ratio -0.034 (-9.14) -0.035 (-9.15) -0.059 (-11.03) -0.073 (-3.68) 0.004 (0.17) 0.002 (0.10) -0.069 (-5.24) -0.041 (-2.75) 0.129 (1.32) 0.145 (1.40) -0.003 (-0.15) 0.048 (1.44) -0.268 (-4.90) -0.086 (-3.26) -0.064 (-1.15) -0.120 (-5.63) -0.025 (-8.63) -0.025 (-8.51)
Adj R2 30.7% 28.7% 29.4% 5.9% 0.1% 0.2% 33.6% 20.6% 60.1% 59.1% 29.9% 24.7% 10.8% 29.0% 21.6% 31.5% 14.3% 9.9%
Table 10 OLS Cross-Dummy Variable T-Statistics * indicates significance ( 5% level) of the interactive term of each varible with the country/group dummy. Variables
Korea
India
Malaysia
Thailand
Zimbabwe
Jordan
Pakistan
Turkey
Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt Bus Risk Logsize Tangibility ROE M/B Debt
US
ALL+US
ALL-US
-1.8 -3.9* -2.5* 3.3* -3.1* 0.8 1.6 -2.6* -8.9* 5.9* -3.5* -7.2 -1.7 2.8* -2.9* 1.2 -1.6 -4.3* 1.1 0.3 0.7 10.8* -2.3* -6.8* 3.6* 0.4 -9.6* 1.8 4.6* -4.6* -1.8 -3.6* 0.8 -0.8 0.5 1.8 3.7* -8.1* -9.6* 0.3 0.4 -8.5* -1.8 -5.2* -0.4 11.8* -1.6 -3.0*
-2.8* -1.1 1.1 -2.1* 0.3 1.7 -2.5* -1.2 -2.0* -0.8 0.3 -2.0* -5.9* 3.5* -1.0 -2.2* -0.5 -5.3* -1.1 0.3 1.2 3.2* 0.9 -2.4* 0.8 0.2 -3.3* 0.1 1.9 -1.5 -1.1 -1.8 0.6 -0.5 0.7 0.5 4.4* -11.0* -12.8* -3.0* 0.9 -11.2* -1.4 -1.8 0.4 3.0* -0.1 -0.7
-1.5 2.7* 5.5* -1.7 0.2 4.2* 0.4 2.0* 1.4 -0.9 -0.6 -0.1 -2.6* 6.4* 1.8 -2.2* -2.5* -1.8 0.2 1.7 2.9* 2.9* 0.3 -1.0 1.2 0.5 -2.6* 0.1 1.7 -1.0 -1.0 -1.2 0.8 -0.1 -0.0 -1.3 4.9* -9.3* -10.6* -4.3* 0.7 -9.6* -0.7 -1.0 1.3 2.7* -0.3 -0.2
Difference 1
4-3
4-1
3-4
3-2
4-1
1-0
4-5
3-1
1 Difference in the number of significant coefficients: US compared to emerging market sample.
Table 11
Pooled Sample of all Firm-year Observations Regression estimates of debt/total assets against the independent variables indicated in the row headings. The first number is the coefficient in brackets is the t statistic.There are 4,282 observations in each model.
Country dummies
Full model
Group: Pooled
0.056 (14.0)
0.060 (11.7)
0.095 (23.1)
Business
0.186 (7.5)
0.038 (1.6)
-0.01 (0.40)
Logsize
0.015 (0.5)
0.081 (1.3)
-0.525 (-15.1)
Tangibility
-0.015 (-3.8)
-0.035 (-8.7)
-0.034 (-8.2)
ROE
0.061 (13.0)
0.035 (7.8)
0.047 (10.5)
Market-to-
0.002 (4.1)
0.004 (6.5)
0.004 (7.5)
Debt Ratio
-0.066 (-15.1)
-0.102 (-21.2)
-0.089 (-21.0)
Constant
0.024 (15.7)
Korea
-0.011 (-5.0)
0.029 (7.6)
India
-0.000 (-0.0)
0.022 (4.5)
Malaysia
0.018 (7.5)
0.023 (6.1)
Thailand
0.039 (10.4)
0.036 (6.7)
Zimbabwe
0.045 (6.7)
0.047 (7.1)
Jordan
0.021 (6.8)
0.033 (10.5)
Pakistan
0.090 (23.7)
0.114 (29.7)
Turkey
0.041 (6.3)
0.056 (8.5)
Most like US
0.054 (19.9)
Least like US
0.072 (23.8)
Other
0.052 (18.2)
Adjusted
18.0%
13.5%
29.6%
24.1%
