Shareholder Reaction to Dividend Announcements in an Emerging Market :

Shareholder Reaction to Dividend Announcements in an Emerging Market :

Evidence from the Tunisian Stock Exchange

Mounira Ben Arab, Nadia Ben Sedrine, Adel Karaa. Finance India. Delhi: Sep

2004.Vol.18, Iss. 3; pg. 1295, 20 pgs http://proquest.umi.com/pqdweb?did=766272711&sid=45&Fmt=4&clientId=68814&RQT

=309&VName=PQD

Abstract (Document Summary)

Dividend policy behaviour of corporations operating in emerging markets is significantly different from the widely accepted dividend policy behaviour of corporations operating in developed markets. This study examines the information content of dividend policy through the share price reaction on the Tunisian Stock Exchange from 1998 to 2001. In particular, the purpose of this study is: (i) To identify the market reaction at the release of news from the ordinary general assembly, which is assessed through the observed return, the systematic risk, the volatility and the abnormal return. (ii) To evaluate the dividend informational effect on the share prices. Methodologically, we apply an appropriate approach situated within the general frame of event studies that disentangles the mean effect from the variance effect when measuring a change in stock prices. [PUBLICATION ABSTRACT]

Full Text (5004 words)

Copyright Finance India, Indian Institute of Finance Business School Sep

2004[Headnote]

Abstract

Dividend policy behaviour of corporations operating in emerging markets is significantly different from the widely accepted dividend policy behaviour of corporations operating in developed markets. This study examines the information content of dividend policy through the share price reaction on the Tunisian Stock Exchange from 1998 to 2001. In particular, the purpose of this study is: (i) To identify the market reaction at the release of news from the ordinary general assembly, which is assessed through the observed return, the systematic risk, the volatility and the abnormal return. (ii) To evaluate the dividend informational effect on the share prices. Methodologically, we apply an appropriate approach situated within the general frame of event studies that disentangles the mean effect from the variance effect when measuring a change in stock prices.

I. Introduction

THE SO-CALLED DIVIDEND puzzle (Black 1976) has been the focus of finance economists at least since Modigliani and Miller's seminal work (1958,1961). This work established that, in a frictionless world, when the investment policy of a firm is constant, its dividend payout policy is irrelevant meaning that it has no consequences for the shareholder's wealth. Higher dividend payout leads to lower retained earnings and capital gains, and vice versa, it leaves total wealth of the shareholders unchanged.

Economists have proposed a number of explanations of the dividend puzzle. One of these adresses gives the idea that firms can signal future profitability by paying dividends (Bhattacharya, 1979; John and Williams 1985; Miller and Rock, 1985).

Empirically, this theory had a considerable initial success, since the firms that initiated

(or raised) distribution of dividends have experienced an increase in share price, and the opposite is true for firms that have taken steps to eliminate (or cut) dividends (Aharony and Swary, 1980; Asquith and Mullins, 1983). Recent evidence has been mixed, since current dividend changes do not appear to help predict the future earnings growth of firms (DeAngelo, DeAngelo and Skinner, 1996; Benartzi, Michaely, and Thaler, 1997). In any event, dividend signalling theories do not have obvious implications for dividend policies across countries.

Emerging markets add more pieces to the "dividend puzzle" and have recently attracted researches trying to explain the dividend policy behaviour of corporations operating in these markets (Glen Karmokolias, Miller, and Shah, 1995). However, it is still not satisfactorily explained why corporations distribute a portion of their earning as dividend or why investors pay attention to dividends.

The purpose of this study is to adopt an appropriate methodology combining two objectives

* To identify the market reaction at the release of announcements (earnings, dividend distribution etc...) at the ordinary general assembly.

* To evaluate the informational effect of dividend.

The remaining parts of the paper are divided into three sections.

Section II provides a relevant background on the dividend signal. Section III contains the description of data and sample, selection of variables, and the methodology of the empirical analysis. The empirical results are reported in this section. The concluding remark, limitation of the study and suggested future research are incorporated in section

IV.

II. The Dividend Signal

The usefulness and the justification of the dividend policy constitute one of the most controversial topic of the financial theory. For Black (1976), "the harder we look at the dividend picture, the more it seems like a puzzle, with pieces that just don't fit together".

Traditionally, the widespread use of dividends as a method of distributing cash to shareholders has been regarded as puzzling. While it is not difficult to proceed with a distribution of some earnings, dividends are treated less favourably than repurchases of shares and therefore appear to be the dominant scheme as a mechanism for transfering resources to shareholders.

Dividend policy is considered one of the most crucial issues for management decision because it seems an important way for companies to communicate with market participants. Investors cannot always trust managers to provide unbiased information about their companies prospects, but dividend signals are relatively reliable because they require cash payments and cash cannot be easily manipulated. This is known as the information content of dividends.

Applications of signalling theory in the area of corporate payout policy have become increasingly common. The best known signalling models (asymmetric information

models) are Bhattacharya (1979), Hakansson (1982), Miller and Rock (1985), Ambarish,

John and Williams (1987). Yet few authors have provided explanations for the practice of signalling with dividends rather than repurchases of shares (John and Williams, 1985,

Bernheim, 1991). The information content hypothesis states that dividend announcements are used by managers as a way to signal shareholders in respect of future prospects of the firm.

In fact a fundamental question in corporate finance has been whether changes in dividend policy convey information about the firm's performance to capital markets. Not only are there well documented price reactions to announcements of changes in dividend policy, but dividends have also been established as a mechanism whereby information related to the operations and future plans of a firm can be communicated

(Benartzi, Michaely and Thaler, 1997).

Tests of significance of dividend changes showed that capital markets react favourably to 'good news' announcements (dividend increases) and adversely to 'bad news' announcements (dividend cuts), supporting the view that dividend changes have an information content (Michaely, Thaler and Woack, 1995).

Overall, empirical studies show that there is a positive market reaction to dividend increases and a negative market reaction to dividend cuts. It should be noted that the market reaction to a dividend cut is far greater than the market reaction to a dividend increase (Benesh, Keown and Pinkerton, 1984; Eades, Hess and Kirn, 1985). Ang

(1987), Alien and Michaely (1997), Lease John, Kalay, Lowenstein and Sarig, (2000) provide an extensive review of the market reaction to dividend announcements.

Additionally, it has been found that signal strength is a function of the amount of information transmitted and large dividend changes are stronger signals than smaller dividend changes (Asquith and Mullins, 1983). As a result the magnitude of information effects of dividends has increased the need for prediction of dividend changes.

Since Lintner (1956), several other researchers examined the association between earnings and dividend changes. More recent studies have focused on the impact of losses on dividend changes (DeAngelo and DeAngelo, 1990), as well as on the effect of cash flow on dividend policy (Simons, 1994; Charitou and Valeas, 1998). DeAngelo and

DeAngelo (1990) document a high incidence of dividend cuts by firms with persistent losses, but they provide no similar evidence for firms with transitory losses. DeAngelo,

DeAngelo and Skinner (1996) have argued that dividends and current earnings are likely substitutes for forecasting future earnings and the information content of dividends will vary depending on the characteristics of current earnings.

Watts (1973), Benartzi, Mickaely and Thaler (1997) observed a weak association between unexpected earnings and dividend changes for randomly selected firms. Using non random samples, DeAngelo, DeAngelo and Skinner (1996), Healy and Palepu

(1988) indicate that dividend cuts have incremental information content in predicting future earnings, given current earnings.

Starting from these results, what is the most appropriate dividend policy that the firms must adopt? This question still remain unanswered. Explanations could be found in the

Lintner model. Lintner (1956) finds that firms follow stable (sticky)dividend policies and in case they experience a substantial increase in earnings, their dividends are not

increased by a substantial amount but are gradually increased considering the targeted dividend payout ratio. On the other side firms do not tend to decrease dividends and even if there is a downturn in earnings, firms try to pay out the same level of dividends that was distributed in previous years.

Lintner also points out that managers believe that investors prefer firms that follow stable dividend policies. Many studies were done in this subject (Shevlin (1982), Baker, Farrelly and Edelman (1985), Pruitt and Gitman (1991), Leithner and Zimmermann (1993), Kato and Loewenstein (1995), Dewenter and Warther (1998) and the common result is that firms follow stable dividend policy.

Consequently, due to a sticky dividend policy, any change in dividend policy is interpreted as a change in the management's expectations of future earnings.

III. Research Design

Within the frame of event studies, the residual approach is mostly retained in order to determine the abnormal return of shares. It consists for each event period, in calculating the abnormal return of shares through a simple difference between the observed return and the norm obtained from a theoretical model whose parameters are estimated within a period that exclude any event that may create a market reaction.

Therefore, the residual approach consists in generating a vector of abnormal return on the event window1. The abnormal return for the firm f is defined as the difference between actual return and expected return.

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Nevertheless, other authors (of which Thompson, 1985, Malatesta, 1986; Eckbo,

Maksimovic and Williams (1990), have considered within their research, the variable event approach that consists in regressing the . observed return on a set of factors and on a dummy variable referring to the event period (which take the value 1 on the event period and O otherwise).


If uncertainty exists in the applications of event studies, it has been in identifying the expected return in equation (1). The most widely used expectation is the risk adjusted measure3.


However, using market model, in order to compute the expected return, is inappropriate.

Courts, Mills and Roberts (1994) show that abnormal return based on the market model exhibit a portfolio of mis-specifications in the estimation period, including residual autocorrelation, ARCH effect. In order to estimate this model, standard QLS regressions will result in inefficient parameter estimates.

Many studies (Schwert and Seguin (1990), Funke, (1992) suggest that the GARCH (1,1) structure explain better the process of the daily return. Empirical studies (Akgiray, 1989, de Santis and Inrohoroghu, 1997) show that the volatility of daily return is not constant over time. So the variance of daily stock returns is characterized as a GARCH process.

Indeed, Ross (1989) shows that increases in the abnormal return may increase the residual variance of stock returns, rather than their mean value, which is a measure of the wealth effect. Without allowing for possible increases in residual variance (the variance effect) one may misinterpret the apparent stock price reaction as a wealth effect. As a result, a positive wealth may be found when there is really no true wealth effect, but rather a strong variance effect.

On the other side, the market model assumed a time invariant systematic risk. However, many studies suggest that the assumption of time invariant risk is invalid (Collins,

Ledolter and Rayburn, 1987; Brooks, Faff and Lee, 1995.

3.1. The market reaction to General Ordinary Assembly (GAO)

To identify the market reaction at the news released on the ordinary general assembly, we start by regressing returns on the market index return and a set of dummy which take the value one depending on whether the period related to an event date.


According to the expected return measured by (4), we can define an excess return

(ER^sub it^) for each firm i from the period January 1998 to December 2001.


The change in the dividend level (eq. 9) depends on the difference between the targeted dividend payment (D*^sub ij^); which depends on the level of earnings (E^sub ij^) and the observed last period dividend payment (D^sub i(i-1)^).


The residuals in equation (10) result from two types of variations: variation across firms

(index i) and variation across years (index j). In other words, several cross-sectional units (firms)are observed over a period of time (a year) in a panel data setting.

There are three common regression techniques used in estimating models with panel data-pooled ordinary least squares, fixed effects models and random effects models. To estimate the equation (10), we choose the most appropriate technique according to the

F-statistic (the null hypothesis indicates that the efficient estimator is the pooled ordinary least squares compared to the fixed effects model) and the Hausman tests (the null hypothesis indicates that the random effects model is more appropriate than the fixed effects model). These three methods are based on the assumption that the matrix of the variance and covariance of residual terms is known. In most empirical studies this matrix is not known and must be estimated. Therefore, we employ a two stage estimation process or FGLS approach.

On the other hand, to estimate the market reaction to the instability of the dividend policy adopted by a corporation, we regress the Cumulative Abnormal Return (CAR) on the difference between the dividend payment announced on the GOA and the expected dividend payment (estimated by Litner's model) and a dummy variable which takes the values one or zero depending on whether the corporation announces to distribute or not dividends.


This model is also estimate by the FGLS method for the same reasons presented in the case of Lintner model estimation.

3.2.1. Data

The data have been gathered from the BVMT and the CMF and adresses the daily stock prices of all companies listed on the Stock Exchange over the period January 1998 -

December 2001. The companies selected for this study are those whose stock is a component of the Tunindex index and that has minimum daily quotations over the year of 180 days.

These data have permitted to set for every company a daily series of returns2.

Using the same approach, the daily series of the Tunindex index has permitted to calculate,the market return. The sample comprises 124 events linked to Ordinary

General Assembly meetings held by 35 companies during the period 1998-2001. For this purpose, we consider the event window as a symetrie event period of 30 days.

3.2.2 Empirical Result

In this study, we have to measure the effect of the OGA (Ordinary General Assembly) on the value of a firm. Through the assumption of an efficient financial market, the effect of an event will be reflected immediately in the asset prices.

Traditionally, the event study has always proceeded in two stages. First the normal return is estimated on an "estimation window" which is commonly preceding to the event window, using simple statistical methods. second and in order to define the expected return for the event, these estimators are used across the event period because the regression analysis assumes the explanatory variables are invariant. However, this assumption is not plausible.

To avoid these problems, we adopt an appropriate methodology, and we analyse the effect of the event, which is the Ordinary General Assembly, through the excess return, being the difference between the daily return of a firm and the normal return.

The normal returns are measured by (4) for each firm and for the whole period of analysis (from January 1998 to December 2001), using Autoregressive-GARCH specification. This model allow us to analyse directly the effect of the event on the observed return, the systematic risk and the volatility.

These results are summarised on the Table I. In the third column are summarised the coefficients linked to the impact of the Ordinary General Assemblies on the observed

return of stocks. A positive (negative) figure indicates an excess (insufficient) return during the event period as compared to the period outside the event. The coefficients between parenthesis indicate the values of Student t that corresponds to the level of the meaning of parameters.


Table I

Regressions Analysis


Table I



Table I



Table I



Table I


Upon the observation of the 3rd column of the table, we cannot conclude to a clear trend in respect of the impact of Ordinary General Assemblies on the observed returns, since over the 124 events studied, only 17 coefficients have come as significantly different from zero with different signs. The impact of Ordinary General Assemblies appears more significant when it is observed on abnormal returns. Indeed, in the column 7 of Table 1, we can find 44 coefficients that are significantly different from zero. Moreover, we can observe that the negative sign coefficients are dominant, which leads to conclude to an abnormal reduction of stock returns during the event period. The reaction observed could be attributed to

* The phenomena of imitation witnessed in the market. Indeed, some "privileged" investors (shareholders) give a special attention to the news released at the General

Ordinary Assembly. Therefore, having a knowledge of corporate earnings before the official release, they can trade on the exchange and bring the other investors which are attentive to interpret their transactions and react consequently.

* The surprise effect. The information that circulates during the General Assemblies are generally characterised by a surprise effect due to the incapacity of the market to forecast the nature of the earnings released, when these are below expectations, the

market shows its unsatisfaction in respect of the management of the company. We can in fact observe that the magnitude of the reaction on stock prices will change depending on the OrdinaryGeneral Assembly releasing good or bad news. Indeed for the majority of companies a bigger change in returns has been witnessed at the release of bad news

(the cases with negative coefficients in column 7 of Table I) rather than good news (the cases with positive coefficients in column 7 Table I). Whenever the release is "positive", we feel the investor is every time surprised and reacts with caution.

* The non respect of the timing of the release. When observing the dates of the release of semi-annual and annual reports/ we see that these are delayed to the point of leading the investors to consider the possibility of bad news. This conclusion is close to the results reached by Chambers and Penman (1984) evidencing that firms releasing bad news are keen to delay the publication of their financial statement and this is sanctioned by the market.

The fifth column of Table I resumes me results in respect of the impact of Ordinary

General Assemblies over the volatility of stocks. The positive coefficients within this column indicate an increase in stock price volatility during the event period. Over the 124 events studied, we have registered 44 cases whereby the Ordinary General Assembly meeting has been followed by a significant change in the volatility of stock prices. In the majority of cases (80.2%), the outcome has been a reduced volatility.

This trend could be explained by the fact that the period outside the event considered in our study comprises the dates of the release of final financial statements reports. This generally results in a higher volatility than that implied by the Ordinary General

Assemblies meeting. According to Firth (1981), the final annual reports bring an information available to the public and directed to all investors in the market. However, the information prior to its release as it is available during the Ordinary General

Assemblies could only benefit to those "privileged" investors (shareholders), the other investors being cautious in their strategy of adjustment of their portfolio. Within this analysis framework, Gilad Livne (2000) shows that the releases to the public eliminate the informational advantage on hand of the avert shareholders during the preannouncement period.

Finally, the values of the coefficients and the values of the f of student that correspond to the column 4 of Table I seems to indicate a significant impact of opposite signs of holding Ordinary General Assemblies on the systematic risk. This result explains the use of a specification that changes the systematic risk (beta), in order to distinguish the event period from the periods outside the event.

In order to calculate the expected dividend, we estimate the Lintner model as indicated in (10). In Table II, in which the Lintner model estimation results for the 1998-2001 period are presented, The WaId test indicates that the model is globally significant:

WaId chi2(2) = 1130.64 and

Pr > chi2 = 0.0000

The FGLS regression results show that all the parameters are statistically significant.

These indicate that the actual of dividend (D^sub i^) depends on the actual earnings

(E^sub t^) and the past level of dividend(D^sub t-t^).


Table II

Cross-sectional time-series FGLS regression of Lintner model

The final stage in our methodology is to study the market reaction to the dividend policy behaviour of corporations operating in the the Tunisian stock exchange. The construction of the model indicated in (11) is based on the assumption of an association between the magnitude of abnormal returns and the process of dividend adjustment within the context of the Lintner model (1956). In other words, we regress the

Cumu lative Abnormal Return (CAR^sub ij^) on DPA^sub ij^ × I^sub 2^.., DPA^sub ij^ ×

(1~I^sup 2^^sub ij^.) and I^sub ij^.. that correspond respectively to

* the difference between the observed and the expected dividend payment when the firm announces for the year j a dividend higher than it is anticipated by the market,

* the difference between the observed and the expected dividend payment when the firm announces for the year j, a dividend lower than it is anticipated by the market,

* the case where the firm announces during the GOA to cut dividend during the year j since it has distributed the previous year.

The FGLS estimation results of the model are indicated in Table III. Globally, the model appear to be significant since WaId test value is statistically significant. Only the variable

DPA^sub ij^ × I^sup 2^^sub ij^ is significant with a positive sign. This outcome is consistant with the information content of the dividend hypothesis (dividend signalling hypothesis). Both the two other 'regressors, DPA.. × (1-I^sup 2^^sub ij^) and I^sup

1^^sub ij^, are of the predicted sign as expected in the dividend signalling hypothesis (-

0.193 and -0.104 respectively), however they are not statistically significant.


Table III

Cross-sectional time-series FGLS regression of the Cumulative Abnormal

IV. Summary and Conclusions

This paper has investigated the assumption related to the informational effect of dividend signalling. Our model takes into account the event effect on the observed return, the systematic risk, the variability of the variance and the abnormal return.

This analysis has established that the event decreases the residual variance of stock returns. So, our model distinguishes the apparent stock price reaction due to a variation of the volatility and a variation of the return.

In general, the event study findings strongly support the dividend signalling hypothesis in explaning the positive price reactions to an increase in the dividend payment. The

results indicate that the firms operating in the Tunisian Stock Exchange are not an exception : The stock price will move in the direction of the dividend change.

But a question still remains, what is the optimal amount of the dividend we have to distribute in order to increase the wealth of the shareholders? and what is the target payout a firm must determine?

[Footnote]

Notes

1. Commonly, researchers set a symmetric event period of 30 days and report abnormal return across the period.

2. R1, it are calculated with closing stock prices : R^sub i.t^ = In (P^sub i.t^ + D^sub i^

V^sub i.t^) - In (P^sub i.t-t^)

3. The market model is a special case of the APT and all the factors were reduced to the market return.

4. We define the abnormal return as the excess return on the event window.

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