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DO CHANGES IN DIVIDEND POLICY SIGNAL THE FUTURE OR THE PAST?

LIM WEI LING

FACULTY OF BUSINESS AND ACCOUNTANCY UNIVERSITY OF MALAYA

NOVEMBER 2008

Do Changes in Dividend Policy Signal the Future or the Past?

Lim Wei Ling

Bachelor of Business Administration Universiti Kebangsaan Malaysia

2001

Submitted to the Graduate School of Business Faculty of Business and Accountancy

University of Malaya, in partial fulfilment of the requirements for the Degree of Master of Business Administration

November 2008

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ABSTRACT

This research study investigates whether Malaysian Main Board companies pursue

changes in dividends to convey information on the future profitability of the

companies by studying on a total of 2,679 firm-year observations from year 1998 to

2007. The Ordinary Least Square regression results show that Main Board listed

companies do not use dividends as a signalling tool to convey information on the

future prospect of the companies. In fact, positive and significant relationship is found

to be stronger between changes in dividends in year T=0 with concurrent changes in

earnings in year T=0, which is consistent with the previous findings by Benartzi,

Michaely and Thaler (1997) and Nissim and Ziv (2001). Further, regression analysis

on sub-samples of firm-year observations categorized by the period of stable

dividends before the dividend change events (2 years, 3 years and 4 years) shows no

relationship exists between the stability of dividends before dividend change events

with the extent of dividend signalling. No relationship is found between size of

dividend change, size of dividend yield with the extent of dividend signalling.

Multiple regression by incorporating industry dummies in the regression equation

shows that no difference in changes in earnings between the 3 major sectors

(Industrial, Trading/Service and Consumer) when there are changes in dividends,

indicating that industry effect does not have any influence on the extent of dividend

signalling of the companies.

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ACKNOWLEDGEMENTS

I would like to express my gratitude to my supervisor of my research project,

Ybhg. Professor Dato' Dr. Mansor for his patience, support and guidance given on my

research area on dividend signalling. Despite the difficulties encountered in my

research due to meticulous works involved and constraints in getting complete

financial database needed in this study, I am glad to be able to complete my research

on time under the intellectual guidance and share of research experiences by Professor

Dato’ Dr. Mansor.

Million of thanks to my beloved family for their unconditional supports and

understanding despite of my less time with them due to my busy schedule for both

work and research project. Appreciation is also dedicated to my superior and

colleagues at work for their support and understanding during my entire MBA course

period.

Special thanks to Mr CG Teh, Mr KL Ooi and Ms Shirley Lo who have

provided their professional insights on dividend signalling in Malaysia. Being top

management involved in the dividend decision of three Main Board listed companies,

their feedbacks are really useful in explaining the reasons of dividend signalling not

applicable in Malaysia.

Last but not least, I would also like to express my appreciation to my fellow

MBA coursemates who have accompanied me for the whole MBA course with joy

and unforgettable memories. Special thanks to Mr Cheong Kok Loong who has

provided his assistance and support to me during my journey of completing this

research study.

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TABLE OF CONTENTS ABSTRACT……………………………………………………………………. ii ACKNOWLEDGEMENTS…………………………………………………… iii LIST OF SYMBOLS AND ABBREVIATIONS…………………………….. viii CHAPTER 1: INTRODUCTION……………………………………………………………... 1 1.1 PURPOSE AND SIGNIFICANCE OF THE STUDY…………………. 1 1.2 OBJECTIVE AND SCOPE OF THE STUDY…………………………. 2 1.3 LIMITATION OF THE STUDY ………………………………………. 4 1.4 ORGANISATION OF THE STUDY…………………………………... 5 CHAPTER 2: LITERATURE REVIEW…………………………………….. 6 2.1 WHAT IS DIVIDEND POLICY……………………………………….. 6 2.2 THE DIVIDEND SIGNALLING THEORY…………………………… 12

2.2.1 Previous literatures that support earnings and past dividends determine current dividends…………………………………… 15

2.2.2 Previous literatures that support changes in dividends do not provide signals to the market…………………………………… 17

2.2.3 Previous literatures that support changes in dividends provide signals to the market…………………………………………… 20

CHAPTER 3: RESEARCH METHODOLOGY……………………………. 23 3.1 DEVELOPMENT OF THE HYPOTHESES…………………………… 23 3.2 SELECTIONS OF MEASURES……………………………………….. 27

3.2.1 Measure of unexpected earnings………………………………... 28 3.2.2 Measure of changes in dividends……………………………….. 29

3.3 SAMPLING DESIGN…………………………………………………... 30 3.4 DATA COLLECTION PROCEDURE…………………………………. 31 3.5 DATA ANALYSIS TECHNIQUES……………………………………. 32

3.5.1 Data Filtering…………………………………………………… 32 3.5.2 Assumptions adopted in the regression analysis……………… 33 3.5.3 Analysis on the relationship between changes in dividends in

year 0 with changes in earnings in the concurrent year and subsequent 5 years ……………………………………………... 34

3.5.4 Analysis on the extent of dividend signalling with the influence of industry effect using multiple regression…………………….. 36

CHAPTER 4: RESEARCH RESULTS……………………………………… 37 4.1 SUMMARY STATISTICS……………………………………………... 37

4.1.1 Overall Dividend Payment Trend of Main Board Listed Companies in Bursa Malaysia…………………………………... 39

4.1.2 Descriptive summary on the selected samples………………….. 53 4.2 ANALYSIS OF MEASURES………………………………………….. 62

4.2.1 Analysis of Regression Result on All Firm-Year Observations... 66 4.2.2 Analysis of Regression Result on Each Individual Year

Observations From Year 1998 to 2007…………………………. 70 4.2.3 Analysis of Regression Result on Dividend Change Events

During the Financial Crisis Period (1998-2001) and Post-Financial Crisis Period (2002-2007)……………………………. 81

4.2.4 Analysis of Regression Result on Dividend Change Events Occurred After Stable DPS for Consecutive 2 years, 3 years and 4 years…………………………………………………………... 85

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4.2.5 Analysis of Regression Result on the Dividend Change Events Categorized by Size of Dividend Change……………………… 88

4.2.6 Analysis of Regression Result on Dividend Change Events Categorized by Size of Dividend Yield………………………… 89

4.2.7 Analysis of Regression Result on All Firm-Year Observations by Incorporating Industry Effect……………………………….. 91

4.3 SUMMARY OF RESEARCH RESULTS……………………………… 97 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS…………... 109 5.1 CONCLUSION…………………………………………………………. 109 5.2 SUGGESTIONS FOR FUTURE RESEARCH ………………………... 117 REFERENCES………………………………………………………………… 119 APPENDICES

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LIST OF FIGURES Figure 4.1

Composition of dividend paying and non-dividend paying companies in the Main Board of Bursa Malaysia (2002-2007)…… 37

Figure 4.2

Dividend paying companies in the Main Board of Bursa Malaysia (by sector), 2002-2007…………………………………………….. 40

Figure 4.3 Type of dividend changes for dividend paying companies (2002-2007)……………………………………………………………….. 41

Figure 4.4 Average DPS of Main Board Companies, categorized by sector (2002-2007)………………………………………………………... 45

Figure 4.5 Average DPR of listed companies between 1981-2007…………… 49 Figure 4.6

Average Dividend Payout Ratio of Main Board Companies categorized by sector (2002-2007)………………………………… 50

Figure 4.7 Average Dividend Yield (%): 1981-2007…………………………. 52 Figure 4.8

Average Dividend Yield of Main Board Companies categorized by sector (2002-2007)………………………………………………… 53

Figure 4.9 DPS, EPS and DPR of Construction Sector (1998-2007)…………. 55 Figure 4.10 DPS, EPS and DPR of Consumer Sector (1998-2007)……………. 56 Figure 4.11 DPS, EPS and DPR of Industrial Sector (1998-2007)…………….. 57 Figure 4.12 DPS, EPS and DPR of Plantation Sector (1998-2007)……………. 58 Figure 4.13 DPS, EPS and DPR of Properties Sector (1998-2007)……………. 59 Figure 4.14 DPS, EPS and DPR of Technology Sector (1998-2007)………….. 60 Figure 4.15 DPS, EPS and DPR of Trading / Services Sector (1998-2007)…… 61

LIST OF TABLES Table 3.1 List of Regression Analysis………………………………………... 35 Table 4.1 No. of dividend paying companies from year 2002 to 2007………. 37 Table 4.2 Percentage of dividend paying companies by sector (Year 2002-

2007)……………………………………………………………….. 39 Table 4.3 Type of dividend changes for dividend paying companies (2002-

2007)……………………………………………………………….. 41 Table 4.4 No. of sample companies by sector (1998 to 2007)……………….. 54 Table 4.5

Regression result on dividend change events for all firm-year observations (1998-2007)………………………………………….. 68

Table 4.6

Regression result on dividend increase events for all firm-year observations (1998-2007)………………………………………….. 69

Table 4.7

Regression result on dividend decrease events for all firm-year observations (1998-2007)…………………………………………. 69

Table 4.8 Regression result on all firm-year observations, categorized by type of dividend change (1998)……………………………………. 71





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Table 4.18 Regression result on all firm-year observations categorized by type of dividend change during the financial crisis period (1998-2001).. 83

Table 4.19 Regression result on all firm-year observations categorized by type of dividend change during the post- financial crisis period (2002-2007)……………………………………………………………….. 84

Table 4.20 Regression result on dividend change events that occurred after stable dividends for 2 years, 3 years and 4 years………………….. 87

Table 4.21 Regression result on dividend increase events that occurred after stable dividends for 2 years, 3 years and 4 years………………….. 87

Table 4.22 Regression result on dividend decrease events that occurred after stable dividends for 2 years, 3 years and 4 years………………….. 87

Table 4.23

Summary on the regression result for dividend change events categorized by different sizes of dividend change………………… 88

Table 4.24 Summary on the regression result for dividend change events categorised by different sizes of dividend yield…………………… 90

Table 4.25 Multiple regression on all firm-year observations controlled by industry effect: Industrial sector as base………………………….. 93

Table 4.26 Multiple regression on all firm-year observations controlled by industry effect: Trading / Services sector as base………………… 93

Table 4.27 Multiple regression on all firm-year observations controlled by industry effect: Consumer sector as base………………………….. 94

Table 4.28 Multiple regression on dividend increase and dividend decrease sub-samples controlled by industry effect: Industrial sector as base 96

Table 4.29 Multiple regression on dividend increase and dividend decrease sub-samples controlled by industry effect: Trading / Services sector as base………………………………………………………. 96

Table 4.30 Multiple regression on dividend increase and dividend decrease sub-samples controlled by industry effect: Consumer sector as base………………………………………………………………… 97

Table 4.31 Regression result for all firm-year observations from year 1998 to 2007………………………………………………………………... 97

Table 4.32 Regression result for all dividend increase observations from year 1998 to 2007……………………………………………………….. 99

Table 4.33 Regression result for all dividend decrease observations from year 1998 to 2007……………………………………………………….. 100

Table 4.34 Multiple regression result for industry dummies………………….. 101

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LIST OF SYMBOLS AND ABBREVIATIONS The symbols and abbreviations used in this research paper and the definition of each

are illustrated below:

UE i,t : Unexpected earnings of firm i in year t E i,t : Earnings of firm i in year t MV i,0 : Market value of equity of firm i on the 1st trading day of the

announcement year EPS i,t : Earnings per share of firm i in year t P i,0 : Share price of firm i at the beginning of dividend change year

0. ∆ EPS i,t : Changes in earnings per share of firm i in year t ∆ Div i,t : Changes in dividend per share of firm i in year 0 D i,0 : Dividend per share of firm i in year t REITS : Real Estate Investment Trusts PN4 : Practice Note 4, as per Bursa Malaysia’s published practice

notes for listed companies (repealed and deleted with effect from 3 January 2005). Listed companies categorized under PN4 are companies with financial condition that does not justify continued trading and/or listing.

PN17 : Practice Note 17, as per Bursa Malaysia’s published practice notes for listed companies. Listed companies categorized under PN17 are companies with financial condition and level of operations on a consolidated basis do not warrant continued trading and/or listing as follows:- (a) the shareholders’ equity on a consolidated basis is equal to

or less than 25% of the issued and paid-up capital of the company and such shareholders’ equity is less than the minimum issued and paid-up capital as required under Bursa Malaysia’s Listing Requirements;

(b) receivers and/or managers have been appointed over the asset of the company, its subsidiary or associated company which asset accounts for at least 50% of the total assets employed of the company on a consolidated basis;

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(c) a winding up of the company’s subsidiary or associated company which accounts for at least 50% of the total assets employed of the company on a consolidated basis;

(d) the auditors have expressed an adverse or disclaimer opinion in the company’s latest audited accounts;

(e) the auditors have expressed a modified opinion with emphasis on the company’s going concern in the company’s latest audited accounts and the shareholders’ equity on a consolidated basis is equal to or less than 50% of the issued and paid-up capital of the company;

(f) a default in payment by the company, its major subsidiary or major associated company and the company is unable to provide a solvency declaration to Bursa Malaysia.

(g) the company has suspended or ceased:- (i) all of its business or its major business; or (ii) its entire or major operations, for reasons of:- (aa) the cancellation, loss or non-renewal of a licence,

concession or other rights necessary to conduct its business activities;

(bb) the disposal of the company's business or major business; or

(cc) a court order or judgment obtained against the company prohibiting the company from conducting its major operations on grounds of infringement of copyright of products etc; or

(h) the company has an insignificant business or operations IPC : Infrastructure Project Companies α0 : Constant term in the regression equation, represents the

intercept of the regression line on axis Y (dependent variables) when the value of X (independent variable) is equal to zero

α1, α2, α3…. and any other subsequent alpha values

: Beta coefficient for the independent variable and any other subsequent independent variables in the regression equation, measured on the effect of changes in independent variables on the dependent variables

∈T : Error term in the regression DPS : Dividend per share EPS : Earnings per share DPR : Dividend payout ratio which shows how much dividend is

payout from every Ringgit Malaysia of EPS. The formula for dividend payout ratio is DPS / EPS

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DY : Dividend yield which measures how much cash flow an investor can get for each Ringgit Malaysia invested in the share of a company. The formula for dividend yield is DPS / Price per share.

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CHAPTER 1: INTRODUCTION

1.1 PURPOSE AND SIGNIFICANCE OF THE STUDY

Dividend policy has become one of the major areas of research amongst the finance

scholars since 1950s. It is obvious from the research results of these scholars that

dividend decision is the most elusive and controversial in financial decision making,

hence remained unsolved with puzzles (Black, 1976). The dividend decision of a

company involves retaining a proportion of net earnings for investment needs in the

future while distributing the rest as dividend to shareholders. A good dividend policy

not only attracts investors and facilitates fund raising from the stock market; it also

caters for the future investment needs of the company. The association between

dividend decision, earnings and future investment needs therefore makes dividend

announcement a source of information to the investors in accessing the future

prospects of a company. In other words, dividend “signals” information to investors.

Majority of the studies on dividend signalling of corporations in developed markets

e.g. United States and Europe concluded with mixed results with some level of

controversial in the theory of dividend signalling. Researchers who support the theory

of dividend signalling claimed that the signalling effect from dividend announcements

help to overcome informational asymmetries between the management of a company

and investors who are less informed about the financial prospects of the company.

Investors may view an increase in dividend payout as a signal that the company has

sufficient future cash flows to meet its debt and dividend payment in the future. Such

positive signal will stimulate positive reaction from investors and further cause an

increase in the share price. (Handjinicolaou and Kalay, 1984). However, there are

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also findings that showed dividend signalling does not exist, especially in an efficient

market.

The research findings in the developed market may not applicable in Malaysia in view

of different firm characteristics such as ownership structure (Mancinelli and Ozkan,

2006), investment decision of firms (Fama, 1974) as well as the industry and market

`characteristics differentiated by industry classification (Baker, 1998). Therefore, this

research study is to examine whether Malaysian Main Board listed companies use

dividend changes to signal their future financial prospects, i.e. earnings of the

companies to the investors.

1.2 OBJECTIVE AND SCOPE OF THE STUDY

The objective of this research is to test whether dividend signalling applies in

Malaysia, given the fact that most previous studies on dividend signalling were

conducted in developed countries. Given the mixed results on dividend signalling in

developed countries, the study on dividend signalling in the context of Malaysia is

interesting due to different market structure, legal enforcement and ownership

structure in the Malaysian stock market. Hence, the objectives of this study are

generally as follows:-

(1) To study whether Main Board companies in Bursa Malaysia use changes in

dividend to convey earnings prospect of the companies

(2) To examine the effect of dividend signalling in the subsequent 5 years

following the changes in dividend, should dividend signalling is proven to

exist amongst the Main Board companies in Bursa Malaysia. In other words,

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the research will examine whether the signalling effect becomes stronger

(weaker) in subsequent years following the dividend change events.

(3) To examine whether the dividend signalling effect becomes stronger when

companies change their dividend policy after some period of stable dividend.

(4) The scope of study is further extended to examine whether the larger the

change in dividend, the stronger the signalling effect based on the behavioural

norms of investors who are more concerned with larger changes as compared

with smaller and insignificant changes in dividends,

(5) To examine the clientele effect by creating the linkage between dividend yield

and dividend signalling. Companies with higher dividend yield will place

more emphasis on dividend in their share valuations as compared with

companies with low dividend yield.

(6) To examine the “industry effect” or “peer group effect” in dividend signalling

hypothesis. Under such industry or peer group effect, a firm will adjust their

dividend decisions “to conform with the industry dividend practices” (Baker

and Powell, 2000; Baker, Veit, and Powell, 2001).

This scope of this research paper is generally to examine whether managers use

changes in dividends to signal future prospects to the investing public i.e. increase

(decrease) in earnings in the subsequent years following changes in dividends to the

investing public. The relationship between changes dividends and changes earnings is

tested by focusing the relationship between dividend changes in year 0 with future

earnings changes in the concurrent (year 0) and subsequent 5 years following the

dividend changes (year 1 to year 5) of the companies listed on the Main Board of

Bursa Malaysia.

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1.3 LIMITATION OF THE STUDY In studying the information content of dividend, changes in future earnings (following

changes in dividends), in some extent may take into account the effect of changes in

earnings in the current year. In Malaysian stock market, the announcements of

dividends and earnings are make simultaneously via the release of annual reports to

the public investors. As highlighted by Aharory and Swary (1980), the major

difficulty in studying the information content of dividend is the synchronization of

dividend and earnings announcement.

The study may not cover adequate width of studies, i.e. the size and pool of the

sample is smaller and may not sufficient for the testing of dividend signalling

hypothesis as compared with the previous studies conducted in more established stock

exchange. The smaller sample with fewer number of dividend paying companies in

each sector is due to the fact that Malaysian stock market is considered as a

developing stock market with smaller number of listed companies. Furthermore, the

number of Main Board listed companies is further eliminate in the filtering process as

(1) some companies did not pay dividends consistently throughout the years; and (2)

companies with incomplete financial information on dividends and earnings are

further eliminated from the study.

The Ordinary Least Square Regression (OLS Regression) adopted in this study has its

limitations in terms of the violation of a host of auxiliary assumptions. For instance,

the error terms in the regression equation might be (1) correlated and may not concern

the effect of outliers or (2) obtained poorly behaved error terms on estimates.

Moreover, the outcome of the OLS Regression might be skewed i.e. when the

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unexpected earnings distribution has “fat-tails” and is heavily right skewed, the

estimates generated by the OLS Regression will be driven by the data in the tails of

the unexpected earnings distribution.

Signalling theory has limitations in the form of monotonous restriction (Bernhardt,

Douglas and Robertson, 2005) by “averaging” across the changes in dividend signals,

but in fact there are many factors which can influence the result. The problem arises

when there are larger reductions in dividend signal (Bernhardt, et. al, 2005).

1.4 ORGANISATION OF THE STUDY

The study on the dividend signalling of Main Board listed companies in Bursa

Malaysia is presented in the subsequent sections. Chapter 2 summarizes the result of

the studies done by the past scholars and researchers on dividend theories and

dividend signalling. Chapter 3 explains the methodologies adopted in this research

study which include the hypotheses being tested, measurements and formulas of the

variables in the study, sampling design, data collection procedures and data analysis

techniques. Chapter 4 presents the descriptive summaries of the sample and the results

of the analysis. Chapter 5 concludes the research findings and suggests for the

possible area for future research. Chapter 6 lists down all the references in relation to

this research study.

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CHAPTER 2: LITERATURE REVIEW

2.1 WHAT IS DIVIDEND POLICY

Dividend can be defined as distribution or payment in either cash or shares to the

shareholders of the company out of the firms’ earnings (Ross, Westerfield and Jordan,

2003; Investopedia online). The decision on the amount of net earnings to be paid out

as dividend to the shareholders involves several factors to be considered such as the

firm’s current earnings, future investment needs, cash flow position, shareholders’

preferences (or composition of shareholders), market sentiment as well as dividend

decisions of other companies within the same industry. Due to the complexities

involved in dividend decision, such decision is normally determined by the top

management of the company such as chief financial officers, treasurers and board of

directors.

Dividend policy is a payout matter considered by firms in relation to when, how much

of the net earnings to be payout as dividends and in what forms the dividends to be

paid. In simpler context, dividend policy relates to the time pattern of dividend payout

(Ross et al, 2003) and is determined by the changes in earnings, after taking into

consideration of investment decisions (Lumby and Jones, 1981). We refer such

condition as “residual dividend policy”. High-growth firms will not pay out large

portion of their earnings as dividends, in view of the requirement to sustain higher

than average growth (Investopedia online). In fact, firms that increase dividends are

found to be larger and more profitable than firms that cut or maintain their dividends

(Grullon, Michaely, Benartzi and Thaler, 2005). Although dividend increase is more

frequent than dividend decrease, dividend increase is smaller in magnitude than

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dividend decrease (DeAngelo and DeAngelo, 1990; Nissim and Ziv, 2001).

There are some studies conducted on the pattern of dividend payout in other countries,

i.e. companies in the United States distribute large part of their earnings as dividends

and try to maintain a stable dividend policy. The establishment of dividend in these

companies is in accordance with the level of current earnings as well as dividends in

previous years (Lintner, 1956). However, dividend policy in emerging markets had

showed some level of differences with developed markets in which the former

pursued less stable dividend policy with lower payout ratio (Glen, Karmokolias,

Miller and Shah, 1995). But there are also cases in which Asian companies in India

and Singapore pursue a stable dividend policy (Pandey and Bhat, 1994; Ariff and

Johnson, 1994).

Many studies were conducted on the dividend policy in Malaysia. Studies in the

1990’s showed that the dividend behavior of Malaysian companies was stable and

confirmed the applicability of the Lintner model in Malaysia (Isa, 1992; Annuar and

Shamser, 1993; Gupta and Lok, 1995; Kester and Isa, 1996). However, subsequent

studies showed that dividend behavior of Malaysin companies was sensitive to

dividend changes (pursued less stable dividend policy) but do not immediately omit

dividends when earnings decreased (Pandey, 2001). Pandey (2001)’s result was

consistent with study done by DeAngelo and DeAngelo (1990), Michaely, Thaler and

Womack (1995), Nissim and Ziv (2001) and Grullon et al (2005) which showed that

dividend cuts are less common than dividend increase and more extreme in magnitude.

Following Pandey’s studies, Al-Twaijry (2007) tested the relationship between DPS

and EPS of listed companies in the Bursa Malaysia and concluded that companies

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follow dividend policies which are not strongly attached to current earnings and

negative (but insignificant) relationship was found between dividend payout ratio and

future earnings.

The following section elaborates on dividend related theories, namely the (1) dividend

irrelevance theory, (2) agency theory, (3) information asymmetry, (4) Bird-in-Hand

fallacy and (5) clientele effect.

(a) Dividend Irrelevance Theory

According to Miller and Modigliani (1961), the pattern of dividend is

irrelevant and therefore the value and the investment decisions of a firm are

independent from dividend policy in a (1) perfect and efficient market and (2)

a world without taxes and transaction costs. Under the dividend irrelevance

theory, a firm is free to determine any dividend policy in a free of tax

environment without affecting the stream of cash flows or value of the firm in

the following manner:-

(i) Pay dividend in excess of cash flows from operations and issue new

equities to finance for the dividend payment

(ii) Pay dividend less than the cash flows from operations after making

investments and the excess cash flows after paying dividends will be

used to repurchase shares (Copeland and Weston, 1988)

Under the dividend irrelevance theory, the pattern of cash flows provided by a

company through the payment of dividends is irrelevant as shareholders are

free to adjust the dividend patterns to suit their desired consumption patterns

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through the capital market (Lumby and Jones, 1981). As dividend is irrelevant

in enhancing shareholders’ wealth in a perfect capital market, the only source

to enhance shareholders’ value is through the investment decision alone.

(b) The Bird-in-Hand Fallacy

Under the theory of Bird-in-Hand fallacy, risk-averse investors prefer

dividends as compared to capital gains due to the uncertainties inherent with

capital gains. However, there are a few arguments to this Bird-in-Hand Fallacy

due to the following reasons:-

(i) The choices between current dividends and the current share price

appreciation. When dividend payment is announced by the company,

share price of the company drops slightly lower than the dividend on

the ex-dividend day.

(ii) When firm increases its dividend without changing its investment

policy, dividend payment has to be financed by issuing new shares and

hence the increase in dividend payment is offset by losing an amount

equivalent to the present value of price appreciation (Damodaran,

2001). As the risk of the firm is determined by the risk of the project

cash flow, a decrease in dividend means greater investments and

higher risk and therefore increase in the market rates of return (higher

share price) (Copeland and Weston, 1988).

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(c) Agency Theory

When there are differences in ownership and control of the company, agency

problem occurs. Managers as agents for shareholders must make their

decisions based on the objective of maximizing shareholders’ wealth. In order

to ensure their decisions are in line with the objective of maximization of

shareholders’ wealth, shareholders will incur nontrivial monitoring costs.

However, pursuing such monitoring action will create “trade-off” issue for

both shareholders and managers. Shareholders will face the trade-off between

monitoring costs and the forms of compensation involved to encourage the

agents to act in the owners’ interest. At the same time, managers also face the

trade-off between maximizing shareholders’ value and its own personal

interests by pursuing non-pecuniary interest. Selfish managers may not pay

out dividends but utilize the funds for personal compensation when the firms

are making profits. Therefore, increase in dividend payout can reduce agency

cost (Rozeff, 1982) as greater dividend payments serves as a mean in

monitoring and bonding the performance of managers. Greater dividend

payout may involve external financing i.e. through fund raising in the capital

markets and hence put the firm under greater scrutiny by the supplier of

capital besides the shareholders of the company. When a company is

controlled by a majority of insiders, there is less need to pay dividends to

reduce agency costs. At the contrary, agency cost will become higher when the

shareholding structure of a company is dispersed and hence higher dividend

payout (Rozeff, 1982).

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(d) Clientele effect

Contrary with the assumptions of perfect capital market and a tax-free world

under the dividend irrelevance theory, the concept of clientele effect exists due

to imperfection in the capital market (e.g. transaction costs, difference in

interest rates and the presence of absolute capital rationing). The imperfection

in capital market will impose certain costs to shareholders when adjustments

in the dividend patterns are made to fit his preferred consumption pattern. In

such an imperfect capital market, simple wealth maximization may not be a

unique desire for the shareholders and therefore a continuous and stable

supply of dividend is viewed positively as a source of cash inflows to match

the desired consumption pattern of the shareholders (Lumby and Jones, 1981).

The fulfillment of the shareholders’ wealth creates a consequential cost to the

company as the company may leave with insufficient funds to finance for

profitable investments. Alternatively, the company has to finance its

investment needs from external resources which involve issuance cost. As

such, companies start to maintain stable dividend policy with the hope that the

stable dividend policy will not incur heavy cost penalties.

(e) Information asymmetry

The concept of information asymmetry is related to the differences in the

amount of information held by the management and the external shareholders.

The management, being the insiders of the company has more priori

information as compared with external shareholders who have limited access

to the information of the company. Due to such differences in a world of

asymmetry information, any changes in the dividend will be interpreted as a

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costly signaling tool used by insiders of a company to convey information on

the firm’s future prospects (Bhattacharya, 1979; John and Williams, 1985;

Miller and Rock, 1985). The problem of information asymmetry is mitigated

when the ownership of a company becomes more concentrated, as such the

importance of dividend signalling is reduced (Vieira and Raposo, 2007).

Dividend policy of a firm can be measured using 2 methods: (1) dividend yield and

dividend payout ratio (Damodaran, 2001; Investopedia online). Changes in these 2

measures provide some information in relation to risks and future growth in earnings

of the company. Previous research studies showed that shares with high dividend

yields will result in excess returns, after adjusting for the market performance and risk

(Damodaran, 2001). Dividend payout ratio is used in estimating future dividends and

expected growth in earnings. When dividend payout ratio increases, the amount of

free cash flow decreases and fewer investments can be made from the available cash

flow, therefore the firm is expected to have lower growth in earnings. In other words,

high retention ratio (1-dividend payout ratio) will result in higher growth in earnings

(Damodaran, 2001).

2.2 THE DIVIDEND SIGNALLING THEORY

Dividend signalling theory suggests that dividend announcements convey information

on the firm’s future prospects (Investopedia online) by stimulating changes in share

prices which further generate returns to the shareholders. In other words, we refer this

as the “information content of dividend” as suggested by Miller and Modigliani

(1961). According to Miller and Modigliani, a company’s value is determined by its

13

expected future earnings and not on current earnings. If dividends are dependent on

the permanent component of the earnings, dividends would serve as a surrogate for

expected future earnings. The classic study on dividend signalling suggests that

current dividend is dependant on future as well as current and past earnings (Lintner,

1956). Although changes in dividends do contain some information to the investors,

dividend signalling is not universally applied to all firms (Chin, 2005).

An early study by John Lintner (1956) on dividend signalling showed that changes in

earnings will affect dividend payout and managers rarely change their dividend

payout in order to achieve the target payout ratio. Subsequent study by Fama and

Babiak (1968) also confirmed the findings by Lintner (1956) in which changes in

dividend lagged changes in earnings.

While early scholars suggested that firms use changes in dividends to convey

information on the firms’ financial prospects to the investors, some argued that firms

rarely change their dividends regardless of the earnings of the firm. The reasons of

such sticky dividend can be explained by 2 factors (Damodaran, 2001):-

(a) Concern of firms in maintaining higher dividends in the future; and

(b) Negative views on dividend decrease, which is associated with decrease in

share price

Based on the assertion of firms’ reluctant to change dividends, an increase in dividend

signals a favorable expectation on the firm’s future prospects and vice versa.

14

There are two important hypotheses related to the dividend signalling theory, namely

the free cash flow hypothesis and the maturity hypothesis. The free cash flow

hypothesis suggests that dividend signals information on investment policies of

overinvestment firms (Litzenberger and Ramaswamy, 1979). An increase in dividend

payment signals lack of investment opportunities for the firm and vice versa. The

maturity hypothesis suggests that an increase in dividend conveys information on

decreased investment opportunities, decreased return on assets and future earnings

growth rate as well as decrease in systematic risks. (Grullon, Michaely, Roni and

Swaminathan, 2002).

Using dividend as a mechanism to convey information on the firm’s profitability

involves signalling cost, especially in countries that impose taxation on both dividend

income and capital gains such as United States. When the cost of signalling becomes

higher due to higher tax rate imposed on dividend as compared to capital gains, an

increase in dividends will involve higher cost and therefore a higher return is required

to compensate for the cost of taxation involved (Brennan, 1970; Litzenberger and

Ramaswamy, 1979). In other words, firm value is more sensitive to a more costly

signal under the signalling model (Bernhardt et al, 2005). Contrary with Bernhardt’s

view, subsequent studies showed that market responses more favorably to dividend

increase when the tax rate on dividend is reduced, as experienced after the

implementation of the Tax Reform Act 1986.

The decision whether to use dividend to signal firm’s prospects to the investors may

be determined by the quality and characteristics of the firms. Firms with reputation

may rely on other lower cost communication channel rather than using dividend

15

signalling to convey information to the shareholders.

If changes in dividends signal information to the investors in an efficient capital

market, such changes will be reflected in the share prices of the firms immediately

after the dividend announcements. According to Fama (1970), a market is efficient

when it fully reflects all available information and is characterized by availability of

investment data, large pool of investors and fund managers, active trading, well-

disseminated business and financial information, appropriate degree of market

regulation and reasonably sophisticated communication system. (Lian, 2000)

2.2.1 Previous literatures that support earnings and past dividends determine

current dividends

The signalling effect of dividend has become the major debates amongst the

finance researchers and scholars. The famous dividend-signalling model in

1950s by Lintner (1956) showed that earnings of a company can be sub-

divided into permanent earnings and temporary earnings. He observed that

only changes in permanent earnings affect changes in dividends, while

temporary earnings will not have any influence on a company’s dividend

policy. Due to the nature of dividend which functions as a lagging indicator of

changes in a company’s permanent earnings, dividend payout ratio rises when

a company begins a period of bad times and falls when a company reaches a

period of good times. Further study by Aharony and Swary (1980) supported

Lintner’s model. According to their findings, quarterly dividend

announcements have information content beyond the earnings announcement,

which further supported the semi-strong form of efficient market hypothesis.

16

Lintner (1956) discovered for the first time that firms maintain a target

dividend payout ratio and adjust their dividend policies to such target. His

studies showed that current earnings of the firm and dividend in the previous

years determined the firms’ dividends. Lintner also pointed that managers

believed that investors prefer firms with stable dividend policies. Subsequent

surveys by Baker, Farrelly, and Edelman (1985) on the listed companies in the

New York Stock Exchange supported Lintner’s views with the conclusion that

the major determinants of dividend payments are current earnings and past

dividends.

Empirical evidences had shown that dividends do signal to the market on the

financial position of a company. A research study by Garrett and Priestly

(2000) showed significant evidence of dividend smoothing and dividends

convey information on unexpected positive changes in current permanent

earnings. No evidence was found to support the notion that the dividend

signals future permanent earnings. In the same year, Guay and Harford (2000)

found that relationship exists between dividend distribution with the past and

contemporary cash flow shock. Their studies were further tested by Al-

Sharaks (2005) and his findings supported the previous research done by Guay

and Harford (2000).

17

2.2.2 Previous literatures that support changes in dividends do not provide

signals to the market

A well-known finance theory on irrelevance of dividends without any

influence on the share prices of the company was introduced by Miller and

Modigliani (1961) who supported the market efficiency theory. While some

researchers have different views that the capital market is inefficient and

therefore changes in dividends provide signal to the market, Miller and

Modigliani theory suggests that changes in dividend might have information

content if there exists insider information (managers are better informed than

investors). Further studies by Watts (1973) and Gonedes (1978) showed that

there is no relationship between current dividends and future earnings.

However research done by Watts (1973, 1976a, 1976b) showed that the

hypothesis on the information content of dividend was trivial.

Although Marsh and Merton (1987) briefly considered the dividend signalling

hypothesis, they argued that dividend signalling unlikely to occur as the firm’s

specific information will be washed-out. In other words, the market efficiency

theory exists to support the study by Marsh and Merton (1987). They argued

that the dividend decisions of individual firms are not independent of the

decision of other firms in the same industry. Managers respond to the dividend

announcements of their peers, regardless of the company’s financial position

and future investment requirements. Further study by Healy and Palepu (1988)

and Benartzi et al (1997) proved the earnings reversal phenomena. The results

by Benartzi et al (1997) showed no significant relationship between changes in

dividends and changes in earnings in the subsequent years. However, changes

18

in dividends indicate changes in earnings in current year.

Using Marsh and Merton model, Kao and Wu (1994) discovered marginal

evidence of dividend signalling. Following Kao and Wu’s studies, Fudenberg

and Tirole (1995), and Vieira and Raposo (2007) proved that dividends are

sticky as managers tend to maintain their dividend per share even when the

company faces temporary net losses. Managers cut down their dividend

payment only when they are sure that the earnings will not revive. There are

researchers who viewed a dividend cut as a good news to the investors as it

shows managers’ decision to solve the firms’ financial problems (Abeyratna

and Power, 2002).

The linearity and non-linearity of the mean reversion of earnings are found to

be the elements that distinguish between the effects of dividend signalling.

Earlier study on dividend signalling by Nissim and Ziv (2001) supported for

the dividend signalling theory, however the reverse was found after

considering the non-linearity of earnings (Grullon et al, 2005). Initial test on

the relationship between changes in dividend and changes in future earnings

by assuming the linearity in the changes in earnings and controlling on the

uniform mean reversion and momentum in earnings showed that changes in

dividends convey some information about future earnings. The study by

Grullon et al (2005) showed that changes in dividends are strongly related to

concurrent earnings. His result was consistent with the empirical evidence that

changes in dividend policy occur only when changes in earnings are

substantial (Brav, Graham, Harvey and Michaely, 2003). In other words,

19

changes in dividends are considered as surrogate for non-linearity of earnings

under a uniform mean reversion model. The result by Grullon et al (2005) was

proven earlier by DeAngelo, DeAngelo and Skinner (1992) and Benartzi et al

(1997). The dividend signalling theory holds true for dividend increase based

on the study by Nissim and Ziv (2001) who found the lack of correlation

between dividend decrease and future earnings as the information content of

dividend decrease is already captured by current year earnings. Indeed, they

found that current year earnings and dividend decrease are highly correlated,

which is consistent with the result of DeAngelo et al (1992) and Benartzi, et al

(1997). Study by Benartzi et al (1997) supported the dividend signalling

theory, showing the evidence on changes in dividends provide information on

the current and past level of earnings. According to Nissim and Ziv (2001), the

negative relationship between these two variables is due to accounting

conservatism.

Besides, market characteristics also determine the extent of dividend

signalling. The usage of dividend as a signalling tool is less prominent in less

developed markets as compared with developed markets such as United

Kingdom in which current dividends are determined by lagged dividends

(Vieira and Raposo, 2007). The fact that a developed stock market with larger

pooled of investors is characterised by less concentrated ownership and the

management may use changes in dividends to convey information on firm’s

prospects to the external shareholders. In other words, the pattern of firm

ownership determines the effect of dividend signalling. Firms with

concentrated ownership may not need dividend as signalling tool (Goergen,

20

Renneboog and Silva, 2005) as concentrated ownership reduces information

asymmetries (Vieira and Clara, 2007).

The size of the dividend announcing firms also has some level of influence on

the extent of dividend signalling. According to Bajaj and Vijh (1990),

dividend announcements by large firms will not trigger large market reaction.

2.2.3 Previous literatures that support changes in dividends provide signals to

the market

Some previous studies on dividend behavior found evidence that managers use

changes in dividend as a signalling device to convey information about

unexpected shock in earnings (Bhattacharya, 1979; John and Williams, 1985;

Miller and Rock, 1985; Aharony and Dotan, 1994; Chen and Wu, 1999;

Nissim and Ziv, 2001; Arnott and Asness, 2001 and 2003; Harada and Nguyen,

2005; Baker, Mukherjee and Paskelian, 2006; Staceseu, 2006; Vivian, 2006).

The reason behind changes in dividends as a clear and unambiguous tool to

convey the future prospects of the companies lies on the fact that financial

reports of the firms only reflect past financial performance of the firms and are

manipulated by the management especially when the firms faced financial and

operational difficulties (Kaplan and Roll, 1972).

Research conducted by Yoon and Starks (1995) supported dividend signaling,

which is in turn supported by the evidence of payout asymmetries. In the same

year, Bernheim and Wantz (1995) found evidence in support of signalling

rather than agency explanations on the reasons dividends are paid.

21

Further, two research studies by Fama and French (1998) explained current

dividend payout signals future expected earnings.

Other researchers who used financial models to test the dividend signalling

and dividend behavior in the stock market such as Brickley (1983), Healy and

Palepu (1988) and Aharony and Dotan (1994) found that an increase in

dividend leads to the increase in future earnings. Research done by Aharony

and Dotan (1994) showed that firms that increase (decrease) their dividends

experience greater (smaller) unexpected changes in earnings in the subsequent

years as compared with firms that do not change their dividends. However, the

magnitude of the relationship becomes smaller when the earnings change

events move further away from the event quarter. Differences in the

magnitude of the changes in the unexpected earnings yield are discovered

under different categories of dividend change.

Some researchers tested the relationship between dividends and future

earnings with and without controlling for the effect of past and current

earnings. Nissim and Ziv (2001) proved a positive relationship between

current dividend and changes in earnings in the subsequent 2 years following

the dividend change year by controlling a particular (linear) form of mean

reversion in earnings. However, their results showed that dividend decrease

was not related to future profits. Brickley (1983) found a positive relationship

between dividend increase (decrease) and earnings increase (decrease) without

controlling for the effect of past and current earnings announcements.

22

From the above review on the historical research findings, we can conclude that there

are different views on dividend as signal on the future prospects of the company. The

reasons on the differences in findings are partly due to geographical differences

(different stock exchanges with different market characteristics / sophistication /

market liquidity), differences in companies’ characteristics (different corporate

culture or dividend policies) and industry effect.

Many research studies on dividend signalling have been done in developed countries,

but lack of research studies are conducted in developing countries such as Malaysia.

As such, there is a need to further discover on the dividend signalling of the listed

companies in Bursa Malaysia.

23

CHAPTER 3: RESEARCH METHODOLOGY 3.1 DEVELOPMENT OF THE HYPOTHESES

The information content of dividend with the underlying assumption that earnings

follow a random walk (Benartzi et al, 1997; Nissim and Ziv, 2001) is tested using the

following hypotheses:-

(A) Relationship between changes in dividends in current year with changes in

earnings in the concurrent and subsequent years:

HAo: Companies that change their dividends in year 0 will not experience

any changes in unexpected earnings in the following years, i.e. year 1

to year 5. Instead, there is a positive and significant relationship

between changes in dividends and unexpected earnings in the

concurrent year.

HA1: Companies that change their dividends in year 0 will experience

changes in unexpected earnings in the following years, i.e. year 1 to

year 5 with positive and significant relationship (Dividend signalling

exists).

The above hypothesis is further extended to test the relationship between the type of

dividend change (dividend increase and dividend decrease) with change in unexpected

earnings in the concurrent and subsequent years as follows:-

(B) Relationship between increase in dividend in current year with increase in


HBo: There is no relationship between increase in dividends in the

24

concurrent year with increase in the unexpected earnings in the

subsequent years from year 1 to year 5. Instead, there is a positive and

significant relationship between increase in dividends with increase in

unexpected earnings in the concurrent year.

HB1: There is a positive relationship between increases in dividend in the

current year with increases in the unexpected earnings in the

subsequent year 1 to year 5 (Dividend signalling exists for dividend

increase).

(C) Relationship between decrease in dividends in current year with decrease in

earnings in the concurrent and subsequent years

HCo: There is no relationship between decrease in dividends in current year

with decrease in unexpected earnings in subsequent years from year 1

to year 5. Instead, there is a positive and significant relationship

between decrease in dividends with decrease in unexpected earnings in

the concurrent year.

HC1: There is a positive and significant relationship between decreases in

dividends in the current year with decreases in the unexpected earnings

in the subsequent year 1 to year 5 (Dividend signalling exists for

dividend decrease).

The subdivision of the dividend change events into sub-groups of dividend increase

and dividend decrease is to identify the type of dividend change which has a stronger

effect on changes in earnings in the concurrent and / or subsequent 5 years following

the dividend change event, as tested in the hypothesis B and C above.

25

Further to the testing of the above hypotheses A to C, the relationship between

changes in dividends with changes in unexpected earnings was tested by each

category of years as follows:-

(a) Each individual year under the study period from year 1998 to 2007

(b) Sub-period during the financial crisis (1998-2001) and post financial crisis (2002-

2007)

(c) Case by case analysis on dividend change events that occurred after experiencing

stable dividend per share for consecutive 2 years, 3 years and 4 years.

The case by case analysis on changes in dividends that happened after some period of

stable dividends as mentioned in (c) above is tested by using the hypothesis below:-

(D) Relationship between the stability of dividend before changes in dividends

with the extent of dividend signalling

HDo: There is no relationship between the stability of dividend before

changes in dividends with the extent of dividend signalling.

HD1: There is a positive relationship between the stability of dividend before

changes in dividends with the extent of dividend signalling. The more

stable of dividend before the changes in dividend policies, the stronger

the dividend signalling.

Besides testing on the relationship between changes in dividends and changes in

earnings on a combined-year and individual-year basis, more in-depth study was

conducted on the extent of dividend signalling based on the size of changes in

26

dividends and the size of dividend yields of the companies. The rationale behind the

study on the extent of dividend signalling based on the size of changes in dividends is

that investors are more concerned with larger changes in dividends as compared with

smaller and insignificant changes. Hence the hypothesis to test the extent of dividend

signalling based on the size of dividend changes is as follows:-

(E) Relationship between the size of changes in dividends with the extent of

dividend signalling

HEo: There is no relationship between the size of changes in dividends with

the extent of dividend signalling.

HE1: There is a positive relationship between the size of changes in dividend

with the extent of dividend signalling. The larger (smaller) the changes

in dividends, the stronger (weaker) the dividend signalling effect.

In addition to the size effect of changes in dividends, study is further expanded to

examine the clientele effect by testing the relationship between the dividend yield with

the extent of dividend signalling. Naturally, companies with higher dividend yield tend

to place more weight on dividend in share valuation as compared with those companies

with low dividend yield. This is due to investors of those companies with low dividend

yield are more concerned with changes in the share price as a source of investment

gains rather than relying on dividend as investment income. Hence the hypothesis

tested is:-

27

(F) Relationship between dividend yield and the extent of dividend signalling

HF0: There is no relationship between dividend yield and the extent of

dividend signalling.

HF1: There is a positive relationship between dividend yield and the extent

of dividend signalling. The larger (smaller) the dividend yield, the

stronger (weaker) the dividend signalling.

Lastly, industry effect in influencing the extent of dividend signalling is further tested

by incorporating the effect of 3 sectors with the highest number of dividend paying

companies (namely, industrial, trading / services and consumer sector) in the

regression model.

(G) Industry effect in influencing the extend of dividend signalling

HG0: Industry effect does not have any influence on the extent of dividend

signalling of the companies.

HG1: Industry effect does exists to influence the extent of dividend

signalling of the companies

3.2 SELECTION OF MEASURES

The information content of dividends of the listed companies in the Main Board of

Bursa Malaysia is measured by using Pearson correlation and regression analysis on 2

major variables, namely the changes in unexpected earnings and changes in dividends.

The measurement of these 2 variables is shown in the formulas below:-

28

3.2.1 Measure of unexpected earnings

The unexpected earnings are measured by using the following formula as

adopted by Benartzi et al (1997).

∆UE i,t = (E i,t – E i,t-1) / MVi,0

Whereas

∆UE i,t = Changes in unexpected earnings of firm i in year t

E i,t = Earnings of firm i in year t

E i,t-1 = Earnings of firm i in year t-1

MV i,0 = Market value of equity of firm i on the 1st trading day of the

announcement year

In this study, expectation model is adopted for annual changes in earnings in

which we assume earnings follow a random walk with drift (Aharony and

Dotan, 1994).

As the above formula (adopted by the previous studies) uses absolute value,

modification has been made to reflect per share value for dividends and

earnings before extraordinary items as below:-

∆EPS i,t= (EPS i,t – EPS i,t-1) / Pi,0

Whereas

∆EPS i,t = Changes in earnings per share of firm i in year t

EPS i,t = Earnings per share of firm i in year t

EPS i,t-1 = Earnings per share of firm i in year t-1

P i,0 = Share price of firm at the beginning of the dividend

change year 0

29

The EPS of the selected sample companies are adjusted in which extraordinary

items such as gain or loss on sale of investments, land etc and diminution in

the value of investments are excluded from the computation of the bottom line

earnings, except in cases where such extraordinary items are regarded as part

of the ordinary business of the selected sample companies. The adoption of

earnings before extraordinary items is in line with the basis of measurement of

earnings as adopted by Benartzi et al (1997).

3.2.2 Measure of changes in dividends

Annual dividend is adopted in the analysis as dividends are set in response to

annual rather than quarterly earnings (Watts, 1973).

The changes in dividend are measured by the difference of dividend per share

in year t and dividend per share for year t-1, scaled by the dividend per share

in year t-1.

∆ Divi,0 = Di,0 – Di,-1 Di,-1

Whereas

∆ Divi,0 = Changes in dividend per share of firm i in year 0

Di,0 = Dividend per share of firm i in year 0

Di,-1 = Dividend per share of firm i in year -1

The changes in dividends are categorized into two dividend change subgroups,

namely (1) dividend increase and (2) dividend decrease.

30

3.3 SAMPLING DESIGN

The sample for this study consists of listed companies on the Main Board of Bursa

Malaysia, which is derived from the yearly publication of Dynaquest Sdn Bhd titled

“Stock Performance Guide” featuring historical financial and stock performance data

of listed companies on the Main Board of Bursa Malaysia. The selection criteria of

the sample are as follows:-

(i) The selected companies must be listed on the Main Board of Bursa Malaysia

since 1997 onwards with complete financial data of EPS and DPS.

(ii) Companies in the Finance, REITS and Closed-End Funds sectors are excluded

from the study to improve homogeneity of the sample as these companies have

very high leverage with different rules for income measurement. Such

selection criterion follows the selection method adopted by Pandey (2001),

Grullon et al (2003) and Short, Zhang and Keasey (2002).

(iii) Companies that are categorised under PN4 and PN17 will be excluded from

the study. A firm being categorised under PN4 is a company with its assets

consist of 70% or more of cash or short term investments. The inclusion of

these companies in the analysis will jeopardise the result as companies with

abundant of cash may distribute large portion of its retained earnings as

dividends, regardless of the losses experienced by the company. Whereas a

PN17 companies are financially distressed companies in which the possibility

of division omission is very high.

(iv) Companies categorized under the IPC, Hotels and Mining are excluded from

the study due to its relatively small number of companies under each sector.

31

(v) The selected companies must pay at least 2 consecutive years of dividends to

enable calculation of yearly changes in dividends. Dividend initiations and

dividend omissions are excluded from the study.

(vi) The selected companies must have financial information on the changes in

EPS for the current and future five years after the dividend payment year.

(vii) Companies with other distribution events such as stock splits or a stock

dividends declared around the declaration of the current dividend will be

excluded from the study (Grullon et al, 2003; Aharony and Dotan, 1994;

Nissim and Ziv, 2001). The selection criterion is to minimize any

contaminating announcements effect as such distribution events will affect the

per unit share price, which is used as the denominator in measuring changes in

earnings.

3.4 DATA COLLECTION PROCEDURES

The analysis to test the relationship between changes in dividends in year 0 (year 0 is

the dividend change year) and changes in earnings in year 0 and 5 years following the

dividend change year (year 1 to year 5) requires data on EPS and DPS from year 1997

until year 2007 and share price on the beginning of the dividend change year from

year 1998 to 2007. All these data are obtained from the latest yearly publication of

Dynaquest Sdn Bhd - “Stock Performance Guide” which features all the Main Board

listed companies in Bursa Malaysia.

32

3.5 DATA ANALYSIS TECHNIQUES 3.5.1 Data Filtering

The final list of sample companies was obtained by going through 4 stages of

filtering to ensure that the final list of the samples contained only companies

with complete financial data for regression analysis.

1st stage : Filtering of dividend paying and non-dividend paying

companies

Companies that did not pay dividends in each individual year

for the period 1998 to 2007 were excluded from the study.

The process of filtering by excluding companies with DPS=0

on each individual year 0 involves the filtering of dividend

omission events at the same time should DPS is more than 0

in year –1.

2nd stage : Filtering of dividend initiation events

Companies with DPS more than 0 in year 0 but DPS equals

to 0 in year –1 were excluded from the study.

3rd stage : Filtering of companies in the sector of Finance, IPC,

Mining, Hotels, REITS and Closed-End Funds

Companies in the sector of Finance, IPC, Mining, Hotels,

REITS and Closed End Funds were further excluded from

study in view of the different accounting procedures adopted

by Finance companies and the relatively small amount of

companies categorized under the sector of IPC, Mining,

Hotels, REITS and Closed-End Funds.

33

4th stage : Filtering out companies with incomplete financial data

The final stage of the filtering process is to filter out those

companies without complete data on changes in earnings

from year 0 to year 5 due to changes in financial years.

The initial sample of dividend paying companies after the filtering process

consists of 2,679 firm-year observations.

3.5.2 Assumptions adopted in the regression analysis

Prior to regression analysis, the following assumptions must be fulfilled to

ensure reliability of the regression results (Coakes and Steed, 2007)

(1) Minimum number of cases for analysis must be at least five times of

independent variables. The ideal number of cases must be twenty times

more than the number of predictors.

(2) Outliers are deleted or modified to minimize the influence on the result

of the regression.

(3) No multicollinearity and singularity between the independent variables

for multiple regressions.

(4) Variables must fulfill the assumption of normality, linearity,

homoscedasticity and independence of residuals.

All the variables have fulfilled the above assumptions as the number of cases

is large (more than 2,000 cases). The normality on all the variables used in the

regression analysis, namely changes in dividends in year 0 and changes in

34

earnings in the concurrent year and 5 years after the dividend change year

(year 1 to year 5) were tested and identified through the value of skewness,

kurtosis and Kolmogorov-Smirnov test. Outliers were identified through the

generation of boxplots during the normality test by using SPSS.

Initial normality test on all the variables used in the regression analysis

showed some variables were not normally distributed with skewness value

more than 3, high value of kurtosis and Kolmogorov-Smirnov value at

significant level p<0.05. To improve the normality of the variables, outliers

were identified from the boxplots generated from the SPSS program and were

further eliminated from the samples. The elimination of outliers from the

samples has helped in reducing the value of skewness and kurtosis.

Berry and Feldman (1995) pointed out that the most important regression

assumption is related to residuals. A residual plot is used to check the

assumption of independence of error terms in the regression. Examination on

the pattern of the scatter plot of residuals against predicted values for each of

the regression showed random and patternless residuals with no clear

relationship of both variables and hence consistent with assumption (4) above.

3.5.3 Analysis on the relationship between changes in dividends in year 0 with

changes in earnings in the concurrent year and subsequent 5 years

The analysis technique adopted in this study is regression analysis. In

analyzing the variables using the regression analysis, 2 categories of dividend

changes are identified namely “INCREASE” and “DECREASE”. The

35

relationship between changes in DPS in year 0 and changes in EPS in the

concurrent and subsequent 5 years after the dividend change year (year 1 to

year 5) are explored by using the regression formulas as adopted by Nissim

and Ziv (2001):-

(EPSi,t – EPS i,t-1) / P i,0 = α0 + α1 ∆Divi,0 + ε T

Whereas

EPSi,t = EPS of firm i in year T= 0, 1, 2, 3, 4 and 5

P i,0 = Share price of firm i at the beginning of dividend change year 0

∆Divi,0 = (DPSi,0 – DPSi,-1) / DPSi,-1in which DPSi,0 = DPS of firm i in

year 0 and DPSi,-1= DPS of firm i in year -1

ε T = Error term of the regression

The list of univariate regression analysis adopted to test the relationship

between changes in dividends with changes in earnings is summarized in

Table 3.1.

Table 3.1 List of Regression Analysis

Regression No. Independent Variable Dependent Variable

Et+0 Changes in DPS in year 0 Changes in EPS in year 0 Et+1 Changes in DPS in year 0 Changes in EPS in year 1 Et+2 Changes in DPS in year 0 Changes in EPS in year 2 Et+3 Changes in DPS in year 0 Changes in EPS in year 3 Et+4 Changes in DPS in year 0 Changes in EPS in year 4 Et+5 Changes in DPS in year 0 Changes in EPS in year 5

36

3.5.4 Analysis on the extent of dividend signaling with the influence of industry

effect using multiple regression

In examining whether differences in the changes in earnings exists between

two sectors with the highest number of dividend paying companies when these

2 sectors experienced changes in dividends, multiple regression analysis was

adopted in this study. 2 sector dummies were incorporated to capture any

differences that exist between 2 sectors which were measured by the beta

coefficient of these sector dummies. The multiple regression equation used is

illustrated below:-

(EPSi,t – EPS i,t-1) / P i,0 = α0 + α1 ∆Divi,0 + α2 Dummya + α3 Dummyb + ε T

Whereas

EPSi,t = EPS of firm i in year T= 0, 1, 2, 3, 4 and 5

P i,0 = Share price of firm i at the beginning of dividend change year 0

∆Divi,0 = (DPSi,0 – DPSi,-1) / DPSi,-1in which DPSi,0 = DPS of firm i in

year 0 and DPSi,-1= DPS of firm i in year -1

Dummya = Dummy for sector a

Dummya = Dummy for sector b


All the regression equations above will be tested using the regression function in the

SPSS program.

37

CHAPTER 4: RESEARCH RESULTS 4.1 SUMMARY STATISTICS

4.1.1 Overall Dividend Payment Trend of Main Board Listed Companies in

Bursa Malaysia

The initial list of Main Board listed companies (excluding PN4 and PN17

companies) for year 2007 consists of 632 companies. Since 2002, the number

of dividend paying companies listed on the Main Board of Bursa Malaysia

showed a continuous increase year to year from 67.6% in 2002 to 75% in year

2007. Further detail of the number of dividend paying companies listed on the

Main Board is demonstrated in Table 4.1 and Figure 4.1.

Table 4.1 No. of dividend paying companies from year 2002 to 2007

Year Total company No. of dividend paying companies % 2002 497 336 67.6% 2003 542 376 69.4% 2004 576 406 70.5% 2005 603 444 73.6% 2006 617 449 72.8% 2007 632 474 75.0%

Figure 4.1

0%

20%

40%

60%

80%

100%

Per

cent

2002 2003 2004 2005 2006 2007

Year

Composition of dividend paying and non-dividend paying companies in the Main Board of Bursa Malaysia (2002-2007)

No. of dividend paying companies No. of non-dividend paying companies

38

More than 50% of the dividend paying companies listed on the Main Board

came from 3 major sectors, namely Industrial, Trading / Services and

Consumer sector, with each sector being the first, second and third sector with

the highest number of dividend paying companies in year 2007. The

percentage of the dividend paying companies from the Consumer sector

remained at more than 80% since year 2002, with the highest percentage of

dividend paying companies recorded in year 2005 (88%). As can be seen from

Table 4.2, the Mining sector continued to become a 100% dividend paying

sector in the Main Board of Bursa Malaysia for 5 consecutive years since 2003,

as there is only 1 company listed under this sector. Excluding Mining sector, 3

sectors with the highest percentage of dividend paying companies for the past

2 years since 2006 were the Consumer, Finance and Technology sector with

more than 80% of the companies in these sectors paying dividends. 2 sectors

that experienced continuous increase in the percentage of dividend paying

companies in each sector since year 2002 are the Industrial and IPC sector.

Hotels sector continued to maintain its percentage of dividend paying

companies at 60% across the years since 2002. 3 sectors with the lowest

percentage of dividend paying companies for the part 2 years since 2006 were

the Closed-End Funds, Properties and Hotels sectors. A study on the trend of

percentage of dividend paying companies showed that a total of 5 sectors

(Consumer, Industrial, Construction, Trading / Services, Properties and

Plantations) experienced decrease in the percentage of dividend paying

companies in year 2006, which recorded the highest number of sectors with

reduced dividend paying companies. This may be caused by unfavorable

outlook on the domestic and global economy which is under the threat of

39

recession with the contagion from the United States financial chaos spreading

worldwide. The Malaysian economy was expected to slow down in year 2008

and 2009 due to the faltering economy and the impact of higher commodity

prices. Based on the data extracted from the 23rd National Economic Briefing

2008 of Malaysian Institute of Economic Research, the Real GDP growth rate

in year 2008 and 2009 is forecasted at 4.6% and 5.0%, respectively, as

compared with 6.3% recorded in year 2007. Further information on the

categorization of dividend paying companies by sector is shown in Table 4.2

and Figure 4.2.

Table 4.2 Percentage of dividend paying companies by sector (Year 2002-2007)

Year 2002 2003 2004 2005 2006 2007 Sector % % % % % %Consumer 80.3 87.0 81.0 88.0 85.5 85.5Industrial 70.8 71.1 73.0 74.5 74.3 74.3Construction 59.4 64.9 65.0 77.5 68.3 71.1Trading/Services 60.6 62.5 65.9 70.2 68.7 70.8Technology 91.7 71.4 81.3 76.5 82.4 82.4IPC 33.3 33.3 33.3 42.9 71.4 75.0Finance 71.4 69.4 75.0 79.5 82.1 82.5Hotels 60.0 60.0 60.0 60.0 60.0 60.0Properties 59.7 61.4 59.8 62.5 60.2 59.3Plantations 76.3 80.0 80.0 80.0 79.1 80.4Mining 0.0 100.0 100.0 100.0 100.0 100.0REITS 100.0 100.0 100.0 40.0 55.6 76.5Closed-End Funds 0.0 0.0 100.0 0.0 50.0 50.0Total dividend paying companies 67.6 69.4 70.5 73.6 72.8 75.0

40

Figure 4.2

0%

20%

40%

60%

80%

100%

P erc

e nt

2002 2003 2004 2005 2006 2007

Year

Dividend paying companies in the Main Board of Bursa Malaysia (by sector), 2002-2007

Consumer Industrial Construction Trading/Services Technology

IPC Finance Hotels Properties Plantations

Mining REITS Closed-End Funds

As shown in the Table 4.3 and Figure 4.3, the number of dividend increase

(which contains dividend initiation) for the period 2002 to 2007 was higher

than dividend unchanged (approximately 52% to 69% of total dividend

changes for dividend increase as compared to approximately 15% to 27% of

total dividend changes for dividend decrease). Dividend decrease only formed

not more than 30% of the total dividend change case, with the highest number

of dividend cuts were experienced in year 2006 (26.7% of the total dividend

change case). This is prominent that the Malaysian Main Board companies

tend to increase dividends and rarely pursue on dividend cut.

41

Table 4.3 Type of dividend changes for dividend paying companies (2002-2007)

Dividend increase

Dividend Unchanged

Dividend decrease

Year

No. of dividend paying

companies Total % Total % Total % 2002 336 175 52.1% 97 28.9% 64 19.0% 2003 376 219 58.2% 91 24.2% 66 17.6% 2004 406 234 57.6% 100 24.6% 72 17.8% 2005 444 259 58.3% 102 23.0% 83 18.7% 2006 449 220 49.0% 109 24.3% 120 26.7% 2007 474 328 69.2% 74 15.6% 72 15.2%

Figure 4.3

0%20%40%60%80%

100%

Perc

ent

2002 2003 2004 2005 2006 2007

Year

Type of dividend changes for dividend paying companies (2002-2007)

Dividend increase Dividend Unchanged Dividend decrease

Analysis on DPS of all Main Board companies for the period 2002 to 2007 As illustrated in Appendix 1, three sectors that pay the highest average DPS

for the past two years of 2006 and 2007 were the Consumer (2006: 17.52 sen,

2007: 15.46 sen), IPC (2006:11.92 sen; 2007: 20.50 sen) and Finance (2006:

12.39 sen; 2007:18.99 sen). IPC experienced the highest increase in the

average DPS paid since 2006, recorded an increase of 2.13 times in the

average DPS paid in 2006 of 11.92 sen as compared with average DPS of 5.60

42

sen in 2005. Major reason behind the huge leap in the average DPS of the IPS

sector was attributable to the increase in the earnings of all the dividend

paying IPC companies, especially from the telecommunication sector.

Being the sector with the 3rd highest number of dividend paying companies,

the Consumer sector recorded the highest DPS paid from year 2002 to 2006,

with the highest DPS of RM3.29 and average DPS of 18.75 sen recorded in

year 2003. Due to its larger number of dividend paying companies, the

standard deviation of DPS was the highest among the sectors, recording a

standard deviation of more than 30 sen since 2002. Continuous high DPS for

the Consumer sector since 2002 was attributable to the increase in earnings of

the companies due to increase in exports for certain consumer goods since

year 2002 such as household electrical appliances, food, beverages and

tobacco (Bank Negara Malaysia Monthly Statistical Bulletin, July 2008) as

well as increase in production of consumer goods.

On average, the Industrial sector, which is the sector with the highest number

of dividend paying companies, paid an average DPS which was lower than the

average DPS of all dividend paying companies since year 2002. The reason of

lower DPS in the Industrial sector was due to companies in the Industrial

sector are asset-based companies with most assets held in the form of

investment in machinery which requires huge cost of investment and

maintenance, hence not much cash reserves can be distributed to shareholders

as dividends. The same phenomena of lower average DPS as compared with

the average DPS paid by all listed companies was also experienced by the

43

Trading / Services sector since year 2003.

Companies in the Technology and Hotels sectors experienced quite stable

average DPS for the past 3 years since 2005 as shown by the standard

deviation of DPS in these sectors. The Technology sector recorded an average

DPS between 7.5 to 8 sen with a standard deviation of 10 sen for 3

consecutive years, while the Hotel sector continued to record an average DPS

of 3 sen per share with a standard deviation of between 2.3 sen to 2.5 sen for

the past 3 years since 2005.

On average, the average DPS of the Property sector were lower than the

average DPS paid by all Main Board listed companies for the past 6 years due

to its higher cash flow requirement to finance the property development

projects. An interesting trend discovered for the dividend payment trend of the

companies in the Properties sector in the period of 2002 to 2007 was that this

sector tends to maintain its dividend payment for the 2 consecutive years and

revise after each 2 years. In the period of 2002 to 2003, the average DPS was 4

sen with a standard deviation of 5 sen. For the period of 2004 to 2005, the

average DPS recorded was between 5 sen to 6 sen, with a standard deviation

of 5 to 6 sen, while for the period of 2006 to 2007, the average DPS was

between 6 to 7 sen with standard deviation of 8 sen. Overall the Properties

sector experienced continuous increase in dividend payment from year to year.

Based on the above analysis on the trend of DPS amongst the sectors, the

variations in the DPS amongst the sectors can be attributable to the following

44

factors:-

a) Industry effect as companies within the same industry or sector tend to

adjust their dividend in tandem with the industry norms.

b) Difference in the financial performance of the industries / sectors,

attributable to the change in economic landscape and government

policies. For instance, expected slowdown in the world economies

such as the United States which is the major importer of electronic and

electrical products. The slowdown of the economy in the United States

may affect the revenue of Industrial sector due to decrease in exports.

Should the government emphasized on domestic oriented growth rather

than export oriented growth in the economy by stimulating private

consumptions, the revenues of companies in the Industrial sector may

be severely affected while the companies under the Consumer sector

will benefit from the increase in consumer expenditures. Differences

in the financial performance of these 2 sectors will further cause the

dividend of these sectors vary, in which Industrial sector will

experience lower DPS as compared with higher DPS of the Consumer

sector.

c) Nature of the industry whether the industry is an asset-based or capital-

intensive industry which requires huge investments in assets such as

machinery. Such sectors (for instance Industrial and Property sectors)

require large amount of cash to be invested in fixed assets and hence

lower dividends are paid as compared with less capital-intensive

industry such as Finance sector.

45

Figure 4.4

Analysis of DPR of all Main Board companies for the period 2002 to 2007 As shown in Appendix 2, the average market DPR for all Main Board listed

companies showed a volatile trend. Average market DPR of all the dividend

paying companies listed on the Main Board experienced huge variance in year

2002 to 2003, with the highest DPR recorded in year 2003 (average market

DPR was 0.56). Subsequently after year 2003, the average market DPR of the

Main Board listed companies decreased due to the unfavorable economy

outlook of the Malaysia economy in which the real GDP fall below 6% for 2

consecutive years after year 2004. For the period of year 2004 to 2005,

average market DPR was below 0.40 (2004: 0.36; 2005: 0.32). Following the

Average DPS of Main Board Companies, categorized by sector (2002-2007)

0

5

10

15

20

25

2002 2003 2004 2005 2006 2007

Year

RM

(sen

)

Consumer Industrial ConstructionTrading/Services Technology IPCFinance Hotels PropertiesPlantations Mining REITSClosed-End Funds Main Board Companies

46

drop in the average market DPR in year 2004 and 2005, the average market

DPR started to increase to more than 0.50 for year 2006 and 2007, due to

favorable stock market condition. During this period, the Kuala Lumpur

Composite Index recorded more than 1,000 points (2006: 1,096.24; 2007:

1,445.03).

Overall, the average DPR of the 3 major sectors with the highest number of

dividend paying companies, namely the Industrial, Trading / Services and

Consumer sector for the past 2 years since 2006 were in tandem with the

average DPR of all the Main Board companies of between 0.50 to 0.60.

Observation on the DPR trends on these 3 major dividend paying sectors from

year 2002 to 2007 showed that the DPR trends were very volatile, especially

between the period 2002 to 2004 in which these sectors experienced the same

volatile swing in the market DPR. Trading/ Services sector, for instance,

experienced huge decrease in the average DPR from 0.57 to 0.28 between the

period of 2002 and 2003.

The average DPR of Construction sector was below the average DPR of the

overall Main Board companies, recorded an average DPR of between 0.31 to

0.38 since 2006 as compared with the average market DPR of between 0.5 to

0.54 for the past 2 years.

Technology, IPC, Hotels and Mining sectors continued to experience decrease

in the DPR year to year for the past 3 years since 2005. The average DPR of

the Technology sector was very low in the period of 2002 to 2003 but started

47

to pick up in year 2004, recorded the highest average DPR of 0.56 in year

2005 and started to decrease year to year after year 2005. Although the trend

of average DPR for the IPC and Hotels sectors were not as volatile as the

Technology sector, however, the average DPR of these sectors were lower

than the overall average DPR across the Main Board companies for the past 2

years since 2006. For the Plantation sector, the highest average DPR of 0.65

were recorded in year 2005 but started to decrease thereafter with its average

DPS in year 2006 and 2007 fall below the average market DPR of 0.50.

Finance sector was one of sectors with the most volatile average DPR across

the years since 2002 and its average industry DPR trend were not in tandem

with the overall market DPR. The highest average DPR recorded was 0.84 in

year 2002 while there were two-year record of negative average DPR in year

2003 and 2005 (2003:-0.07; 2005:-1.33). The negative value of DPR indicates

that on average, companies within the Finance sector pay dividends despite of

their negative earnings before extraordinary items recorded in these years.

Dividend payments were made despite of losses experienced by companies in

the Finance sector mainly due to the fulfillment of shareholders’ requirements

for higher dividends attributable to slowdown in the economy. Real GDP

growth in year 2003 and 2005 were 5.8% and 5.3% respectively, which were

lower than the 6.8% real GDP growth in year 2004. In addition, the overall

stock market performance of the Kuala Lumpur Stock Exchange was below

the 1,000 points. For instance the Kuala Lumpur Composite Index (KLCI)

recorded in year 2003 and 2005 were 793.94 and 899.79 respectively, which

were lower than the KLCI of 907.43 recorded in year 2004. In view of the

48

unfavorable economy and stock market condition, we can conclude that the

payment of dividend despite of losses experienced by most finance companies

can be attributable to the fulfillment of investors’ demand for higher dividend

to offset their capital losses in the stock market.

Average DPR for the Properties sector was in tandem with the overall market

trend of DPR for the period between 2002 to 2007, with the lowest average

DPR of 0.16 recorded in year 2004 and quite stable at the average DPR of

between 0.40 to 0.60 for the past 3 years since 2005.

The average DPR of companies under the REITS and Closed-End Funds were

above the overall market DPR, with the average DPR of these sectors for the

past 3 years at approximately 0.70 as compared with the average market DPR

of approximately 0.50.

A further comparison with the average DPR of listed companies listed in the

Kuala Lumpur Stock Exchange in the 1980s and early 1990s done by Isa

(1993) is showed in the Figure 4.5.

49

Figure 4.5

As shown in Figure 4.5, the lowest average DPR was recorded in year 2005

(0.32), which was lower than the average DPR of 0.49 achieved in the 1980s

and average DPR of 0.46 recorded in early 1990s. As can be observed from

the above trend on the average DPR (except for the lowest average DPR

achieved in year 1984 and 1989), before the year of 1989, the average DPR of

listed companies in the Kuala Lumpur Stock Exchange was approximately

0.60. After the year 1989, the trend of the average DPR of listed companies

was very volatile. Without taking into account the lowest average DPR

recorded after year 1989, the average DPR of listed companies in the Bursa

Malaysia was lower than the pre-1989 period, recorded an average DPR of

approximately 0.50.

Average DPR of listed companies between 1981-2007

0.56

0.5

0.54

0.32

0.36

0.37

0.5

0.46

0.52

0.49

0.56

0.58

0.64

0.6

0.49

0.560.580.59

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 2002 2003 2004 2005 2006 2007

Year

Average DPR

50

Figure 4.6

Average Dividend Payout Ratio of Main Board Companies categorized by sector (2002-2007)

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

2002 2003 2004 2005 2006 2007

Year

Consumer Industrial Construction

Trading/Services Technology IPC

Finance Hotels Properties

Plantations Mining REITS

Closed-End Funds Main Board Companies

Analysis of DY of all Main Board companies for the period 2002 to 2007

Dividend yield (DY) is a financial ratio which measures the amount of cash

payout by the company in the form of dividend relative to its share price. In

other words, it measures how much cash flow an investor can get for each RM

invested in the shares of the company. The DY can be defined as the return of

investment to the investors should the capital gains do not exist.

As shown in Appendix 3, the average DY of all Main Board listed companies

was not more than 4% for the past 6 years since 2002, with the highest market

average DY occurred in year 2006 (3.58%). Overall the trend of the market

51

average DY for Main Board companies was quite stable.

The average DY of 3 major sectors with the highest number of dividend

paying companies, namely the Industrial, Trading / Services and Consumer

sectors were in tandem with the average market DY for all Main Board

companies between the period of 2002 to 2007, with the Consumer sector

experienced slightly higher dividend yield than Industrial and Trading /

Services sectors. Overall, all sectors (except REITS) recorded an average DY

of not more than 4.5% for the period 2002 to 2007 with the Mining sector

recorded the lowest dividend yield (not more than 2% within the period of

2002 to 2007). The REITS sector consistently recorded highest average DY

across the sectors for the period 2002 to 2007, with the average DY ranging

from 3.53% to 5.8%, which were higher than the average market DY during

the same period.

A further comparison with the research result by Isa (1993) on the average DY

of listed companies in Bursa Malaysia between year 1981 to 1992 is illustrated

in Figure 4.7.

52

Figure 4.7

Average Dividend Yield (%) : 1981-2007

4.7

2.84

3.233.34

3.583.47

2.84

3.18

2.81

3.26

2.782.63

3.47

4.03

3.353.28

4.49

3.8

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

2002

2003

2004

2005

2006

2007

Year

Aver

age

divi

dend

yie

ld (%

)

Average Dividend Yield (%)

As can be observed from Figure 4.7, the average market DY for all listed

companies in the Bursa Malaysia was quite volatile before 1990s, with the

highest average DY recorded in year 1986 (4.7%). The average market DY

started to decrease starting from year 1987, maintained at approximately

between 3% to 4% post 1987 period.

53

Figure 4.8

Average Dividend Yield of Main Board Companies categorized by sector (2002-2007)

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

2002 2003 2004 2005 2006 2007

Year

Perc

ent (

%)

Consumer Industrial Construction

Trading/Services Technology IPC

Finance Hotels Properties

Plantations Mining REITSClosed-End Funds Main Board Companies

4.1.2 Descriptive summary on the selected samples

The sample of the study consists of 2,679 firm-year observations on dividend

change events that occurred from year 1998 to 2007. The breakdown on the

firm-year observations in each sector from year 1998 to 2007 is summarized in

Table 4.4.

54

Table 4.4 No. of sample companies by sector (1998 to 2007)

No Sector No. of firm-

year observations

% DPS (sen)

DPR

DY (%)

1. Industrial 706 26.35 5.74 0.34 2.88 2. Trading/Services 605 22.58 6.24 0.35 2.52 3. Consumer 459 17.13 12.07 0.44 3.28 4. Properties 378 14.11 5.43 0.33 2.82 5. Plantations 247 9.22 9.11 0.43 2.99 6. Construction 188 7.02 4.49 0.27 2.40 7. Technology 96 3.58 7.83 0.37 2.31 Total 2,679 100.00 7.28 0.36 2.74

As shown in Table 4.4 above, 3 sectors that pay the highest average DPS for

the period under study were the Consumer sector (Mean = 12.07 sen),

Plantation sector (Mean = 9.11 sen) and Technology sector (Mean = 7.83 sen).

In terms of DPR, Consumer, Plantation and Technology sectors remained as

the top 3 sectors with the highest average DPR of 0.44, 0.43 and 0.37

respectively. The average DY for all the sectors for the period under study was

not more than 4%, with the Consumer sector being the sector with the highest

DY (3.28%), followed by Plantation sector (2.99%) and Industrial sector

(2.88%).

55

Figure 4.9

DPS, EPS and DPR of Construction Sector (1998-2007)

0.25

0.21 0.21

0.29

0.24

0.29 0.29

0.33

0.300.27

0.00

5.00

10.00

15.00

20.00

25.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DPS

/ E

PS

(RM

sen

)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

DP

R

DPS (sen) EPS (sen) DPR

From Figure 4.9 above, the Construction sector recorded quite stable DPS

across the years. The average DPR of the Construction sector followed the

trend of earnings, except in year 1999, 2003 and 2007. Lowest DPR was

recorded in year 1999 and 2000 due to the economic downturn which caused

the delay in most construction projects and tight cash flows of construction

companies. However, higher EPS in the period of 1999 and 2000 despite the

slowdown in the economy was due to accounting transaction related to the

recognition of income for the construction activities. As can be observed from

the trend of the DPR, the period between 1998 and 2002 showed a volatile

trend due to the uncertainty in the economic condition as the world economy

was still in the process of recovery. However, starting from year 2003, the

average DPR was quite stable at the 0.30 threshold with a slight decrease in

56

average DPR in year 2007 due to delay of government projects, oversupply of

medium and high cost properties and increase in the price of raw materials,

which further affected the earnings of the construction companies.

Figure 4.10

DPS, EPS and DPR of Consumer Sector (1998-2007)

0.420.39 0.38 0.38

0.44

0.35

0.500.45

0.600.55

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S / E

PS

(RM

sen

)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

DP

RDPS (sen) EPS (sen) DPR

Figure 4.10 above shows the average DPS of the Consumer sector was quite

stable before the year of 2003 despite the economy recovery process which

occurred in these period. On average, the DPS and DPR of the Consumer

sector before year 2003 was approximately 12.5 sen and 0.40 respectively.

However, volatile trends were observed starting from year 2003 for both

average DPS and DPR, attributable to the swing in the earnings of the

companies. Lowest DPR occurred in year 2003 (0.35) due to the lowest EPS

recorded in the study period (24.2 sen). Subsequent to year 2003, the average

57

DPR of the Consumer sector recorded between 0.45 to 0.60, despite the lower

average EPS as compared with the pre-2003 period. The highest average DPR

was recorded in year 2006 of 0.60. It is obvious that the Consumer sector, on

average increased its DPR despite the lower earnings experienced post-2002

period, in response to favorable stock market conditions after year 2003. The

Kuala Lumpur Composite Index showed a continuous increase post-2003

period from 907.43 in year 2004 to 1,445.03 in year 2007.

Figure 4.11

DPS, EPS and DPR of Industrial Sector (1998-2007)

0.32 0.33

0.26

0.340.31

0.35

0.290.33

0.40

0.45

0.00

5.00

10.00

15.00

20.00

25.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S /

EP

S (R

M s

en)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

DPR


From Figure 4.11 above, the Industrial sector recorded quite stable DPS across

the years from 1998 to 2002. Highest DPS and DPR were achieved in year

2007 when the earnings recorded its highest level in year 2007. The average

DPR trend pre-2004 period showed volatile trend with average DPR ranging

58

from as low as 0.26 to as high as 0.35. Subsequently starting from year 2004,

the trend of the average DPR and DPS showed a continuous increase due to

higher average EPS achieved by companies in the Industrial sector as well as

the favorable stock market condition which started to breach the 900 points

towards 1,000 points of Kuala Lumpur Composite Index starting from year

2004.

Figure 4.12

DPS, EPS and DPR of Plantation Sector (1998-2007)

0.300.36

0.51

0.58

0.430.38

0.43

0.60

0.50

0.40

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S /

EPS

(RM

sen

)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

DPR


Figure 4.12 above showed that the trend of the DPS was in tandem with the

trend of the earnings with minor adjustments taken into account changes in

earnings. However, the trend of the average DPR was very volatile with

exceptional high average DPR recorded in year 2001 (0.58) despite the lowest

EPS recorded in year 2001, attributable to the favorable outlook of the prices

of commodities such as rubber and oil palm. The highest DPR of 0.58

59

recorded in year 2001 was followed by subsequent increase in the average

EPS in the following 3 years from year 2002 to 2004, indicating the increase

in the DPR comprised forward looking information on the future earnings of

the companies. Subsequent decrease in the DPR to 0.43 in 2002 and 0.38 in

2003 despite the increase of earnings in these years was attributable to the

predicted decrease in the market price of commodities in the subsequent years

ahead, as can be observed from the decrease and stabling of the average EPS

in year 2005 and 2006. The cyclical trend of the DPR for every 5 to 6 years

can be attributable to the capital expenditure requirements in obtaining new

land for the cultivation of crops as well as the reservation of cash in hand for

daily operating expenses while the crops are waiting to be harvested.

Figure 4.13

DPS, EPS and DPR of Properties Sector (1998-2007)

0.29 0.27

0.31 0.310.34

0.310.34

0.370.39 0.38

0.00

5.00

10.00

15.00

20.00

25.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S /

EP

S (R

M s

en)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

DPR


60

Figure 4.13 shows that the trend of DPS in the Properties sector was quite

stable with minor adjustments in accordance with changes in earnings. The

DPR trend was in tandem with the trends of the earnings. The average DPR of

the Properties sector showed gradual increase from 0.29 in year 1998 to 0.38

in 2007. In conclusion, the trend of the DPR and DPS of the overall properties

sector are very stable in tandem with the growth in the earnings of the property

companies.

Figure 4.14

DPS, EPS and DPR of Technology Sector (1998-2007)

0.21

0.270.30

0.44

0.280.31

0.55

0.50

0.56

0.47

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S /

EPS

(RM

sen

)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

DP

R


From the trend of DPS as shown in Figure 4.14 above, companies within the

Technology sector tends to make adjustments in its DPS in tandem with the

trend of the average earnings in the industry. The trend of the average DPR in

the Technology sector were very volatile, same as its trend of average

61

earnings. Lower DPR (0.28) was achieved in year 2002 when the average

earnings of the whole industry recorded the lowest level of 13.90 sen per

share. DPR of the Technology sector was less than 0.30 before year 2000 with

volatile swing in DPR between the period 2001 to 2004. Stable trend of DPR

was observed post-2005 period with average DPR at between 0.47 to 0.56,

indicating that most companies that listed in the MESDAQ since year 2000

had achieve their maturity lifecycle with abundant cash for distribution to the

shareholders. Overall, the Technology sector is a capital-intensive sector

which requires extensive in research and development, hence the average DPR

swings in accordance with the capital requirements of the companies for future

investment purposes.

Figure 4.15

DPS, EPS and DPR of Trading / Services Sector (1998-2007)

0.40

0.29

0.34

0.28

0.33 0.35 0.34 0.34

0.410.38

0.00

5.00

10.00

15.00

20.00

25.00

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

DP

S /

EPS

(RM

sen

)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

DP

R


62

As shown in Figure 4.15 above, although the earnings of the companies in the

Trading / Services sector were affected by the financial crisis in 1998 (average

EPS was 14.13 sen), however the companies in this sector still pay a

reasonable high dividend with the average DPS of 5.62 sen with average DPR

of 0.40. The average DPR was quite volatile pre-2002 period and started to

recorded stable average DPS between the period of 2002 to 2005 at

approximately 0.30 when the Kuala Lumpur Composite Index was still below

1,000 points. Subsequently after year 2005 when the Kuala Lumpur

Composite Index started to breach the 1,000 points, most companies in the

Trading and Services sector started to increase their DPR to the highest record

of 0.41 and further slightly reduced to 0.38 in year 2007 in view of the

expectation of the slowdown of the Malaysia and world economy and the

pressure of inflation.

4.2 ANALYSIS OF MEASURES

The univariate OLS Regression performed to test the relationship between changes in

dividends in year 0 (independent variable) and changes in earnings in current year 0

and subsequent 5 years from year 1 to year 5 was further elaborate as follows:-

(a) All firm-year observations for dividend change events that occurred from year

1998 to 2007. All the dividend change events were further subdivided into 2

sub-categories of dividend increase and dividend decrease to examine the

category of dividend change event which shows stronger signalling effect.

63

Regression results were elaborated in Section 4.2.1.

(b) Individual year observation on dividend change events that occurred from year

1998 to 2007. For each individual year, regressions were done on all dividend

events that occurred in that individual year. Subsequently, regression analysis

was conducted on each sub-category of dividend increase and dividend

decrease events in each individual year to examine the category of dividend

change event which shows stronger signalling effect. The reasons such a

detailed analysis was conducted was to identify whether the signalling effect

on all the firm-year observations within the study period was more strongly

affected by certain individual years. The regression results were further

discussed in Section 4.2.2.

(c) All firm-year observations for dividend events that occurred for the sub-

periods between 1998 to 2001 (financial crisis period) and between 2002 to

2007 (post-financial crisis period) to examine whether differences in the extent

of dividend signalling exists between these sub-periods. The year from 1998 to

2001 was categorized as financial crisis period due to the financial crisis

experienced in year 1997 and 1998 and low Gross Domestic Product growth in

year 2001(0.5%). During the 1997 to 2001 period, the Foreign Direct

Investments inflows continued to decrease from approximately US$7 billion

in 1997 to zero in year 2001. In year 2001, Malaysian export growth dropped

to its lowest level to -10%. The period starting from 2002 onwards was

categorized as post-financial crisis period due to the observed trend of

recovery in the economic indicators. The reasons such a detailed analysis was

conducted was to identify whether the signalling effect on all the firm-year

observations within the study period was more strongly affected by certain

64

economic conditions (financial crisis period and post financial crisis period).

Further regressions were performed on sub-category of dividend increase and

dividend decrease events that occurred in each of the sub-period. The results

of the regression performed were elaborated in Section 4.2.3.

(d) Case by case observation on all dividend change events that occurred after 2

years, 3 years and 4 years of stable DPS, in which only companies that

experienced changes in dividends after some period of stable DPS will be

selected in the studies. The purpose of such detailed observations were

performed is to examine whether the signalling effect becomes stronger should

the companies undergone stable dividend policy for a longer period of time.

All the dividend events that occurred after some period of stable DPS were

further subdivided into 2 sub-category of dividend increase and dividend

decrease to identify the extent of signalling effect of each category of dividend

change. Regression results were elaborated in Section 4.2.4.

(e) Sub-group regression on dividend change events that fall within certain

categories of dividend change (measured in percentage). The sub-group

regression analysis was performed to test whether the signalling effect

becomes stronger when the size of dividend change events becomes larger.

The categories of dividend change are:-

1) Dividend decrease ≥100%

2) Dividend decease between 50% to not more than 100%

3) Dividend decrease between 30% to not more than 50%

4) Dividend decrease more than 0% to not more than 30%

65

5) Dividend no change at 0%

6) Dividend increase more than 0% to not more than 30%

7) Dividend increase between 30% to not more than 50%

8) Dividend increase between 50% to not more than 100%

9) Dividend increase equals to or more than 100%

Regression results to test the above relationship between the size of dividend

change with the extent of dividend signalling were elaborated in Section 4.2.5.

(h) All firm year observations on dividend changes event categorised by the size

of dividend yield (measured in percentage). The sub-group regression analysis

on these different categories of dividend yield was performed to test whether

the signalling effect becomes stronger under the clientele effect in which it is

assumed that the larger the dividend yield of a company, the stronger the

signalling effect when the company changed its dividend payment. The sub-

division of dividend yield into different categories are listed below:-

(i) Dividend yield less than 1%

(ii) 1% ≤ Dividend Yield < 4%

(iii) 4% ≤ Dividend Yield < 6%

(iv) 6% ≤ Dividend Yield < 8%

(v) Dividend yield ≥ 8%

Regression results to test the above relationship between the size of dividend

yield with the extent of dividend signalling were elaborated in Section 4.2.6.

66

In addition to the univariate OLS regression, multiple regression was also performed

to test the industry effect in dividend signalling. The industry effect of three major

sectors with the highest number of dividend paying companies, namely Industrial,

Trading / Services and Consumer sector are studied by incorporating industry

dummies in the regression equation. The regression performed was further elaborated

as below:

(i) All firm-year observation for dividend events that occurred from year 1998 to

2007 by controlling the industry effect. Two sector dummy variables from the

Industrial, Trading / Services and Consumer sector were included in the

multiple regression equation. The beta coefficient generated for each of the

dummy variable is used to identify whether any differences exist between 2

sectors. Subsequent to this, all the firm year observations were further

subdivided into 2 sub-categories of dividend increase and dividend decrease to

identify the extent of signalling effect of each category of dividend change

under the influence of industry effect. The regression results were elaborated

in Section 4.2.7.

4.2.1 Analysis of Regression Result on All Firm-Year Observations

The regression equation adopted in this study is as follows:-

(EPS i,t – EPS i,t–1) / P i,0 = α0 + α1 ∆Div i,0 + ε T

67

Whereas

EPS i,t = EPS of firm i in year T= 0, 1, 2, 3, 4 and 5

P i,0 = Share price of firm i at the beginning of dividend change year

T=0

∆Div i,0= (DPS i,0 – DPS i,-1) / DPS i,-1 in which DPS i,0 = DPS of firm i

in year T= 0 and DPS i,-1 = DPS of firm i in year T= -1


Regression result on all firm-year observations on dividend change events that

occurred between year 1998 to 2007 shows that the beta coefficient (α1) for

the predictor (changes in dividends in year 0) is positive and significant in

year T = 0 and year T = 4 with α1 higher in value in year T=0 (α1 = 0.017) as

compared with year T = 4 (α1,= 0.007). For other event years (T = 1, 2, 3 and

5), α1 is negative and insignificant, indicating negative relationship between

changes in dividends in year T= 0 with changes in earnings in these

subsequent years.

The result of the Pearson product-moment correlation coefficient shows weak

positive and significant relationship between changes in dividends and

changes in earnings in year T= 0 and year T=4 (0.18 and 0.07 respectively).

The result of the regression is summarized in Table 4.5, which shows changes

in dividends do not convey information on future profitability. The result is

consistent with the previous findings by Grullon et al (2005) and Nissim and

Ziv (2001). The adoption of the model of Benartzi et al (1997) by Nissim and

Ziv showed that the value of beta coefficient, α1 was significant in year T=0

68

and insignificant in the subsequent years.

Table 4.5 Regression result on dividend change events for all firm-year

observations (1998-2007) T α0 t(α0) α1 t(α1) Pearson

Correlation R2 N

0 -0.005 -3.846 0.017 9.378 0.180 0.032 2,679 1 0.009 5.943 -0.003 -1.440 -0.030 0.001 2,275 2 0.010 5.764 -0.001 -0.531 -0.012 0.000 1,914 3 0.008 4.966 -0.003 -1.472 -0.037 0.001 1,576 4 0.011 5.199 0.007 2.468 0.070 0.005 1,250 5 0.014 7.239 -0.003 -1.051 -0.034 0.001 970

Note: Value in bold indicates significant relationship at p<0.05 N indicates number of firm-year observations

Further analysis on the sub-samples of dividend increase and dividend

decrease events for all the firm-year observations between year 1998 to 2007

shows that dividend decrease has a stronger effect in determining the value of

beta coefficient (α1) on the overall firm-year observations in year T = 0. α1 of

year T=0 under the dividend decrease sub-sample shows a higher positive and

significant value of 0.068 as compared with 0.007 for the dividend increase

sub-sample. The positive α1 of 0.007 for all the firm-year observations in

year T=4 is more strongly influenced by the dividend increase events in year

T=4 with α1=0.008 at significant level of p<0.05. The regression results of the

sub-samples of dividend increase and dividend decrease events are

summarized in Table 4.6 and Table 4.7. From the value of beta coefficient on

the dividend decrease sub-samples, the frequency of negative beta coefficients

occurred in year T=1 to T=5 is higher as compared with the frequency of

positive beta coefficients (3 out of 5), which indicates that dividend decreases

are not related to future profitability in most circumstances. Such negative

69

relationship is consistent with the findings by Grullon et al (2005). The

stronger effect of dividend decrease as a signalling device, especially changes

in earnings in the concurrent year supports the results observed by DeAngelo

and DeAngelo (1990) and Nissim and Ziv (2001). Their studies proved that

dividend increases are more frequent than dividend decreases but are smaller

in magnitude, which further explain the reasons of dividend decrease has

stronger effect of signalling under the study period.

Table 4.6 Regression result on dividend increase events for all firm-year


Correlation R2 N

0 0.005 2.718 0.007 4.322 0.120 0.014 1,274 1 0.002 1.059 0.002 0.873 0.027 0.001 1,044 2 0.005 1.911 0.002 0.722 0.024 0.001 882 3 0.006 2.308 -0.003 -1.157 -0.044 0.002 705 4 0.009 2.718 0.008 2.605 0.112 0.013 532 5 0.014 4.045 -0.003 -0.999 -0.051 0.003 391


Table 4.7 Regression result on dividend decrease events for all firm-year


Correlation R2 N

0 0.000 -0.049 0.068 4.480 0.169 0.028 687 1 0.006 0.868 -0.017 -1.051 -0.042 0.002 625 2 0.007 1.157 -0.014 -0.993 -0.044 0.002 514 3 0.017 2.522 0.022 1.457 0.070 0.005 439 4 0.012 1.794 0.006 0.375 0.019 0.000 374 5 0.007 1.126 -0.013 -0.937 -0.053 0.003 315


70

4.2.2 Analysis of Regression Result on Each Individual Year Observations

From Year 1998 to 2007

Regression analysis was performed on each individual year to examine the

signalling effect of changes in dividends in each individual year and to

examine which individual year has a stronger signalling effect in determining

the overall signalling effect of all the firm year observations under the period

of study.

Regression Result for Year 1998 The regression result shows strongest positive and significant relationship

between changes in dividends and changes in earnings occurred in year T=0

for all firm-year observations (α1 = 0.095), which is strongly influenced by the

dividend decrease event (α1 = 0.092, significant at p<0.05). A negative and

significant beta coefficient was recorded in year T=2 for all firm-year

observations which was strongly influenced by dividend decrease events with

a stronger negative (but insignificant) beta coefficient (α1 = -0.049, p>0.05).

Regression analysis on the sub-samples of both dividend increase and

dividend decrease showed that in most circumstances, dividend increase

(decrease) has a negative relationship with subsequent increase (decrease) in

earnings in year T=1 to T=5. Table 4.8 shows the summary of the regression

result in year 1998:-

71

Table 4.8 Regression result on all firm-year observations, categorized by type of

dividend change (1998)

All firm-year observations

Dividend Increase Dividend Decrease

T α1 R2 α1 R2 α1 R2 0 0.095 0.122 -0.019 0.002 0.092 0.043 1 -0.005 0.001 -0.042 0.030 -0.009 0.001 2 -0.044 0.079 0.017 0.004 -0.049 0.041 3 0.016 0.009 0.012 0.002 0.045 0.029 4 -0.008 0.003 -0.006 0.001 -0.015 0.004 5 -0.005 0.002 -0.023 0.018 -0.017 0.008

Note: Value in bold indicates significant relationshipl at p<0.05

Regression Result for Year 1999

Positive and significant beta coefficient occured in year T=4 (α1 = 0.018)

which was strongly influenced by dividend decrease events (α1 = 0.011,

insignificant with p>0.05). The beta coefficients generated from the regression

analysis for both samples of all firm-year observations and dividend increase

sub-sample show positive and insignificant relationship between changes in

dividends and changes in earnings in the concurrent year T=0. Regression

results on both sub-samples of dividend increase and dividend decrease show

no significant relationship exists with mixed positive and negative value of

beta coefficients recorded from year T=1 to T=5. For the sub-sample of

dividend decrease, negative but insignificant beta coefficient was recorded

from year T=0 until T=2 while the subsequent years starting from T=3 shows

positive but insignificant relationship between changes in dividends and

changes in earnings in these years. From the result generated, it is obvious that

dividend change events that occurred in year 1999 were not associated with

72

the changes in earnings in both concurrent and subsequent years. Summary of

the regression results are illustrated in Table 4.9.





T α1 R2 α1 R2 α1 R2 0 0.005 0.002 0.001 0.000 -0.007 0.001 1 -0.010 0.010 -0.005 0.001 -0.033 0.030 2 0.003 0.001 0.017 0.019 -0.018 0.007 3 -0.010 0.008 -0.025 0.028 0.035 0.036 4 0.018 0.041 0.000 0.000 0.011 0.005 5 0.005 0.004 0.011 0.016 0.005 0.001

Note: Value in bold indicates significant relationship at p<0.05

Regression Result for Year 2000

Regression result on all firm-year observations in year 2000 shows negative

and significant relationship existed between changes in dividends in year T=0

with changes in earnings in year T=4 (α1 = -0.010, p<0.05). No significant

positive and/or negative relationship exists between the dividend change

events with changes in earnings on both sub-samples of dividend increase and

dividend decrease from year T=0 to T=5. Unlike the regression result for the

dividend increase sub-sample (with negative beta coefficients recorded from

year T=1 to year T=3), positive beta coefficients were recorded in these years

for the dividend decrease sub-sample which recorded higher (but insignificant)

value of beta coefficients as compared with the dividend increase sub-sample.

It is obvious that dividend change events in year 2000 were not associated

with the changes in earnings in both concurrent and subsequent years.

Summary of the regression results are illustrated in Table 4.10.

73





T α1 R2 α1 R2 α1 R2 0 0.009 0.023 0.004 0.004 0.000 0.000 1 -0.007 0.009 -0.003 0.002 0.042 0.036 2 0.001 0.000 -0.001 0.000 0.003 0.000 3 -0.010 0.034 -0.008 0.022 0.025 0.028 4 -0.002 0.002 0.002 0.002 -0.014 0.006 5 0.002 0.001 0.011 0.019 -0.001 0.000


Regression Result For Year 2001

Positive and significant relationship between both changes in dividends and

changes in earnings in year T=0 (α1 = 0.026, p<0.05) for all firm-year

observations, which is more strongly influenced by dividend decrease events

(α1 = 0.024, p>0.05). Negative but insignificant results were recorded in the

subsequent years T=1 until T=3 and positive but insignificant relationship

between both changes in dividends and earnings occurred in year T=4 and

T=5. A separate regression analysis on the dividend increase sub-sample

showed mixed result with both positive and negative (insignificant) beta

coefficients occurred between year T=1 to T=5. For the dividend decrease

sub-sample, regression results shows a positive and significant relationship

occurred between changes in dividends in year 0 with changes in earnings in

year T=4 (α1 = 0.067, p<0.05). Same as the regression result of the dividend

increase sub-sample, mixed beta coefficients were recorded from year T=1

until year T=5. Summary of the regression results are illustrated in Table 4.11.

74





T α1 R2 α1 R2 α1 R2 0 0.026 0.048 0.019 0.024 0.024 0.009 1 -0.010 0.011 -0.022 0.039 0.008 0.001 2 -0.012 0.015 0.015 0.016 -0.020 0.013 3 -0.015 0.020 0.011 0.011 -0.025 0.012 4 0.016 0.015 0.020 0.017 0.067 0.094 5 0.002 0.000 -0.006 0.002 0.021 0.011


Regression Result for Year 2002 Regression result in year 2002 showed positive and significant relationship

between changes in dividends in year T=0 with changes in earnings in year

T=1 (α1 = 0.016, p<0.05). The positive and significant relationship was mainly

influenced by dividend increase (α1 = 0.017, p<0.05). Strongest positive and

significant beta coefficient was recorded in year T=4 for dividend increase

sub-sample with α1 = 0.033, p<0.05. Regression result on the dividend

decrease sub-sample shows no significant relationship across the years with

majority of the beta coefficients recorded negative values. Contrary to the

regression results of individual years in the previous sections, regression on

the dividend increase sub-sample shows more frequent occurrence of positive

significant beta coefficients in the subsequent years after the dividend increase

in year T=0, which indicates dividend signalling occurs for dividend increase

events in year 2002. Summary of the regression results are illustrated in Table

4.12.

75





T α1 R2 α1 R2 α1 R2 0 -0.004 0.000 -0.005 0.005 -0.018 0.005 1 0.016 0.040 0.017 0.092 0.026 0.019 2 -0.007 0.006 -0.003 0.003 -0.018 0.009 3 -0.005 0.002 0.001 0.000 -0.039 0.017 4 0.013 0.012 0.033 0.095 0.019 0.006 5 -0.010 0.007 -0.010 0.009 -0.002 0.000

Note: Value in bold indicates significant relationshipl at p<0.05

Regression Result for Year 2003 Regression result on all firm-year observations in year 2003 shows none of the

changes in earnings in the concurrent year T=0 and subsequent years of T=1

until T=5 has any significant relationship with the changes in dividends in

year T=0. The same result also occurred in the dividend increase sub-sample

with very weak positive relationship (beta coefficients for the dividend

increase sub-sample ranged between 0 to 0.007 from year T=0 to year T=5).

For the dividend decrease sub-sample, negative and significant relationship

occurs in year T=0 (α1 = -0.048, p<0.05). Mixed results on correlations

between changes in dividends with changes with earnings were recorded for

the dividend decrease sub-sample, which is different from the dividend

increase sub-sample. The regression result on the dividend increase sub-

sample shows all positive (but insignificant) beta coefficients between year

T=0 to year T=5. Summary of the regression results are illustrated in Table

4.13.

76





T α1 R2 α1 R2 α1 R2 0 0.006 0.015 0.007 0.022 -0.048 0.080 1 0.004 0.004 0.004 0.006 0.002 0.000 2 -0.003 0.001 0.004 0.003 -0.017 0.003 3 -0.007 0.006 0.000 0.000 0.017 0.004 4 0.007 0.006 0.003 0.001 0.006 0.001 5 N/A N/A N/A N/A N/A N/A

Note: Value in bold indicates significant relationship at p<0.05 N/A indicates no result generated as data required for year 2008 are not available

Regression Result for Year 2004 The regression result on all dividend change events in year 2004 shows

negative and significant relationship exists between changes in dividends in

year T=0 with changes in earnings in year T=1 (α1 = -0.012, p<0.05). The

negative and significant relationship was more strongly affected by the

dividend decrease event which have a higher negative but insignificant beta

coefficient of α1 = -0.043 at p>0.05. No significant relationship exists for both

dividend increase and dividend decrease sub-samples. Further examination on

the frequency of positive and negative beta coefficients in the subsequent

years following dividend change events in year T=0 shows 2 out of 3 years

subsequent to the dividend change events in year T=0, the beta coefficients

generated are negative. Hence, it is prominent that dividend signalling does

not exist in year 2004. There is no significant relationship between changes in

dividends and changes in earnings in the concurrent year T=0, as shown by the

beta coefficient for the all firm-year observations and the dividend increase

77

sub-sample (α1 = 0.006 and 0.003 respectively at p>0.05). Summary of the

regression results are illustrated in Table 4.14.





T α1 R2 α1 R2 α1 R2 0 0.006 0.010 0.003 0.002 -0.014 0.012 1 -0.012 0.018 -0.010 0.010 -0.043 0.038 2 -0.003 0.001 -0.011 0.013 0.002 0.000 3 0.004 0.002 0.008 0.008 -0.030 0.023 4 N/A N/A N/A N/A N/A N/A 5 N/A N/A N/A N/A N/A N/A

Note: Value in bold indicates significant relationship at p<0.05 N/A indicates no result generated as data required for year 2008 and 2009 are not available

Regression Result For Year 2005 Regression result on all dividend change events in year 2005 shows no

dividend signalling as the beta coefficients for both year T=1 and T=2 shows

negative and insignificant value (α1 = -0.009 and -0.008 respectively). Positive

but insignificant relationship exists for both changes in dividends and earnings

in the concurrent year T=0 (α1 = 0.012, p>0.05). Same as the regression result

on all firm-year observations, no significant relationship exists between

dividend increase in year 0 with changes in earnings in the concurrent and

subsequent 2 years. Except the positive relationship between changes in

dividends in year T=0 with changes in earnings in year T=0 and T=2, negative

coefficients was recorded in year T=1 (α1 = -0.007, p>0.05) for the dividend

increase sub-sample. Contrary to the dividend increase sub-sample, significant

relationships exist between dividend decrease in year T=0 with (1) changes in

78

earnings in year T=0 (α1 = 0.077, p<0.05) and (2) changes in earnings in year

T=1(α1 = -0.075, p<0.05). Based on the higher beta coefficient generated in

year T=0 under the dividend decrease sub-sample, conclusions can be made

that dividend decrease events have stronger information content in portraying

past earnings. The negative beta coefficient recorded in year T=1 under the

dividend decrease sub-sample shows that earnings increases in the subsequent

year after firms experienced dividend cuts in the previous years. Summary of

the regression results are illustrated in Table 4.15.





T α1 R2 α1 R2 α1 R2 0 0.012 0.013 0.004 0.001 0.077 0.124 1 -0.009 0.006 -0.007 0.004 -0.075 0.076 2 -0.008 0.004 0.004 0.001 -0.027 0.011 3 N/A N/A N/A N/A N/A N/A 4 N/A N/A N/A N/A N/A N/A 5 N/A N/A N/A N/A N/A N/A

Note: Value in bold indicates significant relationship at p<0.05 N/A indicates no result generated as data required for year 2008, 2009 and 2010 are not available

Regression Result for Year 2006 Regression result on all firm-year observations shows that positive and

significant relationship exists between changes in dividends with changes in

earnings in concurrent year T = 0 (α1 = 0.017, p<0.05). However, negative but

insignificant beta coefficient was recorded in year T=1 (α1 = -0.005, p>0.05),

which shows the inexistence of dividend signalling. Consistent with the

regression result for all dividend events sample, the regression result for the

79

dividend increase sub-sample also showed the similar results in year T=0 (α1 =

0.010) and year T=1 (α1 = -0.005). However the relationship between these

two variables was insignificant under the dividend increase sub-sample in year

T=0. No significant relationship was found from the regression on the

dividend decrease sub-sample. However, negative but insignificant

relationship was recorded for both changes in dividends and earnings in year

T=0 (α1 = -0.013, p>0.05). Stronger but insignificant signalling effect (α1 = -

0.017, p>0.05) was observed between changes in dividends in year T=0 with

changes in earnings in the subsequent year T=1 under the dividend decrease

sub-sample as compared with the dividend increase events. Summary of the






T α1 R2 α1 R2 α1 R2 0 0.017 0.027 0.010 0.015 -0.023 0.006 1 -0.005 0.001 -0.005 0.001 0.017 0.002 2 N/A N/A N/A N/A N/A N/A 3 N/A N/A N/A N/A N/A N/A 4 N/A N/A N/A N/A N/A N/A

5 N/A N/A N/A N/A N/A N/A Note: Value in bold indicates significant relationship at p<0.05 N/A indicates no result generated as data required for year 2008, 2009, 2010 and 2011 are not available

Regression Result for Year 2007 The regression result on all dividend change events showed a positive and

significant relationship between both changes in dividends and earnings in the

concurrent year T=0, attributable to the positive and significant influence by

80

the dividend increase events (α1 = 0.008, p<0.05). For the dividend decrease

sub-sample, positive but insignificant relationship occurred between changes

in dividends and changes in earnings (α1 = 0.034, p>0.05). Summary of the






T α1 R2 α1 R2 α1 R2 0 0.014 0.041 0.008 0.024 0.034 0.021 1 N/A N/A N/A N/A N/A N/A 2 N/A N/A N/A N/A N/A N/A 3 N/A N/A N/A N/A N/A N/A

4 N/A N/A N/A N/A N/A N/A 5 N/A N/A N/A N/A N/A N/A

Note: Value in bold indicates significant relationship at p<0.05 N/A indicates no result generated as data required for year 2008, 2009, 2010, 2011 and 2012 are not available

In conclusion, the regression result in each individual year shows that majority

of the years do not support the existence of dividend signalling among the

Main Board listed companies. Instead, dividend change events (especially

decrease in dividends) are strongly related to changes in earnings in the

concurrent year. The result is consistent with the result of Grullon et al (2005)

which showed that current changes in dividends are not a reliable signal on

changes in future profitability. Overall, the positive significant relationship

between both changes in dividends and changes in earnings in year T=0 on all

firm-year observations is more strongly influence by dividend change events

in year 1998 (in which the later is strongly influenced by dividend decrease).

While for the positive significant relationship between changes in dividends in

81

year T=0 with changes in earnings in year T=4 on all firm-year observations,

the significant relationship is more strongly influence by dividend change

events in year 1999 (in which the later is strongly influenced by dividend

decrease).

4.2.3 Analysis of Regression Result on Dividend Change Events During the

Financial Crisis Period (1998-2001) and Post-Financial Crisis Period

(2002-2007)

Regression analysis was performed on sub-groups of dividend change events

during the financial crisis period (1998 to 2001) and after the financial crisis

period (2002 to 2007) to examine whether the signalling effect differs between

these two sub-groups. The regression analysis performed is based on the

following reasoning:-

i. Stronger signalling effect exists during the financial crisis period as

compared with post-financial crisis period. Any changes in dividends

during the financial crisis period are associated with the firms’

expectations on the future profitability given the economic condition

during the financial crisis period. An increase in dividends during the

financial crisis period can be interpreted as positive outlook of the

firms in its ability to regain its profitability while other industry players

are still experiencing decrease in profitability.

ii. Weaker signalling effect after the financial crisis period as compared

with financial crisis period as any changes in dividends has weaker

signalling effect when the economy condition becomes more stable.

82

Regression results on all firm-year observations during the crisis period (1998

to 2001) show positive and significant relationship occurred in year T=0 (α1 =

0.031, p<0.05), and in year T=1, negative and significant relationship exists

between changes in earnings in year T=1 with changes in dividends in year

T=0 (α1 = -0.010, p<0.05). Separate regression on the dividend increase sub-

sample, however showed no significant relationship between changes in

dividends in year T= 0 with changes in earnings in concurrent and subsequent

years from year T = 0 to year T = 5. Mixed results were generated under the

dividend increase sub-sample with 3 years of negative beta coefficients for the

period between T=1 and T=5. Result of the regression analysis on the dividend

decrease sub-sample shows positive (negative) and significant relationship

exists between changes in dividends in year T=0 with changes in earnings in

year T=0 (T=2), with beta coefficients of 0.079 (-0.036). From the result

generated, conclusion can be arrived in which:-

(1) positive relationship between changes in dividends with changes in

earnings in year T=0 for all firm-year observations during the financial

crisis period is more strongly influenced by the dividend decrease events;

(2) Dividend decrease events in year T = 0 is associated with increase in

earnings in the subsequent year T=2 during the financial crisis period. In

fact, in most circumstances under the dividend decrease sub-sample

(although the value of the beta coefficients is not significant), negative

relationship exists between dividend decrease in year T = 0 with increase

in earnings in the subsequent years.

83

The regression results are summarized in Table 4.18.


dividend change during the financial crisis period (1998-2001)



T α1 R2 α1 R2 α1 R2 0 0.031 0.052 0.009 0.008 0.079 0.041 1 -0.010 0.008 -0.007 0.004 -0.017 0.003 2 -0.006 0.004 0.005 0.003 -0.036 0.016 3 -0.007 0.004 -0.006 0.005 0.022 0.006 4 0.004 0.001 0.006 0.004 -0.002 0.000 5 -0.004 0.001 -0.004 0.002 -0.021 0.006


Further, regression result on the sub-sample of dividend change events post-

financial crisis period (2002 to 2007) shows positive and significant

relationship occurred in year T=0 (α1 = 0.013, p<0.05), while the beta

coefficients for the subsequent years are positive but insignificant. Contrary to

the dividend increase sub-sample during the financial crisis period (in which

no significant relationship was found), positive and significant relationships

occurs in year T=0 and T=4 with α1 = 0.010 and α1 = 0.009 respectively. For

the dividend decrease sub-sample, no significant relationship was found

between changes in dividends and changes in earnings in both concurrent and

subsequent years. In fact, 3 out of 5 of the value of beta coefficients from year

T=1 to T=5 show negative value, indicating that no signalling effect exists for

the dividend decrease sub-sample. Overall, the regression analysis generates

the following conclusions:-

84

(1) positive relationship between changes in dividends with changes in

earnings in year T=0 for all firm-year observations during the post-

financial crisis period is more strongly influenced by the dividend

increase events;

(2) In most circumstances under the dividend decrease sub-sample

(although the value of the beta coefficients is not significant), negative

relationship exists between dividend decrease in year T = 0 with

increase in earnings in the subsequent years.

The regression results for the dividend change events during the post-financial

crisis period are summarized in Table 4.19.


dividend change during the post-financial crisis period (2002-2007)



T α1 R2 α1 R2 α1 R2 0 0.013 0.028 0.010 0.029 0.013 0.002 1 0.000 0.000 0.005 0.005 -0.022 0.005 2 0.001 0.000 0.002 0.001 0.001 0.000 3 0.000 0.000 0.003 0.002 -0.019 0.004 4 0.006 0.007 0.009 0.018 0.009 0.002 5 0.001 0.000 0.005 0.005 -0.004 0.000

Note: Value in bold indicates significant level at p<0.05

In conclusion, dividend decrease has stronger signalling effect during the

financial crisis period while dividend increase has stronger signalling effect

during the post-financial crisis period. The findings on stronger influence of

dividend decrease under the dividend signalling hypothesis was proven by

85

Grullon et al (2005) in which the regression result on each individual year, i.e.

year 1997 showed a higher beta coefficient for dividend decrease events (α1 =

0.063) as compared with dividend increase events (α1 = 0.021).

4.2.4 Analysis of Regression Result on Dividend Change Events Occurred After

Stable DPS for Consecutive 2 Years, 3 Years and 4 Years

Regression analysis was performed on sub-samples of dividend change events

that occurred after certain period of stable DPS to examine the differences in

signalling effect under different period of stable dividend. As such, the

expected regression result shall be higher beta coefficients for dividend change

events that occurred after longer period of stable dividend.

Regression result on the dividend change events that occurred after 2

consecutive years of stable DPS shows positive and significant relationship

occurred in year T=0 and further analysis on the sub-sample of dividend

increase shows the same result with α1 = 0.011 and 0.007 respectively.

However, regression result on the dividend decrease sub-sample shows no

significant positive or negative relationship between dividend decrease with

concurrent and subsequent increase or decrease in earnings.

Surprisingly, different from the regression result for dividend change events

that occurred after 2 consecutive years of stable dividends, no positive and

significant relationship exists between the changes in dividends in year 0 with

the concurrent changes in earnings for the dividend change events that

occurred after 3 consecutive years of stable dividends. The same result was

86

recorded by the dividend increase sub-sample as well. Negative and

significant relationship between dividend change events in year T=0 with

changes in earnings occurred in year T=3 (α1 = -0.010, p<0.05), which is

strongly influence by the dividend decrease events (α1 = -0.051, p>0.05).

Regression result on the relationship between decrease in dividend in year 0

with changes in earnings in year T=4 shows a positive and significant

relationship (α1 = 0.159, p<0.05). No significant relationship was found

between changes in earnings with changes in dividends that occurred after

consecutive 3 years of stable dividends.

The regression result for the dividend change events that occurred after 4

consecutive years of stable dividend also shows the same result with the sub-

sample of dividend change events that occurred after 3 consecutive years of

stable dividend. The beta coefficient in year T = 4 has a stronger negative

value of α1 = -0.145 as compared with the sub-sample of dividend change

events that occurred after 3 consecutive years of stable dividend (α1 = -0.010

p<0.05). Significant relationships are recorded for dividend increase events in

year 0 with changes in earnings in year 1, 3 and 4 with beta coefficient of

0.114, -0.211 and 0.207 respectively. No significant positive or negative

relationship exists between dividend decreases with changes in earnings under

the dividend decrease sub-samples.

Hence, the results showed the dividend signalling effect is stronger and

prominent between changes in both dividends and earnings in the concurrent

year T=0. A summary on the regression results on all dividend changes events

87

occurred after certain period of stable dividends are listed in Table 4.20, Table

4.21 and Table 4.22.

Table 4.20 Regression result on dividend change events that occurred after stable

dividends for 2 years, 3 years and 4 years Beta coefficient for dividend change events after stable dividend for

T 2 years 3 years 4 years 0 0.011 0.002 0.020 1 -0.005 -0.008 0.053 2 -0.001 0.004 0.019 3 0.000 -0.010 -0.145 4 0.005 0.006 0.170 5 -0.008 -0.002 -0.018


Table 4.21 Regression result on dividend increase events that occurred after stable

dividends for 2 years, 3 years and 4 years Beta coefficient for dividend increase events after stable dividend

for T 2 years 3 years 4 years 0 0.007 0.001 0.018 1 -0.004 -0.007 0.114 2 0.000 0.004 0.020 3 -0.001 -0.011 -0.211 4 0.000 0.007 0.207 5 -0.007 -0.007 -0.010


Table 4.22 Regression result on dividend decrease events that occurred after stable

dividends for 2 years, 3 years and 4 years Beta coefficient for dividend decrease events after stable dividend

for T 2 years 3 years 4 years 0 0.014 0.223 0.037 1 0.009 -0.107 -0.006 2 0.030 -0.205 -0.061 3 0.016 -0.051 -0.071 4 0.039 0.159 0.034 5 -0.049 0.165 0.510


88

From Table 4.20, consistent increase in beta coefficient for companies that

experienced longer period of stable dividends only occurred in year T = 2 and

T = 4 but insignificant at p>0.05. The same trend also occurred for the

dividend increase sub-sample as shown in Table 4.21. Hence we can conclude

that no stronger signalling effect is observed for dividend change events that

occurred after longer period of stable dividends.

4.2.5 Analysis of Regression Result on the Dividend Changes Events

Categorised by Size of Dividend Change

The regression analysis conducted at this stage is to examine the relationship

between the size of dividend change with the extent of dividend signalling

based on the rationale that investors are normally more concerned with larger

changes in dividends as compared with smaller and insignificant changes. As

such, a larger change in dividend has a stronger signalling effect than a smaller

change in dividend. The result of the regression analysis on the dividend

change events categorised by the size of dividend change is summarized in

Table 4.23.

Table 4.23 Summary on the regression result for dividend change events categorized

by different sizes of dividend change Beta coefficient (α1) Size of dividend change

Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 Decrease ≥100% - - - - - - Decrease 50% to <100% 0.193 0.058 (0.012) 0.086 (0.038) (0.090)Decrease 30% to < 50% 0.166 (0.378) (0.147) 0.015 0.155 0.038 Decrease > 0% to <30% 0.058 (0.007) (0.029) (0.101) 0.051 0.078 Increase >0% to < 30% 0.020 (0.059) (0.013) 0.061 (0.031) 0.042 Increase 30% to < 50% 0.024 (0.139) 0.010 (0.023) 0.023 0.047 Increase 50% to <100% 0.019 0.022 (0.037) (0.057) (0.010) 0.029

Increase ≥100% 0.005 0.008 0.003 (0.003) 0.004 (0.002)


89

From Table 4.22, continuous increase in the value of beta coefficient occurs in

year T=0 when the size of dividend decrease becomes larger. i.e. dividend

decreases from more than 0% to less than 100% in year T=0. Positive and

significant beta coefficient of 0.193 recorded in year T=0 when the dividend

decreases from 50% to less than 100%. For the dividend increase sub-sample,

stronger signalling effect only occurred when the dividend increases from

more than 0% to not more than 50%, as can be observed in year T=1 and year

T=5. As such, we can conclude that the result has proved that there is no

strong relationship between the size of dividend change with the extent of

dividend signalling as the continuous increase in the beta coefficients when

the size of dividend change increases only occurred in year T=0.

4.2.6 Analysis of Regression Result on the Dividend Change Events

Categorised by Size of Dividend Yield

The objective of the regression analysis is to examine the relationship between

the size of dividend yield with the extent of dividend signalling based on the

rationale that companies with higher dividend yields will place more weight in

their dividend decisions. This is because such high dividend yield companies

use dividend as their basis of share valuation. In contrary, companies with low

dividend yield will place more weight on share price appreciation. Hence, we

can hypothesize that the higher the dividend yield, the greater the signalling

effect when a company changes its dividend payment.

The analysis on the extent of dividend signalling on the concurrent and

subsequent years after the changes in dividends, categorized by the size of

90

dividend yield is summarized in Table 4.24.

Table 4.24

Summary on the regression result for dividend change events categorized by different sizes of dividend yield

Beta coefficients(α1) Size of dividend

yield (“DY”) Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 DY<1% 0.033 0.017 (0.014) (0.001) 0.044 (0.007) 1% ≤ DY < 4% 0.018 (0.006) (0.001) (0.002) 0.004 (0.004) 4% ≤ DY < 6% 0.026 (0.002) 0.005 (0.009) 0.000 0.007 6% ≤ DY < 8% 0.020 (0.007) 0.013 0.000 0.010 (0.014) DY ≥ 8% 0.003 0.001 0.002 0.004 0.002 0.003

Note: Value in bold indicates significant relationship at p<0.05 From Table 4.23 above, there is no strong prove on the positive relationship

between higher dividend yield with stronger dividend signalling in both

concurrent and subsequent 5 years after the dividend change events. In fact,

the regression result shows that when the dividend yield is very high, i.e.

equals or more than 8%, the relationships between changes in dividends with

changes in earnings in the concurrent and subsequent 5 years become very

small and insignificant (α1 between 0.001 to 0.004 with p>0.05). Consistent

with the previous regression results, most of the positive and significant

relationships exist between changes in dividends with changes in earnings in

the concurrent year 0 and subsequent year T=4, in which the largest beta

coefficient was recorded in year 4 (α1 = 0.033 for year T=0 and α1 = 0.044 for

year T=4) for companies with less than 1% dividend yield, attributable to the

majority of companies fall under this category. As for other years, no

consistent increase in beta coefficient when the dividend yield becomes larger

with mixed result (positive and negative beta coefficients exist

91

interchangeably in the subsequent year T=1 to T=5. For the sub-sample of

companies with dividend yield between 1% to less than 4%, result of

regressions in most of the subsequent years under study (4 out of 5 years)

show negative beta coefficient while for the sub-sample of companies with

dividend yield of more than 8%, positive (but insignificant) relationship exists

at a smaller magnitude. Hence, we can conclude that no relationship exists

between the size of dividend yield and the extent of signalling.

4.2.7 Analysis of Regression Result on All Firm-Year Observations by

Incorporating Industry Effect

The multiple regression equation adopted in this study is as follows:-

(EPS i,t – EPS i,t–1) / P i,0 = α0 + α1 ∆Divi,0 + α2 Dummya + α3 Dummyb + ε T

Whereas



T=0

∆Div i,0= (DPS i,0 – DPS i,-1) / DPS-1 in which DPS i,0 = DPS of firm i in

year T=0 and DPS i,-1 = DPS of firm i in year T= -1

Dummya = Dummy variable for sector a which takes the value of 1 if it is

sector a and 0 if otherwise

Dummyb = Dummy variable for sector b which takes the value of 1 if it is

sector b and 0 if otherwise


92

Based on the analysis on the Main Board dividend paying companies, three

sectors with the highest number of dividend paying companies are the

Industrial, Trading / Services and Consumer sectors. Hence, 3 multiple

regressions are performed by incorporating 2 sector dummies to examine

whether there is any difference in the signalling effect between 2 sectors when

the dividend of the companies change.

1st run of multiple regression (Industrial sector as base):

(EPS i,t – EPS i,t–1) / P i,0 = α0 + α1 ∆Div i,0 + α2 DummyT + α3 DummyC + ε T

2nd run of multiple regression (Trading / Services sector as base)

(EPS i,t – EPS i,t–1) / P i,0 = α0 + α1 ∆Div i,0 + α2 DummyI + α3 DummyC + ε T

3rd run of multiple regression (Consumer sector as base)

(EPS i,t – EPS i,t–1) / P i,0 = α0 + α1 ∆Div i,0 + α2 DummyI + α3 DummyT + ε T

Whereas



T=0

∆Div i,0 = (DPS i,0 – DPS i,-1) / DPS i,-1 in which DPS i,0 = DPS of firm i in

year T= 0 and DPS i,-1 = DPS of firm i in year T= -1

DummyT = Dummy variable which takes the value of 1 if it is Trading /

Services sector and 0 if otherwise

93

DummyC = Dummy variable which takes the value of 1 if it is Consumer

sector and 0 if otherwise

DummyI = Dummy variable which takes the value of 1 if it is Industrial

sector and 0 if otherwise


Summary on the 3 stages of multiple regression result on all firm-year

observations from year 1998 to year 2007 are listed in the following tables:-

Table 4.25 Multiple regression on all firm-year observations controlled by industry

effect: Industrial sector as base T α1 t(α1) α2 t(α2) α3 t(α3) 0 0.017 9.376 (0.002) (0.491) 0.000 (0.040) 1 (0.003) (1.467) (0.001) (0.271) (0.008) (1.908) 2 (0.001) (0.556) (0.006) (1.426) (0.010) (2.207) 3 (0.003) (1.494) (0.006) (1.421) (0.009) (1.955) 4 0.006 2.439 (0.006) (1.195) (0.016) (2.934) 5 (0.003) (1.068) (0.009) (1.852) (0.009) (1.720)


Table 4.26

Multiple regression on all-firm year observations controlled by industry effect: Trading / Services sector as base

T α1 t(α1) α2 t(α2) α3 t(α3) 0 0.017 9.377 (0.002) (0.672) 0.000 (0.103) 1 (0.003) (1.467) 0.000 0.087 (0.007) (1.805) 2 (0.001) (0.563) 0.008 2.240 (0.005) (1.231) 3 (0.003) (1.498) 0.005 1.305 (0.005) (1.236) 4 0.006 2.435 0.007 1.399 (0.012) (2.239) 5 (0.003) (1.073) 0.006 1.415 (0.004) (0.866)


94

Table 4.27 Multiple regression all firm-year observations controlled by industry

effect: Consumer sector as base T α1 t(α1) α2 t(α2) α3 t(α3) 0 0.017 9.385 (0.003) (0.879) (0.003) (0.756) 1 (0.003) (1.446) 0.003 0.708 0.002 0.426 2 (0.001) (0.546) 0.010 2.516 0.000 (0.044) 3 (0.003) (1.479) 0.006 1.471 (0.002) (0.436) 4 0.006 2.458 0.010 2.038 0.001 0.206 5 (0.003) (1.054) 0.006 1.309 (0.005) (0.966)


Multiple regression result on all firm-year observations between year 1998 to

2007 (industrial sector as base) shows that the beta coefficient (α1) for the

predictor (changes in dividends in year T=0) is positive and significant in year

T = 0 and year T = 4 with α1 higher in value in year T=0 (α1 = 0.017) as

compared with year T = 4 (α1 = 0.006). For other event years (T = 1, 2, 3 and

5), α1 is negative but insignificant, which indicates negative relationship exists

between changes in dividends in year 0 with changes in earnings in the

subsequent years. The regression result in Table 4.24 above shows that all

Trading / Services sector (α2) and Consumer sector dummies (α3) recorded

relatively small negative and insignificant value in all the 5 years after the

dividend change events. For the Consumer sector dummy, significant negative

beta coefficients (α3) were recorded in year 2 and year 4 (-0.010 and -0.016

respectively). Therefore, we can conclude that industry effect does not exist

between (1) Trading / Services and Industrial sector (refer to value α2) and (2)

Consumer and Industrial sector (refer to value α3).

95

As shown by the value of beta coefficients for the sector dummies (α2 and α3)

in Table 4.25 above, only small difference between (1) Industrial and Trading

/ Services sectors and (2) Consumer and Trading / Services sectors in terms of

signalling effect in concurrent and subsequent years T=0 to T=5 when these

sectors experienced changes in dividends. The value of beta coefficients for

the Industry dummy ranged between 0.005 (year 3) to 0.008 (year 2) with no

differences recorded in signalling effect for year T=1 (α2 = 0.000). Same

result was also recorded for the differences in the signalling effect between

Consumer and Trading / Services sector as shown by the very low negative

beta coefficients in the subsequent 5 years after the changes in dividends in

year T=0. Negative and significant Consumer sector dummy only occurred for

changes in earnings in year T=2 and T=4 (α2 = =0.005 and α2 = -0.012

respectively). Hence, the 2nd run regression (Trading / Services sector as base)

shows no big difference in the signalling effect when changes in dividend

occur between (1) Industrial and Trading / Services sector and (2) Consumer

and Trading / Services sector.

The result of the 3rd run regression (Consumer sector as base) also generates

the same conclusion as per the 2 multiple regressions performed previously.

From Table 4.26 above, all the value of the beta coefficient for the Industry

sector dummy showed positive but small value in the subsequent years T=1 to

T=5 (positive and significant beta coefficient of 0.010 occurred in year T=2

and T=4). Mixed results (both positive and negative value of beta coefficient

for the Trading / Services sector dummy) were recorded with small and

insignificant value of the beta coefficients. Therefore we can conclude that

96

there is not much difference in the changes in earnings when there are changes

in dividends between (1) Industrial and Consumer sector and (2) Trading /

Services and Consumer sector.

Multiple regression results on the sub-samples of dividend increase and

dividend decrease are further summarized in Table 4.28 to Table 4.30. The

multiple regressions on these sub-samples also show little differences in the

signalling effect between the sectors in both concurrent and subsequent years

when there are changes in dividends.

Table 4.28 Multiple regression on dividend increase and dividend decrease sub-

samples controlled by industry effect: Industrial sector as base Dividend Increase Dividend Decrease

T α1 α2 α3 α1 α2 α3 0 0.007 (0.007) (0.004) 0.067 0.011 0.007 1 0.002 0.006 0.000 (0.015) (0.004) (0.020) 2 0.002 0.002 (0.004) (0.011) (0.020) (0.016) 3 (0.003) (0.004) (0.004) 0.023 (0.005) (0.008) 4 0.008 (0.013) (0.023) 0.006 0.003 (0.007) 5 (0.003) (0.001) (0.002) (0.012) (0.009) (0.007)



samples controlled by industry effect: Trading / Services sector as base Dividend Increase Dividend Decrease

T α1 α2 α3 α1 α2 α3 0 0.007 0.003 (0.001) 0.067 (0.010) 0.000 1 0.002 (0.001) (0.002) (0.015) (0.004) (0.021) 2 0.002 0.006 (0.002) (0.011) 0.022 (0.003) 3 (0.003) 0.005 (0.001) 0.023 (0.011) (0.007) 4 0.008 0.000 (0.019) 0.006 0.013 (0.003) 5 (0.003) 0.002 (0.002) (0.012) 0.010 (0.001)


97


samples controlled by industry effect: Consumer sector as base Dividend Increase Dividend Decrease

T α1 α2 α3 α1 α2 α3 0 0.007 0.002 (0.006) 0.067 (0.009) 0.006 1 0.002 0.001 0.006 (0.015) 0.001 0.001 2 0.002 0.009 0.006 (0.011) 0.020 (0.009) 3 (0.003) 0.005 (0.002) 0.023 (0.001) (0.003) 4 0.008 0.002 (0.008) 0.006 0.018 0.011 5 (0.003) 0.002 0.000 (0.012) 0.009 (0.004)

Note: Value in bold indicates significant level at p<0.05

4.3 SUMMARY OF RESEARCH RESULTS

The regression analysis presented in section 4.2 above can be summarized in

Table 4.31 to Table 4.34.

Table 4.31 Regression Result for All Firm-Year Observations from year 1998 to 2007

Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α1 α1 α1 α1 α1 α1 All Samples S+

0.017 - - - S+

0.007 -

Financial Crisis period (1998-2001)

S+ 0.031

S- -0.010

- - - -

Post-Financial Crisis period (2002-2007)

S+ 0.013

- - - - -

Stable dividend for consecutive 2 years

S+ 0.011

- - - - -


- - - S- -0.010

- -


- - - S- -0.145

- -

1998 S+ 0.095

- S- -0.044

- - -

98

Table 4.31 continued 1999 - - - - S+

0.018 -

2000 - - - S- -0.010

- -

2001 S+ 0.026

- - - - -

2002 - S+ 0.016

- - - -

2003

- - - - - -

2004 - S- -0.012

- - - -

2005

- - - - - -

2006 S+ 0.017

- - - - -

2007 S+ 0.014

- - - - -

Analysis of Dividend Signalling By Size of Dividend Change Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α1 α1 α1 α1 α1 α1 Decrease≥100% - - - - - -

Decrease 50% to <100%

S+ 0.193

- - - - -

Decrease 30% to <50%

- S- -0.378

- - - -

Decrease >0% to <30%

- - - - - -

Increase >0% to <30%

- - - - - -

Increase 30% to <50%

- - - - - -

Increase 50% to <100%

- - - - - -

Increase ≥100% - S+ 0.008

- - - -

Analysis of Dividend Signalling By Size of Dividend Yield (“DY”) Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α1 α1 α1 α1 α1 α1 DY<1% S+

0.033 - - - S+

0.044 -

1% ≤ DY < 4% S+ 0.018

S- -0.006

- - - -

4% ≤ DY < 6% S+ 0.026

- - - - -

6 % ≤ DY < 8% S+ 0.020

- - - - -

DY ≥ 8% -

- - - - -

Note: S+ indicates positive and significant beta coefficient S- indicates negative and significant beta coefficient

99

Table 4.32 Regression Result for All Dividend Increase Observations from year 1998 to

2007 Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α1 α1 α1 α1 α1 α1 All Samples S+

0.007 - - - S+

0.008 -


- - - - - -


S+ 0.010

- - - S+ 0.009

-


S+ 0.007

- - - - -


- - - - - -


- S+ 0.114

- S- -0.211

S+ 0.207

-

1998

- - - - - -

1999

- - - - - -

2000

- - - - - -

2001

- - - - - -

2002 - S+ 0.017

- - S+ 0.033

-

2003

- - - - - -

2004

- - - - - -

2005

- - - - - -

2006

- - - - - -

2007 S+ 0.008

- - - - -


100

Table 4.33 Regression Result for All Dividend Decrease Observations from year 1998 to

2007

Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α1 α1 α1 α1 α1 α1 All Samples S+

0.068 - - - - -


S+ 0.079

- S- -0.036

- - -


- - - - - -


- - - - - -


- - - - S+ 0.159

-


- - - - - -

1998 S+ 0.092

- - - - -

1999

- - - - - -

2000

- - - - - -

2001 - - - - S+ 0.067

-

2002

- - - - - -

2003

S- -0.048

- - - - -

2004

- - - - - -

2005

S+ 0.077

S- -0.075

- - - -

2006

- - - - - -

2007

- - - - - -


101

Table 4.34 Multiple regression result for industry dummies

Industry sector as base Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 All Samples - - - - - S-

(0.010) - - - S-

(0.016) - -

Dividend Increase

S- (0.007)

- - - - - - - S- (0.013)

S- (0.023)

- -

Dividend Decrease

- - - S- (0.020)

S- (0.020)

- - - - - - -

Trading / Service sector as base Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 All Samples - - - - S+

0.008 S-

(0.005) - - - S-

(0.012) - -

Dividend Increase

- - - - - - - - - S- (0.019)

- -

Dividend Decrease

- - - S- (0.021)

S- (0.022)

- - - - - - -

Consumer sector as base Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 α2 α3 All Samples - - - - S+

0.010 - - - S+

0.010 - - -

Dividend Increase

- - - - - - - - - - - -

Dividend Decrease

- - - - S+ 0.020

- - - S+ 0.018

- - -


As shown in Table 4.31, positive and significant relationships occurred most

frequently in year T=0, indicating that changes in dividends is positively related to

changes in earnings in the concurrent year under the study period. Such positive

relationship in year T=0 is attributable to stronger signalling effect of dividend change

events in year 1998 (in which dividend decrease events has stronger signalling effect

as compared with dividend increase). Stronger beta coefficient in year T=0 during the

financial crisis period (1998-2001) as compared with post-financial crisis period

(2002-2007) was due to the stronger signalling effect of dividend decrease events

during the financial crisis period as shown in Table 4.33 (α1 = 0.079, p<0.05). We can

conclude that the dividend decrease events during the financial crisis period have

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stronger signalling effect as compared with dividend increase events and dividend

cuts occurred in year 1998 have the strongest influence in determining the positive

and significant value of the beta coefficients recorded under the study period.

Only positive and significant beta coefficient was recorded for dividend decrease

between 50% to less than 100% in year T=0 and this indicates that stronger signalling

effect only occurred in year T=0 when the size of dividend decrease is very large. For

the regression analysis on different categories of dividend yield, positive and

significant relationship occurs in year T=0 when the dividend yield was less than 8%.

However, no significant relationship is found between both changes in dividends and

earnings in the concurrent year T=0 when the dividend yield is more than 8% due to

smaller sample of companies (less than 100 companies). As there is no increase in the

value of the beta coefficients when the dividend yield becomes larger, we can

conclude that no relationship exists between the size of dividend yield and the extent

of dividend signalling in the concurrent year T=0.

No strong relationships occurs between changes in dividend with changes in earnings

in the subsequent years from T=1 to T=5 as shown in Table 4.31. In most cases, there

are negative and significant relationships between changes in dividends in year T=0

with subsequent changes in earnings. Such negative relationships occurred due to the

utilization of cash reserves from dividend cuts in year T=0 in pursuing more income-

generated activities and as the consequence, the earnings of the company increases in

the subsequent years following the dividend decrease. In most circumstances, the

frequency of occurrence of positive and significant beta coefficients is higher under

the post-financial crisis period, while under the financial crisis period, most beta

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coefficients recorded negative and significant value after dividend change events in

year T=0.

An interesting result observed in year T=4 shows a weak positive and significant

relationship existed between changes in dividends in year T=0 with subsequent

changes in earnings in year T=4 (α1 = 0.007, p<0.05). Such weak positive signalling

effect was more strongly influenced by dividend increase events that occurred after

stable DPS for consecutive 4 years (refer to Table 4.32 which shows α1 = 0.207,

p<0.05). For the dividend decrease sub-sample, positive and stronger relationship

recorded for the relationship between decrease in earnings in year T=4 with decrease

in dividends in year T=0 under the scenario of stable dividend for 3 consecutive years.

Dividend decrease events that occurred after a shorter period of stable dividends i.e. 3

years recorded positive and significant beta coefficients, while for the dividend

increase sub-sample, signalling effect occurs after a longer period of stable dividends,

i.e. 4 years. Hence, we can conclude that the signalling effect of dividend decrease is

more prominent after a shorter period of stable dividend and dividend increase events

will only show its signalling effect after a longer period of stable dividend. No

positive and significant relationship is recorded between changes in dividends in year

0 with changes in earnings in year 5.

In concluding the relationship between changes in dividends with changes in earnings,

the regression result clearly shows that the relationship is stronger and prominent for

both changes in dividends and earnings in the concurrent year T=0. Hence, the

conclusions of the regression results , expressed by way of the acceptance or rejection

of the hypotheses as listed in Section 3.1 above are as follows:-

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(A) Relationship between changes in dividends in current year with changes in


Accept hypothesis HAo: Companies that change their dividends in year 0 will

not experience any changes in unexpected earnings in the following years, i.e.

year 1 to year 5. Instead, there is a positive and significant relationship

between changes in dividends and unexpected earnings in the concurrent year.

(B) Relationship between increase in dividend in current year with increase in


Accept HBo: There is no relationship between increase in dividends in the

concurrent year with increase in the unexpected earnings in the subsequent

years from year 1 to year 5. Instead, there is a positive and significant

relationship between increase in dividends with increase in unexpected

earnings in the concurrent year.

(C) Relationship between decrease in dividends in current year with decrease in

earnings in the concurrent and subsequent years

Accept HCo: There is no relationship between decrease in dividends in

current year with decreases in unexpected earnings in subsequent years from

year 1 to year 5. Instead, there is a positive and significant relationship

between decrease in dividends with decrease in unexpected earnings in the

concurrent year.

The testing of dividend signalling for each individual year from year 1998 to 2007

shows stronger and significant relationship between changes in dividends and changes

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in earnings exists in year T=0, which supports the hypothesis HA0 and HC0 above.

However when testing hypothesis B under each individual year from year 1998 to

2007, a positive relationship exists between increase in dividends in year T=0 with

increase in earnings in year T= 1 (for all firm-year observations and dividend increase

events in year 2002) and year T= 4 (for dividend increase events in year 2002), while

the remaining years shows no positive significant relationship. In view of the result

generated, we can conclude that weak signalling effect occurs for dividend increase

events in year 2002 with increase in earnings in year 2003 and 2006.

The result on the case by case analysis on dividend change events occurred after

stable dividend for consecutive 2 years, 3 years and 4 years showed that the dividend

signalling effect is stronger and prominent for both changes in earnings and dividends

in the concurrent year T=0. As shown in Table 4.31, weak positive and significant

relationship recorded in year T=0 for dividend change events that occurred after

stable dividend for 2 consecutive years (α1 = 0.011, p<0.05). Stronger positive and

significant beta coefficients occurred for the relationship between (1) increase in

dividend (after 4 years of stable dividend) with increase in earnings in year T=4 (α1 =

0.207) and (2) decrease in dividend (after 3 years of stable dividend) with increase in

earnings in year T=4 (α1 = 0.159). In view of the smaller value of beta coefficients

recorded, we can conclude that weak relationship exists between the stability of

dividend with the extent of dividend signalling as follows:-

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(D) Relationship between the stability of dividend before changes in dividends

with the extent of dividend signalling

Accept HDo: There is no relationship between the stability of dividend

before changes in dividends with the extent of dividend signalling.

The regression analysis to examine the extent of dividend signalling based on

different sizes of dividend change has further generate the following result :-

(E) Relationship between the size of changes in dividends with the extent of

dividend signalling

Accept HEo: There is no relationship between the size of changes in

dividends with the extent of dividend signalling.

The analysis on the extent of dividend signalling based on different sizes of dividend

change shows that the signalling effect becomes stronger when the size of dividend

decrease becomes larger and such positive relationship is prominent only in year T=0.

For the dividend increase events, such positive relationship between the size of

dividend increase with dividend signalling only occurs in year T=0 when the size of

dividend increase ranged between 0% to less than 50%. Further analysis on the extent

of signalling in the subsequent years from T=1 to T=5 shows that only 3 cases which

showed the positive relationship between size of dividend change with the extent of

dividend signalling as follows:-

(a) when the dividend decreases from 30% onwards, the signalling effect becomes

stronger in year T = 3 at larger dividend decrease (α1 increased from 0.015 to

0.086, insignificant with p>0.05)

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(b) when the dividend decreases from 0% to less than 50%, the signalling effect

becomes stronger in year T = 4 at larger dividend decrease (α1 increased from

0.051 to 0.155, insignificant with p>0.05)

(c) when the dividend increases from 0% to less than 50%, the signalling effect

becomes stronger in year T = 5 at larger dividend increase (α1 increased from

0.042 to 0.047, insignificant with p>0.05)

The regression analysis on the relationship between dividend yield and the extent of

dividend signalling shows dividend signalling becomes stronger when the dividend

yield increases from 1% to less than 6% and this only occurred in year T=0. No

significant continuous increase in the value of beta coefficients when the dividend

yield increases in the subsequent years from year 1 to year 5. As such, the following

conclusion is made:-

(F) Relationship between dividend yield and the extent of dividend signalling

Accept HF0: There is no relationship between dividend yield and the extent

of dividend signalling.

Finally, the following conclusion was arrived after multiple regression analysis was

performed to examine whether there is any difference between sectors in their

signalling effect when there are changes in dividends:-

(H) Industry effect in influencing the extend of dividend signalling

Accept HG0: Industry effect does not have any influence on the extent of

dividend signalling of the companies.

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The above conclusion is achieved based on the relative small beta coefficients for the

sector dummies generated from the regression analysis as shown in Table 4.34 above.

Overall, from the series of the regression results concluded above, it is clear that

dividend signalling does not exist among the Main Board listed companies in

Malaysia, which are consistent with the studies done by Grullon et al (2005) and

initial analysis done by Nissim and Ziv (2001) who had adopted the regression

equation of Benartzi et al (1997). Both studies by Nissim and Ziv (2001) and Benartzi

et al (1997) showed the beta coefficient α1 is positive and highly significant in year T

= 0 but is insignificant for T =1 and T=2.

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CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS 5.1 CONCLUSION

The result of this study shows that Main Board companies do not use dividends as a

signalling tool to convey future prospect of the companies, which is consistent with

the findings by Grullon et al (2005) and Nissim and Ziv (2001). Positive and

significant relationship exists between changes in dividends and changes in earnings

in the concurrent year T=0, which strongly proved that changes in dividends are

related to changes in earnings in the past. In fact, in most circumstances, dividend

decreases has a stronger signaling effect in the concurrent year T=0 and are not

related to future profitability, which is consistent with the research findings by

Grullon et al (2005). Overall, the positive and significant relationship between both

changes in dividends and earnings in the concurrent year T=0 for all firm-year

observations under the study period from 1998 to 2007 was strongly influenced by the

dividend decrease events occurred in year 1998. Separate studies on both financial

crisis period and post-financial crisis period shows difference in the signaling effect of

dividend increase and dividend decrease events; with the former has a stronger

signaling effect post-financial crisis period, while the later has a stronger signaling

effect during the financial crisis period.

A comparison amongst the dividend change events that occurred after consecutive 2

years, 3 years and 4 years of stable dividend shows that the signalling effect of

dividend decrease is more prominent after a shorter period of stable dividend as

compared with dividend increase. While the dividend increase events show stronger

signalling effect after a longer period of stable dividend. The result is consistent with

the Lintner (1956) which showed that firms rarely changed their dividend policies

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unless the management of the firms were confident that the firms can maintain the

higher or lower level of dividends in the future. Hence, investors may consider a cut

in dividends as a stronger signal as compared with the dividend increase events.

However, no strong signalling effect is observed for dividend change events that

occurred after longer period of stable dividends, which supports the acceptance of

hypothesis HD0 above.

Regressions to test the extent of dividend signalling given different sizes of dividend

change and dividend yield were conducted based on the assumptions that the bigger

the size of the dividend changes and dividend yield, the stronger the signalling effect

as dividends are sticky (firms rarely change their dividends). Hence any major

changes in dividends may be viewed by the investors as signals by the firms on the

future prospects of the firm. For the relationship between the dividend yield and the

extent of dividend signalling, regression is performed on the rationale of clientele

effect. The results on both regressions show that (1) no strong relationship exists

between the size of dividend change with the extent of dividend signalling and (2) no

strong relationship exists between the size of dividend yield with the extent of

dividend signalling. The result of the regression to test the dividend signalling based

on different sizes of dividend changes shows a stronger significant relationship

existed for dividend decrease and concurrent earnings decrease in year T=0. For the

regression result on the relationship between the size of dividend yield and the extent

of dividend signalling, positive and significant relationship exists for the dividend

yield ranges from 1% to less than 6% in year T=0. For subsequent years from T=1 to

T=5, the regression results showed mixed results with both positive and negative

value of beta coefficient and no consistent increase in the beta coefficients values

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when the dividend yield increases.

Finally, multiple regressions by incorporating industry effect or “peer influence”

proved that industry effect does not exist, as can be observed from the low value of

the beta coefficient of the sector dummies (α2, α3). In other words, there is no different

in the changes in earnings between the sectors when there are changes in dividends.

To further obtain the evidence that Main Board listed companies in Malaysia do not

use changes in dividend to signal information on the future prospects of the

companies, informal interviews were conducted with a few Group Accountant and

Chief Financial Officers of Main Board listed companies. All of them agreed that

dividend signalling does not exist in Malaysia and there are certain established

corporations which adopt dividend signalling theory while majority are still catching

up with the ideas of dividend signalling. Some of them claimed that the dividend

behaviour of listed companies in Malaysia is more towards dividend speculation

rather than dividend signalling as controlling shareholders would have the most

influence in the dividend payouts of the investee company unless the company adopts

a clear dividend policy which spells out the quantum of dividend payout per dollar

earned. The reasons of dividend are not used as a signalling tool to the investors can

be summarized as follows:-

(1) Earnings in the future are unpredictable

The earnings of a company is unpredictable in the future and hence changes in

dividend shall not be used as a signalling tool. This statement supports

Lintner’s findings in the United States that firms were reluctant to increase

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dividends to levels that cannot be sustained. The concept of “sticky dividends”

as per Lintner’s findings was also noted by Donaldson (1961) in which the

later observed that although the firms in the United States have target payout

ratios to their investment opportunities, any changes in dividend payments

were done gradually to void sudden changes in dividend payments.

(2) Composition of the shareholders

The inexistence of dividend signalling in Malaysia conveys an important

earnings behaviour following changes in dividend in which in most

circumstance an increase (decrease) in the dividends in year T=0 will be

followed by a decrease (increase) in the earnings in the subsequent years. Such

phenomena may be attributable to the dividend policy of a company which is

more focus on paying higher dividends regardless of its earnings position. The

decision of continuously paying dividends to investors was attributable to the

composition of its shareholders who value dividends as a “sure” return as

compared with share price appreciation, which we referred as to the “Bird-in-

Hand Fallacy”. For companies controlled by institutional investors or the

company is a trustee stock company11, such companies may maintain certain

period of uninterrupted dividend payments in accordance to the investment

guidelines or investment philosophy of such institutional investors which

require continuous payment of dividends as a source of investment income.

1 For shares categorised as trustee stock in accordance to Section 4 of Tustee Act 1949, the company must have (1) paid-up share capital of not less than RM5 million; (2) pay dividend not less than 5% for the past 3 years; and (3) total amount of borrowings (including interest due) does not exceed 2/3 of the borrowing amount from the borrower.

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(3) Section 108 of Income Tax Act

This Section can be considered as a constraining factor on the dividend

payments of the company as Malaysian companies generally pay dividend

without incurring additional tax payment to the government by not paying

dividends more than the amount allowed by Section 108 credit balance of

notional account. Credit entry will be made for the current year’s income tax

payable while a tax deduction on the gross dividend declared is debited into

the account.

(4) Fulfilment of shareholders’ need on return on investment

Some respondents mentioned that one of the reason dividend signalling does

not exist in Malaysia is due to the companies wish to fulfil the need of

shareholders to get their dividends as a source of return on their investments,

especially during the period of losses, albeit a smaller sum.

(5) Fund requirement for expansion in the future

According to the reply from the respondents, it is quite common for the

companies to pay consistent dividends as to reserve funds for expansions or

dividend payment in the future and therefore dividend signalling does not

happen in Malaysia.

(6) More concern on changes in share price as compared with dividend

Companies do not use dividends as a signalling tool to the investors may be

attributable to Malaysian investors who do not pay much attention to dividend

announcement. Instead, more concern is placed on share price appreciation as

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a “short-term” return to the investors.

Subsequent to the interviews conducted on Group Accountants and Chief Financial

Officers of Main Board listed companies on their views on dividend signalling,

further examination on previous literatures in dividend policy in other countries

shows that other possible reasons or factors that caused the inexistence of dividend

signalling as follows:-

(7) Difference in the firm’s characteristics

Although managers in some extent may use dividend (especially dividend

decease) to convey useful information on the firm’s future prospect, changes

in dividends are not perfect signals to the investors. According to research

done by Easterbrook (1994), dividend increase may be an ambiguous signal

unless the market can distinguish between growing firms and firms with a lack

of investment opportunities. A growing firm may reduce its dividend payment

for strategic investments in income generating assets or expansion of its

operations but experience increase in earnings following a dividend cut, which

can be explained by the increase in return generated from the new investment

made in pervious year.

(8) Dividend smoothing behaviour of firms

Although managers advocated a long-range target payout ratio (Fama and

Babiak, 1968; Baker et al, 1985), most managers believe that shareholders

prefer a steady increase of dividends. Hence, managers sought to avoid

making changes in their dividend payment that might have to be reversed in

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the future although they foresee possible earnings reduction in the coming

years. Therefore, managers tend to make partial adjustments toward a target

payout ratio rather than dramatic changes in the dividends. In other words,

managers “smooth” their dividend payment in the short run to avoid frequent

changes in the future.

(9) Changes in dividends are related to permanent cash flow increase

Research by Yaron (1998) showed that only firms with permanent increase in

cash flow will increase their dividends. In his study which established the

direct link between positive income shocks, dividend decisions and stock

returns, his result showed that all or even most dividend decisions were not

signalling the future profitability. The subdivision of the firms into (1) firms

with permanent increase in cash flows and (2) firms with temporary increase

(“TI”) in cash flows showed that TI firms will increase their dividends

substantially when their cash flows increase. Following the initial increase in

dividends, the dividends of the TI firms will continue to increase at a slower

rate despite the fall of cash flow in the subsequent years. It shows that the TI

firms are reluctant to acknowledge negative earnings information and do not

aware of the continue deteriorating of their financial performance. Yaron’s

result is consistent with the result of Benartzi et al (1997) which showed that

dividends are related to the past and not future earnings. In addition, the

research result shows that the size of dividend increases in prior years have no

relationship with future changes in earnings, which are consistent with the

result of this research study.

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(10) Concern of managers on market reaction towards dividend change events

As most shareholders react to dividend change announcement by interpreting

the dividend increase as positive signals and vice versa, managers normally do

not use dividends as signals for negative information. DeAngelo et al (1992)

argued that the reliability of dividends as a signalling mechanism was reduced

by the over optimism of the managers and small cash obligations associated

with dividend increase.

(11) Availability of other mechanism of profit distribution

Firms that decrease their dividends may accumulate cash for their proposed

share-buybacks as another mechanism of profit distribution to shareholders.

When a firm implement its share-buybacks, the firm believes that the shares of

the firms are undervalued with good prospects. According to Vermaelen

(1984), share-buybacks signals improved future profitability. Hence a decrease

in dividend may be followed by an increase in earnings in the following years.

In relation to the question on whether the respondent’s company dividend decision is

influenced by dividend decisions of other company (i.e. industry effect in the dividend

decision), all the respondents agree that in some extent, dividend decisions or

announcement by their peers served as a guide to their dividend decisions but will not

influence the dividend decisions of the company. This is due to (1) every company

performed differently from their peers in term of profitability and cash flows; (2)

dividend payment tends to follow previous dividend payout track record; and (3)

every company has its own capital expenditure requirement, i.e. need to retain certain

amount of cash not distributable as dividends and (4) the dividend decision of a

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company is not comparable with other dividend decisions of other companies as some

Malaysian listed companies have varied interests in other businesses other than their

mainstay.

Given the result of the research, we can conclude that changes in dividend are not

strong signalling tools for the Main Board companies in Malaysia and hence investors

should not rely to dividend change to predict future prospect of a company.

5.2 SUGGESTIONS FOR FUTURE RESEARCH

The current study on dividend signaling of Main Board listed companies covers a

relatively smaller number of firm-year observations as compared with major dividend

signalling studies conducted in other developed markets. For researchers who wish to

conduct more in depth studies on dividend signalling in Malaysia in the future, they

may consider the following suggestions:-

(a) Studies shall cover both Main Board and Second Board companies in

Malaysia. Comparisons between the regression results on Main Board

companies with Second Board companies could be done to examine the

differences in terms of signalling effect of these companies.

(b) Generally, most of the studies on dividend signalling covered annual

dividends changes with no strong support on dividend signalling hypothesis.

Researchers might consider to study on the relationship between special

dividends and interim dividends declared by companies that rarely practiced

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such profit distribution in the past to examine whether the declaration of

special dividends and interim dividends conveys forward-looking information.

(c) Companies with different ownership structure might be different in

communicating their future prospects to the external shareholders as

companies that are mostly controlled by the management and employees

might not use dividend as signalling tool. Researchers might conduct studies

on two different group of companies (highly concentrated in ownership and

dispersed ownership companies) to examine the dividend signalling effect.

(d) Current research results do not support the dividend signalling hypothesis for

the Main Board listed companies in Malaysia due to factors such as

shareholder structure, income tax regulation in Malaysia etc, which are

obtained from informal interviews. As such, research studies in the future may

structure the study on dividend signalling by way of structured questionnaires

or face-to-face interviews with the chief financial officers of the listed

companies to study on the factors that affect the dividend decision of the

company.

Generally, many possibilities and factors that may affect the signalling effect of

dividend and researchers should explore other factors that may influence the dividned

signaling in Malaysia.

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APPENDICES

Appendix 1

Descriptive Statistics for DPS (sen) paid by Main Board companies categorized by sector Sector 2002 2003 2004 2005 2006 2007Consumer No of companies 53 60 64 73 71 71 Max (sen) 201.00 329.00 247.00 216.00 275.00 256.00 Min (sen) 0.50 0.40 0.70 0.70 0.50 0.20 Mean (sen) 12.96 18.75 13.35 13.43 17.52 15.46 Std Deviation 30.14 56.47 32.53 31.52 40.15 34.96 Variance 908.15 3189.04 1058.11 993.21 1612.09 1222.14Industrial No of companies 80 91 100 108 110 110 Max (sen) 21.60 135.00 28.80 55.40 79.20 55.00 Min (sen) 0.10 0.10 0.10 0.40 0.40 0.20 Mean (sen) 4.66 6.95 5.67 6.18 6.21 6.67 Std Deviation 4.29 15.03 5.82 7.50 9.20 7.77 Variance 18.44 225.98 33.88 56.30 84.69 60.43Construction No of companies 19 24 26 31 28 32 Max (sen) 8.00 11.50 15.10 14.90 11.50 38.60 Min (sen) 0.70 0.70 0.70 0.70 0.70 0.70 Mean (sen) 4.01 4.07 4.30 4.12 4.31 6.94 Std Deviation 2.37 2.57 3.22 3.46 3.37 8.76 Variance 5.61 6.58 10.40 11.95 11.38 76.81Trading/Services No of companies 66 75 83 92 92 102 Max (sen) 137.00 36.20 50.40 77.00 51.50 100.00 Min (sen) 0.30 0.50 0.60 0.40 0.20 0.40 Mean (sen) 9.14 5.99 6.05 7.08 6.91 9.00 Std Deviation 21.48 7.43 8.14 11.12 9.41 14.64 Variance 461.55 55.20 66.21 123.56 88.53 214.33Technology No of companies 11 10 13 13 14 14 Max (sen) 40.80 49.80 58.60 37.50 39.50 40.00 Min (sen) 0.40 0.40 0.10 0.10 0.10 0.30 Mean (sen) 7.69 8.99 8.57 7.48 7.94 7.68 Std Deviation 11.52 14.84 15.43 9.90 10.17 10.14 Variance 132.61 220.15 238.00 98.08 103.38 102.87IPC No of companies 2 2 2 3 5 6 Max (sen) 6.70 6.70 6.70 6.90 38.50 92.00 Min (sen) 3.90 5.90 5.90 3.30 3.00 1.50 Mean (sen) 5.30 6.30 6.30 5.60 11.92 20.50 Std Deviation 1.98 0.57 0.57 2.00 14.97 35.20 Variance 3.92 0.32 0.32 3.99 224.07 1239.30Finance No of companies 25 25 27 31 32 33 Max (sen) 15.00 44.40 44.60 75.90 61.20 121.00 Min (sen) 0.70 0.70 0.40 0.70 0.70 0.10 Mean (sen) 4.95 8.03 9.68 12.15 12.39 18.99 Std Deviation 3.81 10.00 11.42 17.56 15.49 26.68 Variance 14.52 99.91 130.31 308.44 239.84 711.69Hotels No of companies 3 3 3 3 3 3 Max (sen) 4.30 4.30 4.70 5.40 5.80 5.80 Min (sen) 0.20 0.70 0.70 1.30 1.40 1.50 Mean (sen) 1.73 1.90 2.17 2.70 2.87 3.17 Std Deviation 2.24 2.08 2.20 2.34 2.54 2.31 Variance 5.00 4.32 4.85 5.47 6.45 5.32

Appendix 1

Sector 2002 2003 2004 2005 2006 2007Properties No of companies 46 51 52 55 53 51 Max (sen) 25.20 28.80 32.40 36.00 46.80 47.50 Min (sen) 0.20 0.10 0.50 0.70 0.50 0.30 Mean (sen) 4.03 4.06 5.00 5.74 6.34 6.83 Std Deviation 4.77 4.47 5.14 5.77 7.47 7.58 Variance 22.78 20.02 26.40 33.26 55.79 57.44Plantations No of companies 29 32 32 32 34 37 Max (sen) 21.10 26.00 49.70 23.80 34.20 34.70 Min (sen) 0.30 0.10 0.70 1.10 0.70 0.70 Mean (sen) 5.43 6.84 9.27 8.55 8.96 9.89 Std Deviation 5.83 6.79 10.25 6.39 8.59 9.17 Variance 33.96 46.15 104.99 40.78 73.81 84.04Mining No of companies 0 1 1 1 1 1 Max (sen) - 0.20 0.10 0.40 0.30 1.60 Min (sen) - 0.20 0.10 0.40 0.30 1.60 Mean (sen) - 0.20 0.10 0.40 0.30 1.60 Std Deviation - - - - - - Variance - - - - - - REITS No of companies 2 2 2 2 5 13 Max (sen) 4.70 4.4 3.70 4.30 10.90 12.90 Min (sen) 2.40 1.9 0.80 2.50 2.40 2.00 Mean (sen) 3.55 3.15 2.25 3.40 4.72 5.86 Std Deviation 1.63 1.77 2.05 1.27 3.61 3.23 Variance 2.65 3.13 4.21 1.62 13.07 10.43Closed-End Funds No of companies 0 0 1 0 1 1 Max (sen) - - 2.00 - 4.00 4.50 Min (sen) - - 2.00 - 4.00 4.50 Mean (sen) - - 2.00 - 4.00 4.50 Std Deviation - - - - - - Variance - - - - - - Total No of companies 336 376 406 444 449 474 Max (sen) 201.00 329.00 247.00 216.00 275.00 256.00 Min (sen) 0.10 0.10 0.10 0.10 0.10 0.10 Mean (sen) 6.88 8.10 7.37 7.93 8.75 9.78 Std Deviation 16.02 24.68 14.93 15.52 18.52 18.43 Variance 256.54 608.86 223.02 240.93 342.91 339.53

Appendix 2

Descriptive Statistics for DPR paid by Main Board companies categorized by sector Sector 2002 2003 2004 2005 2006 2007Consumer No of companies 53 60 64 73 71 71 Max 2.50 36.00 3.13 4.14 3.81 3.47 Min -4.62 -4.14 -1.20 -1.08 -0.21 -1.93 Mean 0.33 1.25 0.56 0.52 0.66 0.56 Std Deviation 0.92 4.97 0.63 0.59 0.64 0.57 Variance 0.85 24.68 0.40 0.35 0.41 0.33Industrial No of companies 80 91 100 108 110 110 Max 25.00 16.67 5.00 6.67 15.00 11.00 Min -43.00 -1.29 -7.29 -1.92 -5.00 -2.00 Mean 0.10 0.77 0.27 0.50 0.53 0.46 Std Deviation 5.72 2.01 1.05 0.94 1.61 1.12 Variance 32.69 4.03 1.10 0.88 2.60 1.25Construction No of companies 19 24 26 31 28 32 Max 3.14 4.40 0.82 3.60 1.03 1.78 Min -0.25 -2.67 -3.67 -0.48 -0.43 -0.19 Mean 0.39 0.41 0.09 0.38 0.31 0.35 Std Deviation 0.69 1.08 0.85 0.68 0.31 0.37 Variance 0.48 1.17 0.72 0.46 0.10 0.14Trading/Services No of companies 66 75 83 92 92 102 Max 4.54 3.60 16.80 11.43 7.22 6.67 Min -0.24 -7.00 -1.17 -25.00 -0.07 -0.75 Mean 0.57 0.28 0.59 0.26 0.60 0.56 Std Deviation 0.84 1.14 1.91 2.95 0.99 0.87 Variance 0.70 1.30 3.64 8.68 0.98 0.75Technology No of companies 11 10 13 13 14 14 Max 1.17 2.12 0.89 2.33 1.41 1.39 Min -2.72 -4.13 0.04 -0.47 -0.23 -2.00 Mean -0.06 0.10 0.46 0.56 0.46 0.34 Std Deviation 1.26 1.60 0.27 0.71 0.41 0.76 Variance 1.59 2.56 0.07 0.50 0.16 0.58IPC No of companies 2 2 2 3 5 6 Max 0.68 0.60 0.55 0.51 0.47 0.74 Min 0.23 0.55 0.45 0.17 0.20 0.02 Mean 0.46 0.57 0.50 0.39 0.35 0.37 Std Deviation 0.32 0.03 0.07 0.19 0.11 0.25 Variance 0.10 0.00 0.00 0.04 0.01 0.06Finance No of companies 25 25 27 31 32 33 Max 12.00 3.58 1.18 3.21 1.75 6.05 Min -0.48 -12.00 -5.22 -36.00 -3.57 -0.61 Mean 0.84 -0.07 0.15 -1.33 0.37 0.63 Std Deviation 2.35 2.66 1.11 7.53 0.84 1.08 Variance 5.54 7.08 1.23 56.74 0.71 1.16Hotels No of companies 3 3 3 3 3 3 Max 2.26 1.16 0.43 0.95 0.72 0.55 Min -0.07 0.23 0.20 0.16 0.16 0.23 Mean 0.97 0.80 0.28 0.48 0.41 0.37 Std Deviation 1.19 0.50 0.13 0.42 0.28 0.16 Variance 1.41 0.25 0.02 0.17 0.08 0.03

Appendix 2

Sector 2002 2003 2004 2005 2006 2007Properties No of companies 46 51 52 55 53 51 Max 4.20 2.44 8.00 2.40 2.53 4.40 Min -3.50 -1.40 -22.00 -1.29 -0.16 -3.56 Mean 0.36 0.36 0.16 0.40 0.58 0.47 Std Deviation 0.92 0.54 3.35 0.44 0.65 0.90 Variance 0.85 0.29 11.24 0.20 0.42 0.80Plantations No of companies 29 32 32 32 34 37 Max 1.52 0.97 1.83 3.71 1.38 1.03 Min -0.05 -0.03 0.03 0.14 -0.13 0.03 Mean 0.47 0.37 0.44 0.65 0.49 0.38 Std Deviation 0.40 0.27 0.39 0.66 0.36 0.25 Variance 0.16 0.07 0.15 0.43 0.13 0.06Mining No of companies 0 1 1 1 1 1 Max - 2.00 0.04 0.31 -N/A- 0.11 Min - 2.00 0.04 0.31 -N/A- 0.11 Mean - 2.00 0.04 0.31 -N/A- 0.11 Std Deviation - - - - - - Variance - - - - - - REITS No of companies 2 2 2 2 5 13 Max 1.27 1.10 0.95 0.96 0.96 1.14 Min -1.26 0.95 0.95 0.48 0.33 0.24 Mean 0.00 1.03 0.95 0.72 0.70 0.74 Std Deviation 1.79 0.11 - 0.34 0.29 0.29 Variance 3.21 0.01 - 0.11 0.08 0.09Closed-End Funds No of companies 0 0 1 0 1 1 Max - - -3.33 - 0.85 0.64 Min - - -3.33 - 0.85 0.64 Mean - - -3.33 - 0.85 0.64 Std Deviation - - - - - - Variance - - - - - - Total No of companies 336 376 406 444 449 474 Max 25.00 36.00 16.80 11.43 15.00 11.00 Min -43.00 -12.00 -22.00 -36.00 -5.00 -3.56 Mean 0.37 0.56 0.36 0.32 0.54 0.50 Std Deviation 2.93 2.42 1.64 2.50 1.02 0.84 Variance 8.57 5.86 2.71 6.25 1.03 0.70

Appendix 3

Descriptive Statistics for Dividend Yield (%) by Main Board companies categorized by sector Sector 2002 2003 2004 2005 2006 2007Consumer No of companies 53 60 64 73 71 71 Max 12.48 110.40 14.07 17.25 78.50 12.64 Min 0.17 0.45 0.53 0.55 0.64 0.10 Mean 3.18 4.35 3.48 3.89 5.10 4.17 Std Deviation 1.88 7.72 2.34 2.19 6.07 2.26 Variance 3.54 59.56 5.50 4.82 36.80 5.10Industrial No of companies 80 91 100 108 110 110 Max 10.87 116.38 16.19 18.10 14.50 17.07 Min 0.09 0.05 0.08 0.38 0.08 0.25 Mean 2.83 3.87 2.91 3.59 3.53 3.29 Std Deviation 1.77 7.27 2.11 2.06 2.16 2.02 Variance 3.12 52.92 4.45 4.26 4.67 4.06Construction No of companies 19 24 26 31 28 32 Max 7.56 6.35 5.69 10.21 9.86 9.01 Min 0.22 0.47 0.54 0.56 0.48 0.28 Mean 2.15 2.21 2.23 2.97 2.86 2.47 Std Deviation 1.07 1.10 0.85 1.60 1.77 1.56 Variance 1.15 1.20 0.72 2.57 3.14 2.44Trading/Services No of companies 66 75 83 92 92 102 Max 57.08 16.45 24.00 26.74 9.73 82.64 Min 0.20 0.14 0.23 0.19 0.15 0.18 Mean 3.39 2.67 2.48 3.01 2.95 3.34 Std Deviation 5.61 2.39 1.88 2.46 1.73 4.69 Variance 31.52 5.71 3.55 6.07 3.01 22.03Technology No of companies 11 10 13 13 14 14 Max 2.75 5.06 4.51 9.00 8.60 8.62 Min 0.18 0.22 0.37 0.15 0.38 0.42 Mean 1.82 1.89 2.06 3.33 3.48 3.49 Std Deviation 1.05 0.97 0.93 1.61 1.99 1.89 Variance 1.10 0.95 0.86 2.58 3.95 3.58IPC No of companies 2 2 2 3 5 6 Max 6.44 5.28 4.47 4.23 7.14 6.09 Min 1.38 2.15 2.12 1.11 1.34 0.49 Mean 3.52 3.57 3.25 2.57 3.05 2.86 Std Deviation 2.76 1.42 1.18 1.17 1.07 1.65 Variance 7.59 2.02 1.39 1.38 1.14 2.73Finance No of companies 25 25 27 31 32 33 Max 5.88 9.35 8.51 10.40 9.95 39.29 Min 0.43 0.53 0.22 0.74 0.80 0.07 Mean 2.09 2.73 2.86 3.52 3.46 4.17 Std Deviation 1.22 1.70 1.75 2.16 1.84 5.07 Variance 1.48 2.89 3.05 4.67 3.38 25.73Hotels No of companies 3 3 3 3 3 3 Max 4.48 5.06 4.48 4.70 4.68 4.07 Min 0.26 0.89 1.13 1.07 0.70 0.50 Mean 1.77 2.27 2.24 2.88 2.28 1.95 Std Deviation 1.94 1.79 1.48 1.38 1.18 1.15 Variance 3.77 3.21 2.20 1.90 1.39 1.32

Appendix 3

Sector 2002 2003 2004 2005 2006 2007Properties No of companies 46 51 52 55 53 51 Max 21.00 10.48 12.00 21.18 10.97 14.23 Min 0.32 0.36 0.30 0.40 0.45 0.43 Mean 2.63 2.55 2.73 3.89 3.87 2.79 Std Deviation 2.34 1.25 1.49 2.26 1.84 1.24 Variance 5.49 1.57 2.22 5.12 3.37 1.54Plantations No of companies 29 32 32 32 34 37 Max 6.92 7.90 16.03 6.94 8.59 7.30 Min 0.09 0.06 0.06 0.11 0.21 0.22 Mean 2.34 2.78 3.33 3.21 2.76 2.36 Std Deviation 1.56 1.72 2.75 1.48 1.53 1.21 Variance 2.42 2.96 7.54 2.19 2.35 1.47Mining No of companies 0 1 1 1 1 1 Max - 0.39 0.14 0.55 0.42 1.72 Min - 0.25 0.07 0.36 0.06 1.01 Mean - 0.31 0.09 0.43 0.11 1.27 Std Deviation - - - - - - Variance - - - - - - REITS No of companies 2 2 2 2 5 13 Max 7.34 7.33 5.78 7.05 7.04 10.69 Min 4.00 2.68 1.25 5.00 1.00 1.00 Mean 5.62 4.90 3.53 5.80 4.47 4.68 Std Deviation 1.09 2.29 2.82 0.07 2.29 2.15 Variance 1.20 5.26 7.94 0.01 5.22 4.64Closed-End Funds No of companies 0 0 1 0 1 1 Max - - 2.82 - 5.19 5.29 Min - - 2.50 - 4.35 3.88 Mean - - 2.65 - 4.73 4.48 Std Deviation - - - - - - Variance - - - - - - Total No of companies 336 376 406 444 449 474 Max 57.08 116.38 24.00 26.74 78.5 82.64 Min 0.09 0.05 0.06 0.11 0.06 0.07 Mean 2.81 3.18 2.84 3.47 3.58 3.34 Std Deviation 2.98 4.96 2.00 2.14 3.04 3.03 Variance 8.86 24.59 4.00 4.59 9.26 9.21

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