capital structure and dividend policy in a personal tax free environment

CAPITAL STRUCTURE AND DIVIDEND POLICY IN A PERSONAL TAX FREE ENVIRONMENT: THE CASE

OF OMAN

Khamis Al Yahyaee

SCHOOL OF BANKING AND FINANCE THE UNIVERSITY OF NEW SOUTH WALES

A dissertation submitted to the University of New South Wales in fulfillment of the requirements for the degree of Doctor of Philosophy.

2006

ii

CERTIFICATION

I hereby declare that this submission is my own work and to the best of my knowledge it

contains no materials previously published or written by another person, or substantial

proportions of material which have been accepted for the award of any other degree or

diploma at UNSW or any other educational institution, except where due

acknowledgment is made in the thesis. Any contribution made to the research by others,

with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the

thesis. I also declare that the intellectual content of this thesis is the product of my own

work, except to the extent that assistance from others in the project’s design and

conception or in style, presentation and linguistic expression is acknowledged.

Signed _________________________________________________________________

Date _________________________________________________________________

iii

COPYRIGHT STATEMENT I hereby grant the University of New South Wales or its agents the right to archive and

to make available my thesis or dissertation in whole or part in the University libraries in

all forms of media, now or here after known, subject to the provisions of the Copyright

Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to

use in future works (such as articles or books) all or part of this thesis or dissertation.

I also authorise University Microfilms to use the 350 word abstract of my thesis

in Dissertation Abstract International. I have either used no substantial portions of

copyright material in my thesis or I have obtained permission to use copyright material;

where permission has not been granted I have applied/will apply for a partial restriction

of the digital copy of my thesis or dissertation.

Signed _________________________________________________________________

Date _________________________________________________________________

iv

AUTHENTICITY STATEMENT

I certify that the library deposit digital copy is a direct equivalent of the final officially

approved version of my thesis. No emendation of content has occurred and if there are

any minor variations in formatting, they are the result of the conversion to digital format.

Signed _________________________________________________________________

Date _________________________________________________________________

v

ABSTRACT

This dissertation examines four specific aspects of capital structure and dividend policy.

The first issue concerns the determinants of capital structure dynamics. The primary

objective is to examine whether stock returns are important factors in firm’s capital

structure choice, and if so, whether this effect is persistent. In so doing, we use a data

set which (1) avoids the complexity of tax rates faced by previous studies, (2) we

introduce new variables that are unique to Oman, and (3) we distinguish empirically

between bank debt and non-bank debt. We find stock returns are a first order

determinant of capital structure. Firms do show some tendency to rebalance towards

their target capital structure. However, the impact of stock returns dominates the effects

of rebalancing. We also find new evidence that firms do take countermeasures to offset

changes in their leverage that stem from equity value variations, but do so at a low

speed.

The next topic studied concerns the ex-dividend day behaviour. We investigate

this issue using a unique data set where there are no taxes on dividends and capital gains

and stock prices are decimalized. In this economy, any price decline that is smaller than

the dividends can not be attributed to taxes and price discreteness. We find that the

stock price drops by less than the amount of dividends and there is a significant positive

ex-day return. We are able to account for our results using market microstructure

models.

The third issue investigated is the stock price reaction to dividend

announcements. Tax-based signaling models argue that dividends would not have

vi

information and be informative if it is not for the higher taxes on dividends relative to

capital gains that they apply to shareholders. The absence of personal taxes in Oman

presents a valuable opportunity to test this prediction. Our results show that the

announcements of dividend increases (decreases) are associated with a stock price

increase (decrease) which contradicts the tax-based signaling models.

The final chapter analyzes the determinants and stability of dividend policy of

financial and non-financial firms. Investigating this issue is important for at least two

reasons. First, Omani firms distribute almost 100% of their profits in dividends which

led the Capital Market Authority (CMA) to issue a circular (number 12/2003) arguing

that firms should retain some of their earnings for “rainy days”. This allows us

understand the characteristics of firms that pay dividends. Second, firms are highly

levered mainly through bank loans which render the role of dividends in reducing the

agency costs less important. Unlike most previous studies, we include both dividend

paying and non-dividend paying firms to avoid a selection bias. We find that there are

some common factors that determine dividend policy of both financial and non-financial

firms and there are some factors that affect only non-financial firms. We also find that

the factors that influence the probability to pay dividends are the same factors that drive

the amount of dividends paid for both financial and non-financial firms. We document

that non-financial firms adopt a policy of smoothing dividends while financial firms do

not have a stable dividend policy.

vii

ACKNOWLEDGMENTS

Above all, I would like to express my gratitude to Professor Terry Walter, my thesis

advisor, for exceptional guidance, detailed comments, critical inputs, and his time.

Without his support and assistance, this thesis would have never been completed. I

would also like to express my indebtedness to Associate Professor Toan Pham, my co-

supervisor, for his valuable feedback, warm encouragement, and support. I am also

thankful to Associate Professor Ah Boon Sim for valuable advice on econometric issues

and to Dr. Jason Zien for his assistance in some parts of this thesis.

I would also like to thank the participants at the 18th PhD Conference in

Economics and Business and in particular to Professor Tom Smith and Professor

Richard Heaney for their valuable suggestions and insights. I am also thankful to the

participants at the 17th Asian FA/FMA Conference and in particular to Associate

Professor Ronal Hoffmeister, Dr. Otto Reich, and Dr. Ravi Jain. I extend my

appreciation to Professor Ivo Welch for helping with some data and methodology issues.

I would also like to acknowledge useful comments from Professor John Graham,

Professor Palani-Rajan Kadapakkam, and Professor Keith Jakob. I am also grateful to

Dr. Hatem Al Shanfari and Dr. Fahim Al Marhubi for their support and assistance in

obtaining the data. I must thank the Muscat Securities Market, Capital Market

Authority, the Central Bank of Oman, and SIRCA for providing the data used in this

thesis.

The support of my family can not be acknowledged enough. I am dearly grateful

to my parents for their endless encouragement and continued support to finish this work.

viii

I am indebted for life to my wife for her love, sacrifice, and for sharing the burden of

graduate study. I am very fortunate to have such a wonderful and considerate wife.

Additionally, I thank my lovely daughter, Hadil, for her being with me.

ix

TABLE OF CONTENTS

CERTIFICATION ii

COPYRIGHT STATEMENT iii

AUTHENTICITY STATEMENT iv

ABSTRACT v

ACKNOWLEDGEMENTS vii

TABLE OF CONTENTS ix

LIST OF TABLES xv

CHAPTER 1: INTRODUCTION .............................................................................................1

CHAPTER 2: WHAT ARE THE DETERMINANTS OF CAPITAL STRUCTURE? EVIDENCE

FROM A COUNTRY WITH UNIQUE FINANCING ARRANGEMENTS .....................................8

2.1. INTRODUCTION ...........................................................................................................8

2.2. DATA AND METHODOLOGY......................................................................................15

2.2.1. Data ....................................................................................................................15

2.2.2. Measures of Leverage ........................................................................................16

2.2.3. Empirical Model ................................................................................................17

2.2.4. Descriptive Statistics..........................................................................................20

2.3. ESTIMATION RESULTS ..............................................................................................25

2.3.1. Regression Specification....................................................................................25

2.3.2. Changes in Capital Structure..............................................................................29

2.3.3. Does the Form of Debt Matter? .........................................................................30

2.3.4. Can Adjustment Costs Explain the Inertia Behaviour?......................................31

x

2.3.5. Variance Decomposition....................................................................................33

2.4. OTHER DETERMINANTS OF CAPITAL STRUCTURE ..................................................35

2.4.1. Tax .....................................................................................................................35

2.4.2. Government Ownership .....................................................................................37

2.4.3. Soft Loans ..........................................................................................................37

2.4.4. Signaling ............................................................................................................38

2.4.5. Profitability ........................................................................................................39

2.4.6. Tangibility ..........................................................................................................40

2.4.7. Size.....................................................................................................................42

2.4.8. Non Debt Tax Shields (NDTS) ..........................................................................43

2.4.9. Growth ...............................................................................................................45

2.4.10. Volatility ..........................................................................................................46

2.4.11. Interest Coverage .............................................................................................47

2.4.12. Industry ............................................................................................................47

2.4.13. Liquidity...........................................................................................................48

2.4.14. Future Stock Return Reversals.........................................................................49

2.5. DETERMINANTS OF CHANGE IN LEVERAGE.............................................................49

2.6. ARE THE RESULTS SENSITIVE TO THE USE OF BANK DEBT? ..................................57

2.7. COMPARISONS WITH THE CURRENT LITERATURE ..................................................61

2.8. CONCLUSION.............................................................................................................67

CHAPTER 3: EX-DIVIDEND DAY BEHAVIOUR IN THE ABSENCE OF TAXES AND PRICE

DISCRETENESS .................................................................................................................70

3.1. INTRODUCTION .........................................................................................................70

3.2. THEORY, HYPOTHESIS, AND EMPIRICAL EVIDENCE ...............................................74

3.2.1. Tax Explanations................................................................................................74

3.2.1.1. Empirical Evidence .....................................................................................76

xi

3.2.2. The Interactions of Taxes, Transaction Costs and Risk.....................................83


3.2.3. Market Microstructure Theories ........................................................................87


3.3. OMAN STOCK MARKET: INSTITUTIONAL ASPECTS ................................................91

3.3.1. Trading Rules and Practices...............................................................................91

3.3.2. Dividends ...........................................................................................................92

3.3.3. Data ....................................................................................................................92

3.4. EMPIRICAL RESULTS ................................................................................................94

3.4.1. Price Behaviour on Ex-Dividend Day................................................................94

3.4.2. Abnormal Returns on Ex-Dividend Day............................................................95

3.4.3. Transaction Costs and Risk................................................................................98

3.4.4. Behaviour of Trading Volume around Ex-Days ..............................................101

3.4.5. Midpoint Pricing Using RASP Data ................................................................103

3.4.6. Volume Analysis Using RASP Data................................................................109

3.5. CONCLUSION...........................................................................................................110

CHAPTER 4: THE INFORMATION CONTENT OF CASH DIVIDEND ANNOUNCEMENTS IN A

UNIQUE ENVIRONMENT.................................................................................................112

4.1. INTRODUCTION .......................................................................................................112

4.2. THEORETICAL AND EMPIRICAL STUDIES...............................................................116

4.2.1. Theoretical Studies...........................................................................................116

4.2.2. Empirical Literature .........................................................................................120

4.3. DATA .......................................................................................................................131

4.4. METHODOLOGY......................................................................................................134

4.5. EMPIRICAL RESULTS ..............................................................................................136

xii

4.5.1. Dividend Increase ............................................................................................136

4.5.2. Dividend Decrease ...........................................................................................138

4.5.3. No Change........................................................................................................140

4.5.4. Cumulative Abnormal Returns ........................................................................142

4.5.5. Regression Results on Changes in Dividends and Earnings............................143

4.5.6. Market Efficiency.............................................................................................145

4.6. BID-ASK BOUNCE ...................................................................................................146

4.7. CONCLUSION...........................................................................................................148

CHAPTER 5: DIVIDEND POLICY IN THE ABSENCE OF TAXES .......................................150

5.1. INTRODUCTION .......................................................................................................150

5.2. THEORETICAL AND EMPIRICAL STUDIES...............................................................154

5.2.1. Dividend Irrelevance Hypothesis.....................................................................155

5.2.1.1. Empirical Evidence ...................................................................................155

5.2.2. Bird-In-The-Hand Hypothesis .........................................................................157


5.2.3. Tax Effect Hypothesis......................................................................................159


5.2.4. Agency Costs and Free Cash Flow Hypothesis ...............................................161


5.3. FACTORS THAT INFLUENCE DIVIDEND POLICY.....................................................167

5.3.1. Profitability ......................................................................................................167

5.3.2. Firm Size ..........................................................................................................168

5.3.3. Leverage...........................................................................................................169

5.3.4. Agency Costs ...................................................................................................170

5.3.5. Business Risk ...................................................................................................171

5.3.6. Ownership Structure ........................................................................................172

5.3.7. Maturity Hypothesis.........................................................................................173

xiii

5.3.8. Tangibility ........................................................................................................174

5.3.9. Growth Opportunities ......................................................................................175

5.4. DATA .......................................................................................................................177

5.4.1. Estimation Model .............................................................................................179

5.4.2. Payment of Dividends ......................................................................................180

5.4.3. Descriptive Statistics........................................................................................183

5.5. DETERMINANTS OF DIVIDEND POLICY ..................................................................186

5.5.1. Non-Financial Firms ........................................................................................187

5.5.2. Financial Firms ................................................................................................191

5.6. DETERMINANTS OF THE DECISION TO PAY DIVIDENDS ........................................192

5.6.1. Non-Financial Firms ........................................................................................193

5.6.2. Financial Firms ................................................................................................194

5.7. THE LINTNER MODEL ............................................................................................196

5.7.1. Empirical Results for the Lintner Model .........................................................199

5.7.1.1. Non-Financial Firms .................................................................................200

5.7.1.2. Financial Firms .........................................................................................202

5.8. CONCLUSION...........................................................................................................203

CHAPTER 6: CONCLUSION.............................................................................................205

APPENDICES...................................................................................................................208

APPENDIX A ...................................................................................................................208

APPENDIX B ...................................................................................................................259

APPENDIX C ...................................................................................................................291

APPENDIX D ...................................................................................................................294

xiv

APPENDIX E ...................................................................................................................296

REFERENCES..................................................................................................................302

xv

LIST OF TABLES

TABLE 2.1. DESCRIPTIVE STATISTICS................................................................................21 TABLE 2.2. CORPORATE ACTIVITY, EQUITY GROWTH, AND CAPITAL STRUCTURE,

CLASSIFIED BY STOCK RETURNS (YEAR-ADJUSTED AND SALES ADJUSTED). ...........23 TABLE 2.3. FAMA-MACBETH REGRESSIONS PREDICTING ADRT+K WITH ADRT AND

IDRT,T+K. ................................................................................................................28 TABLE 2.4. ALTERNATIVE DEBT DEFINITIONS ..................................................................31 TABLE 2.5. CAN THE RESULTS BE EXPLAINED BY ADJUSTMENT COSTS? ..........................32 TABLE 2.6. EXPLANATORY POWER OF COMPONENTS OF DEBT RATIOS AND DEBT RATIO

DYNAMICS ................................................................................................................34 TABLE 2.7. F-M REGRESSIONS EXPLAINING DEBT RATIO CHANGES (ADRT+K, -ADRT)

ADDING VARIABLES USED IN PRIOR LITERATURE. ...................................................51 TABLE 2.8. F-M REGRESSIONS EXPLAINING BANK DEBT RATIO CHANGES (ADRT+K -

ADRT) ADDING VARIABLES USED IN PRIOR LITERATURE........................................59 TABLE 2.9. FLANNERY AND RANGAN MODEL EXPLAINING ACTUAL DEBT RATIO

(ADRI,T+1) ADDING VARIABLES USED IN PRIOR LITERATURE. ...............................65 TABLE 3.1. SAMPLE CHARACTERISTICS ............................................................................94 TABLE 3.2. PREMIUM SUMMARY STATISTICS....................................................................95 TABLE 3.3. EX-DAY ABNORMAL RETURNS SUMMARY STATISTICS ..................................97 TABLE 3.4. THE EFFECT OF DIVIDEND YIELD, TRANSACTION COSTS, AND RISK ON EX-

DAY ABNORMAL RETURNS .....................................................................................100 TABLE 3.5. DAILY ABNORMAL TRADING VOLUME .........................................................102 TABLE 3.6. PREMIUM AND EX-DAY ABNORMAL RETURN (AR) USING RASP CLOSING

TRANSACTION PRICES. ............................................................................................104 TABLE 3.7. PREMIUM AND EX-DAY ABNORMAL RETURN (AR) USING RASP CLOSING

QUOTE MIDPOINTS..................................................................................................105

xvi

TABLE 3.8. PREMIUM AND EX-DAY ABNORMAL RETURN (AR) USING RASP OPENING QUOTE MIDPOINTS..................................................................................................106

TABLE 3.9. PREMIUM AND EX-DAY ABNORMAL RETURN (AR) USING RASP CLOSING BID

AND ASK QUOTES ...................................................................................................107 TABLE 3.10. PREMIUM AND EX-DAY ABNORMAL RETURN (AR) USING RASP OPENING

BID AND ASK QUOTES ............................................................................................108 TABLE 3.11. DAILY ABNORMAL TRADING VOLUME USING RASP DATA.......................109 TABLE 4.1. FREQUENCY OF FIRM-YEAR OBSERVATIONS ................................................132 TABLE 4.2. CASH DIVIDEND DISTRIBUTIONS ..................................................................133 TABLE 4.3. DESCRIPTIVE STATISTICS..............................................................................134 TABLE 4.4. THE STOCK MARKET REACTION TO DIVIDEND INCREASE IN THE MUSCAT

SECURITIES MARKET. .............................................................................................137 TABLE 4.5. THE STOCK MARKET REACTION TO DIVIDEND DECREASE IN THE MUSCAT

SECURITIES MARKET. .............................................................................................139 TABLE 4.6. THE STOCK MARKET REACTION TO NO CHANGE IN DIVIDENDS IN THE

MUSCAT SECURITIES MARKET................................................................................140 TABLE 4.7. CUMULATIVE ABNORMAL RETURNS FOR DIVIDEND INCREASE, DIVIDEND

DECREASE, AND NO CHANGE IN DIVIDENDS...........................................................143 TABLE 4.8. REGRESSION RESULTS OF ABNORMAL RETURNS ON DIVIDEND CHANGES AND

EARNINGS CHANGES RELATIVE TO STOCK PRICE. ..................................................144 TABLE 4.9. REGRESSION RESULTS OF ABNORMAL RETURNS ON DIVIDEND CHANGES AND

EARNINGS CHANGES. ..............................................................................................145 TABLE 4.10. MEAN ABNORMAL RETURN (AR) USING RASP QUOTE MIDPOINTS ..........147 TABLE 5.1. SUMMARY OF TESTABLE HYPOTHESIS AND PROXY VARIABLES ...................176 TABLE 5.2. DIVIDEND PAYOUT RATIO FOR ALL, FINANCIAL, AND NON-FINANCIAL FIRMS

OVER THE PERIOD 1989-2004. ................................................................................181 TABLE 5.3. DESCRIPTIVE STATISTICS FOR NON-FINANCIAL FIRMS.................................183 TABLE 5.4. DESCRIPTIVE STATISTICS FOR FINANCIAL FIRMS..........................................184

xvii

TABLE 5.5. NUMBER AND FRACTION OF NON-FINANCIAL FIRMS PAYING DIVIDENDS ....185 TABLE 5.6. NUMBER AND FRACTION OF FINANCIAL FIRMS PAYING DIVIDENDS.............186 TABLE 5.7. TOBIT REGRESSION FOR THE DETERMINANTS OF DIVIDEND POLICY OF NON-

FINANCIAL FIRMS. ..................................................................................................188 TABLE 5.8. TOBIT REGRESSION FOR THE DETERMINANTS OF DIVIDEND POLICY OF

FINANCIAL FIRMS. ..................................................................................................192 TABLE 5.9. PROBIT REGRESSIONS TO EXPLAIN WHICH NON-FINANCIAL FIRMS PAY

DIVIDENDS..............................................................................................................194 TABLE 5.10. PROBIT REGRESSIONS TO EXPLAIN WHICH FINANCIAL FIRMS PAY DIVIDENDS

................................................................................................................................195 TABLE 5.11. LINTNER MODEL ESTIMATES FOR NON-FINANCIAL FIRMS .........................201 TABLE 5.12. LINTNER MODEL ESTIMATES FOR FINANCIAL FIRMS..................................203

1

Chapter 1: Introduction

Capital structure and dividend policy remain among the most controversial issues in

corporate finance. This controversy is related to the complexity of the tax codes, price

discreteness, and disperse ownership in western countries where most studies are

undertaken. In this thesis, we use a unique data set from Oman where the above factors

are either absent or limited.

First, there are no taxes on dividends and capital gains in Oman. The country’s

main tax is corporate income tax where Omani companies are taxed at a flat rate of 12%.

This makes Oman taxing system one of the simplest in the world. Second, Omani firms

distribute almost 100% of their profits in dividends. In addition, dividends are

distributed annually. These factors have important implications on the ex-dividend day

behaviour.

Third, Omani firms are highly levered through bank loans. In addition, the

majority of Omani firms are owned by a small number of investors who have controlling

interests. This concentrated ownership can reach up to 80% in some firms for a single

group of investors. These two factors should have a positive impact on the agency

problem between shareholders and management. They also suggest a diminished role

for dividends as a signaling mechanism in Oman.

Fourth, transparency in Oman is low and corporate disclosure requirements are

loose (Islam (2002)). There is a scarcity of professional financial analysts and there are

no management forecasts are provided. Investors have few other sources of information

on Omani companies which makes cash dividend announcements an important piece of

2

information that can assist investors in pricing Omani shares. It is important to examine

whether this is indeed true.

Fifth, as part of its efforts to attract investment and activate the private sector,

Oman offers several financial incentives and support for investors. The country is

subsidizing certain companies by giving them soft loans that are interest free. These

loans are given for acquiring fixed assets for new projects, buying machinery and

equipment required for expansion of existing projects, and infusion of finance into a

“sick” industry. The eligibility of the company to get this subsidy increases its

willingness to borrow. We test whether this is indeed the case.

We use this unique data set to examine four distinct and specific aspects of

capital structure and dividend policy. In doing so, we present four independent chapters

which concern capital structure and dividend policy. The first topic examined in this

dissertation relates to capital structure while the other three topics investigate issues

related to dividend policy.

The first issue investigated in this thesis in Chapter 2, concerns the determinants

of capital structure dynamics. Previous studies examining this issue use data from

western countries which are characterized by the complexity of the tax code which

makes it hard to evaluate the importance of taxes on firm’s capital structure (Myers

(1984) and Graham (2000)). The simplicity of the Oman tax system may help us to

provide clearer results on the impact of taxes on capital structure. Moreover, while there

is a wide agreement that stock returns are an important determinant of capital structure,

there is an intensive debate on whether this effect is persistent. These findings are

mainly derived using data from the US. We provide independent evidence from Oman.

3

We also investigate whether firms try to counteract the mechanistic effect of stock

returns, and if so, how quickly managers offset the impact of stock return surprises.

This is an important issue since the current literature provides mixed results with some

studies finding evidence supporting and others failing to do so. In addition, the vast

majority of theoretical models on the choice of debt structure assume that bank debt and

non-bank debt are equivalent, and as a result most empirical studies either exclude bank

debt or combine it with non-bank debt (Hooks and Opler (1993)). In this study, a

distinction is made between bank debt and non-bank debt in an effort to enhance our

understanding about the characteristics of firms that use them. This distinction is

important since bank debt may exhibit different characteristics to those of non-bank

debt.

We find stock returns are a first order determinant of capital structure. Firms do

show some tendency to rebalance towards their target capital structure. However, the

impact of stock returns dominates the effects of rebalancing. We also find new evidence

that firms do take countermeasures to offset changes in their leverage that stem from

equity value variations, but do so at a low speed. Adding previously popular

determinates of capital structure has only modest economic impact on capital structure

dynamics. When used with bank debt, stock returns continue to dominate other

determinants of capital structure. The results are robust to several alternative estimation

techniques.

The second issue examined in Chapter 3 relates to the ex-dividend day

behaviour. Previous research documents that stock prices drop by significantly less than

the dividend on the ex-day. Several interpretations are advanced in the literature to

4

explain the ex-dividend day behaviour including taxes, price discreteness, and

transaction costs. In this chapter, we use a unique data set from Oman where the above

factors are either absent or limited. These data offer significant advantages over data

used by previous studies. First, the absence of taxation of dividends and capital gains in

Oman provides an ideal opportunity to examine the ex-dividend behaviour without any

ambiguity regarding effective marginal tax rates on dividends and capital gains. Second,

the fact that stock prices are decimalized in Oman implies that the confounding effects

of stock price discreteness on ex-day behaviour are much smaller compared to other

market where prices are not decimalized (until recently the minimum tick size was one-

eighth of a dollar in the US). In addition, dividends are usually paid once a year in

Oman, whereas in many other countries (e.g., US, UK, Australia) dividends are paid

quarterly or semi-annually. These factors increase the size of the dividends relative to

the minimum tick size for the stock compared to other countries, and this reduces the

importance of the tick size as a driver of the ex-day behaviour. Third, transaction costs

become more important when dividends are relatively small, and act like a barrier

against short-term trading. However, since dividends are usually distributed annually

rather than quarterly, this would suggest that transaction cost models may not be

important in Oman. Fourth, in addition to the daily stock prices, the data set contains

intra-daily data which allow us to directly test the Frank and Jagannathan (1998) market

microstructure model. Because of these data advantages, we can examine the ex-

dividend day behaviour in a less noisy and a more powerful manner than previous

studies.

5

Like previous studies, we find that the stock price drops by less than the amount

of dividends and there is a significant positive ex-day return. By examining abnormal

volumes around the ex-dividend day, we find no evidence of short-term trading. We are

however able to account for our results using market microstructure models.

The third topic analyzed in Chapter 4 is the stock price reaction to dividend

announcements. Tax-based signaling models argue that dividends would not have

information and be informative if it is not for the higher taxes on dividends relative to

capital gains that they apply to shareholders (Amihud and Murgia (1997)). The absence

of personal taxes presents us a golden opportunity to examine this prediction. If we find

that the stock price reacts to cash dividend announcements, then this would suggest that

the higher taxation on dividends relative to capital gains is not a necessary condition for

them to have information and be informative. It would also suggest that there are other

factors, beyond higher taxation, that make dividends informative. Moreover, Omani

companies rely heavily on bank financing. If bank monitoring is effective, then

dividend payments may not be necessary to reduce managers’ tendency to overinvest

free cash flow. This should reduce the announcement effects of dividend on stock

prices. In addition, the concentration of ownership structure in Oman should reduce the

agency cost between managers and shareholders. If the concentration of ownership

leads to less information asymmetry between managers and shareholders, dividend

announcements should have a smaller pricing effects compared to countries where

companies are owned by a diverse group of investors. Both of these arguments, together

with the absence of taxes on dividends and capital gains, suggest that dividends do not

act as a signal of information or as a disciplinary mechanism, or at least suggest a

6

diminished role for dividends in Oman. On the other hand, the low corporate

transparency in Oman suggests a positive effect of dividends. It is an empirical issue as

to how the Omani market balances the negative pricing effect of non-taxability of

dividends, bank leverage, and ownership concentration and the positive pricing effect of

low transparency on dividends.

Our results show that the announcements of dividend increases (decreases) are

associated with a stock price increase (decrease). Firms that do not change their

dividends experience insignificant negative returns. These results contradict the tax-

based signaling models which argue that higher taxes on dividends relative to capital

gains are a necessary condition for dividends to have information and be informative.

The final topic examined in Chapter 5 is the determinants and stability of

dividend policy for financial and non-financial firms. Investigating this issue is

important because Omani firms have high dividend payout ratios which led the CMA to

issue a circular (number 12/2003) arguing that firms should retain some of their earnings

for “rainy days”. This allows us understand the characteristics of firms that pay

dividends. In addition, dividend policy remains a puzzle. A major part of the puzzle

stems from the fact that firms continue to pay dividends despite the tax disadvantage.

While this is true in the U.S. and other western countries, Oman poses a unique case.

The absence of taxes means that a major source of the puzzle is eliminated. Moreover,

the determinants of dividend policy are controversial and there is no unanimity among

researchers on the factors that affect dividend policy. This controversy motivates this

research to provide new evidence on the factors that affect dividend policy. Unlike most

previous studies, we include both dividend paying and non-dividend paying firms. This

7

is important since the exclusion of the non-dividend paying firms from the analysis may

create a selection bias (Kim and Maddala (1992) and Deshmukh (2003)).

We find that there are some common factors that determine dividend policy of

both financial and non-financial firms and there are some factors that affect only non-

financial firms. In particular, the common factors are profitability, size, and business

risk. Government ownership, leverage, and age have a significant impact on the

dividend policy of non-financial firms but no effect on financial firms. Our results also

show that agency costs are not a critical driver of dividend policy of Omani firms which

is not surprising given that Omani firms have high debt ratios. We also find that the

factors that influence the probability to pay dividends are the same factors that drive the

amount of dividends paid for both financial and non-financial firms. We document that

non-financial firms adopt a policy of smoothing dividends while financial firms do not

have a stable dividend policy.

In Appendix A we provide a general overview of the Oman economy and its

financial sector. In particular, we discuss the performance and the unique characteristics

of Oman and describe the major features of the Muscat Securities Market (MSM).1 The

Appendix also provides a brief description of the financial sector with an emphasis on

those aspects of the MSM and debt market that are of particular interest and relevance to

the current study on capital structure and dividend policy.

1 The MSM is the only securities market in Oman where shares are traded.

8

Chapter 2: What are the Determinants of Capital Structure? Evidence

from a Country with Unique Financing Arrangements

2.1. Introduction

Capital structure decisions are enigmatic.2 Economists have neither a persuasive

theory nor a clear understanding of what factors affect capital structure decisions. This

led Myers (1984) to call it the “capital structure puzzle”. In the same paper, Myers

(1984, p. 575) asked “How do firms choose their capital structures?...the answer is, “We

don’t know”…we know very little about capital structure. We do not know how firms

choose the debt, equity or hybrid securities they issue…In general, we have inadequate

understanding of corporate financing behavior, and of how that behavior affects security

returns”.

In an influential paper, Welch (2004) provides some answers to Myers questions.

For instance, Welch (2004) provides evidence that firms are basically inert and their

capital structure changes are mainly driven by their stock returns. Moreover, he

documents that US firms do not issue debt or equity to counter the effect of stock returns

on their capital structure. Welch also shows that after controlling for stock return

effects, many previously used proxies play a minor role in explaining capital structure

dynamics. But how general is the inertia theory? Are the Welch results general or

unique to a US-style institutional setting?

2 See Appendix B for a detailed review of the capital structure literature.

9

There are some institutional factors that differentiate the US from Oman. For

example, Welch argues that long-term debt issuing activity is the most capital structure

relevant for the US, however, as we will demonstrate later, Oman depends mostly on

short-term financing where banks play a pivotal role in financing firms listed on the

Muscat Securities Market. The question of whether the institutional setting affects the

results can be tested empirically by conducting similar studies in emerging countries. So

it is yet to be seen whether the Welch findings hold in environments that are different

from the US. In fact, Rajan and Zingales (1995, p. 1421) stress that “without testing the

robustness of this finding outside the environment in which they were uncovered, it is

hard to determine whether these empirical regularities are merely spurious correlations,

let alone whether they support one theory or another.”

Oman is of interest for many reasons. First, as we will show later, Oman has

unique financing arrangements that are characterized by high leverage and high reliance

on bank debt. The fact that Omani firms depends on banks to finance their activities

adds further importance to the study. The literature has often described banks as being

particularly good at investigating informationally-opaque firms and deciding which are

viable borrowers. Banks have an advantage at collecting information but are potentially

more expensive sources of capital than the public debt markets. The costs of monitoring

and imperfect financial contracting should raise the costs of debt for firms borrowing

from banks, and hence lower their debt ratios (Faulkender and Petersen (2006)). The

fact that Omani firms are highly levered seems surprising given the high costs of

obtaining debt in Oman.

10

Second, due to the simplicity of the tax system, Oman is an important case to test

financial theories. In Oman there are neither personal taxes nor taxes on dividends and

capital gains. This is different from western countries, where most studies are

undertaken, which are characterized by the complexity of the tax code, making it hard to

evaluate the importance of debt. Indeed, the dynamic nature of the treatment of tax

shields in the American tax system makes it difficult to evaluate the quantitative

importance of debt. In fact, Myers (1984, p. 588) concludes after reviewing the

available empirical work that there was “no study clearly demonstrating that a firm’s tax

status has a predictable, material effect on its debt policy. I think the wait for such a

study will be protracted.” One of the reasons for this conclusion by Myers is the

complexity of the tax system in most western countries which makes such study a

difficult task. Actually, Graham (2000, p. 1901) notes that “Researchers face several

problems when they investigate how tax incentives affect corporate financial policy and

firm value. Chief among these problems is the difficulty of calculating corporate tax

rates due to data problems and the complexity of the tax code. Other challenges include

quantifying the effects of interest taxation at the personal level”. Thus, this may

contribute to the capital structure puzzle. Indeed, one of the problems that led to Myers’

capital structure puzzle is related to properly quantifying corporate tax rates and

incentives. While complexity is true for the US, it is clearly not true for some other

countries including Oman where firms are taxed at flat rate of 12%. Thus, Oman offers

a unique environment that enables us to avoid the complexity of tax rates. As a result, it

may help get clearer result on the impact of taxes on firm financing decisions. This is

one of the objectives of this study. A finding of a positive association between leverage

11

and taxes would help in resolving the capital structure puzzle. In fact, Graham,

Lemmon, and Schallheim (1998, p. 153) state “finding a positive relation between debt

levels and taxes helps resolve “the capital structure puzzle”.

Apart from the contribution to the sparse literature on capital structure in

emerging markets, this study extends the capital structure literature along a number of

dimensions. Firstly, we provide evidence about the broad patterns of financing activity

in Oman. This provides the empirical context for the more formal tests on the factors

that affect capital structure dynamics. Secondly, while there is a wide agreement that

stock returns are an important determinant of capital structure, there is an intensive

debate on whether this effect is persistent. These findings are mainly derived using data

from the US. We provide independent evidence from Oman. Thirdly, in comparison to

previous work on this topic, we examine a boarder set of explanatory variables and

introduce some factors that are unique to Oman. Much of the analysis is devoted to

determining which variables are economically important in predicting leverage, with a

central focus on stock returns. In particular, this study is designed to explain the

variation in debt ratios across all publicly traded Omani firms and, hence, to identify

empirically the determinants of capital structure dynamics. The primary objective of the

study is to examine whether stock returns are important factors in firms capital structure

choices. The relationship between debt ratios and stock returns will be investigated with

various determinants commonly found in previous studies, such as firm size, type of

asset, growth opportunities, profitability, uniqueness, etc. Moreover, since the theories

have different empirical implications in regard to different types of debt instruments, the

study uses separate measures of short-term, long-term and an aggregate measure of

12

leverage to check the robustness of our model. Fourthly, the simplicity of the tax code

in Oman provides us with a unique opportunity to avoid the complexities faced by

previous studies. These may enable us to get clearer results on the impact of taxes on

capital structure.

Fifthly, we investigate whether firms try to counteract the mechanistic effect of

stock returns, and if so, how quickly managers offset the impact of stock return

surprises. This is an important issue since the current literature provides mixed results

with some studies finding evidence supporting and others failing to do so. Sixthly, the

vast majority of theoretical models on the choice of debt structure assume that bank debt

and non-bank debt are equivalent, and as a result most empirical studies either exclude

bank debt or combine it with non-bank debt (Hooks and Opler (1993)). In this study, a

distinction is made between bank debt and non-bank debt in an effort to enhance our

understanding about the characteristics of firms that use them. This distinction is

important since it is possible that bank debt may exhibit different characteristics than

non-bank debt.

Finally, the results of the study can be effectively used by both the management

of firms and the government. It should also narrow the gap between empirical research

in developed and developing countries and hence identify whether the determinants are

critically different for these two classes of markets. In addition, this study will not only

improve the understanding of the Omani capital structure, but it also tests for the

robustness of the evidence brought forward by studies on other countries.

Our results show that Omani firms have high leverage ratios and the main source

of debt is short-term bank financing. The limited bond market leaves room for banks to

13

play an important role in financing Omani firms. Banks mainly provide short-term loans

which explain the high reliance of Omani firms on this form of financing.

We find robust evidence that stock price changes have a strong and primary

effect on observed market-based debt ratios. Firm’s capital structure seems to move

practically in line with that mechanistically induced by their stock returns. We also find

that firms show some tendency to nudge back to their old debt ratios. However, the

impact of stock returns dominates the effects of readjustment.

Adding previously popular determinates of capital structure has only modest

economic impact on capital structure dynamics. In essence, when we include other

featured variables into our model, stock returns subsume other factors. Nevertheless,

there are non-stock return variables that have both statistical and economic significance.

For example, taxes show some incremental explanatory power over five years.

However, tax’s impact is far less than that of stock returns. When used with bank debt,

stock returns continue to subsume other determinants of capital structure.

Nonetheless, it is important to note that there are some differences between the

findings of this study and Welch. First, the impact of stock returns is much less than that

reported by Welch for the US. Similarly, firm’s tendencies to rebalance towards their

target capital structure are much higher for Oman compared to the US. Second, in

contrast to Welch, short-term debt issuing activity is the most capital structure relevant

corporate activity, explaining 19.9% of the variation in leverage changes. Third, we find

new evidence that firms show some tendency to counteract the effect of stock return

surprises. However, the speed of adjustment to offset the mechanistic effects of stock

14

returns is slow. This view differs from Welch who claims that firms do nothing to

counteract the impact of stock returns for the US.

A recent study by Leary and Roberts (2005a) argues that the persistent effects of

shocks on leverage documented in previous studies are due to adjustment costs. We

examine these results and we find evidence that adjustment costs are unlikely to be the

main reason behind our results. In a similar vein, Flannery and Rangan (2006) claim

that the Fama and MacBeth (F-M) regression used in Welch fail to recognize the panel

aspect of the data. They argue that partial adjustment with fixed effects is a more

appropriate estimator. We employ Flannery and Rangan partial adjustment model and

we estimate it using F-M, fixed effects, and the System (extended) General Method of

Moments (GMM). We find that our results are robust to these methods. In general, our

results that stock returns are a primary determinant of capital structure is consistent with

the recent work by Cai and Zhang (2005), Chen and Zhao (2005a), and Kayhan and

Titman (2006). The slow adjustment we find is in line with the evidence reported by

Jalilvand and Harris (1984), Fama and French (2002), Baker and Wurgler (2002),

Kayhan and Titman (2006), Huang and Ritter (2005), and Titman and Tsyplakov (2005).

The remainder of the chapter proceeds as follows. Section 2.2 describes the data

and presents the measures that we construct to estimate the impact of stock returns on

capital structure dynamics. Section 2.3 develops the regression specification, and

examines whether the form of debt matters and presents the estimation results. Section

2.4 briefly discusses other potential determinants of capital structure used in the study.

Section 2.5 presents the results for the determinants of change in leverage followed by

an investigation of the extent to which these effects hold with bank debt in Section 2.6.

15

In Section 2.7 we provide comparison with the current literature. Section 2.8 concludes

the chapter.

2.2. Data and Methodology

2.2.1. Data

The data for this study are taken from “Share-Holding Guide of MSM Listed

Companies” published by the MSM. The MSM collects annual financial statements and

stock price data of all firms listed on MSM and it has a website to provide information

and financial data related to the performance of MSM and all listed companies. Every

year it publishes a book called “Share-Holding Guide of MSM Listed Companies”

which comprises accounting information from financial statements as well as stock

return data and data on ownership structure. We complement the data from the MSM

Guide with MSM index which we obtain from the MSM.

As the data were available in hard copy only, the first task was to input the data

into a computer database. The data set comprise all publicly traded firms listed at the

MSM. In the sample, firms come from all four sectors that comprise the MSM namely,

financial and banking sector, service sector, industry sector, and insurance sector. These

sectors contain firms from hotels, poultry, leasing, fisheries, oil, agriculture, energy,

power, aviation, banks, investment firms, and manufacturing firms. The data are time

series cross-sectional variables which are collected over the entire life of the MSM from

1989 to 2003.

To check for the accuracy of the data, we compare the figures from the MSM

Guide with the data from the firm’s financial statements available on the internet, where

16

possible. Any observations with missing data for the book value of debt, and/or market

value of equity are deleted because these variables are required to calculate our

dependent and independent variables. Because our regression specification includes

lagged variables, we also exclude any firm with fewer than two consecutive years of

data. The number of firms included in the study changes from one year to another, with

a range from 60 to 142. These resulted in a data set of an unbalanced panel containing

1,263 firm-year observations.

2.2.2. Measures of Leverage

The definition of leverage is important since an ill-defined measure of debt may

not only lead to spurious relationships, but more importantly the researcher will be

unable to capture the full response of the firms (Plesko (2001)). Several definitions of

leverage have been used in the literature where most studies consider some form of a

debt ratio. The difference between these studies is whether book value measures or

market value measures are employed. Most of the current academic literature focuses

on market debt ratios (e.g., Hovakimian, Opler, and Titman (2001), Frank and Goyal

(2004), Welch (2004), Leary and Roberts (2005a), Hovakimian (2006), and Flannery

and Rangan (2006)), whereas the older academic literature tends to focus on book value

(e.g., Rajan and Zingales (1995), and Booth, Aivazian, Demirguc-Kunt, and

Maksimovic (2001)). However, most of the finance literature supports the concept that

market value is a more accurate measure because it presents the present value of the

firm’s equity as a going concern, as reflected in the stock market of the publicly traded

firms, that is, it reflects the present value of the firm’s expected future cash flows. In

17

fact, Welch and Hoberg (2002) provide evidence that book value of equity is a

problematic measure of value.3 They suggest that it is a plug number used to balance the

left-hand side and the right-hand side of the balance sheet and it has little economic

significance. Moreover, it has low correlation with the market value of equity. As a

result, they argue that market value of equity is much a better measure of value.

Consequently, this study employs market value of equity to calculate debt ratios.

2.2.3. Empirical Model

The primary objective of the chapter is to examine the determinants of capital

structure decisions with a focus on stock returns. The main research question of this

study is whether variation in market leverage ratio is caused primarily by stock returns

or deliberate managerial choices to adjust to their past target debt ratios. The basic

empirical model is a time series cross sectional regression of firm’s debt ratios against

the lagged market leverage ratio and the stock return induced changes in market value of

equity. This estimating equation extends the model used by Welch (2004) to Oman. As

with previous studies, the dependent variable in our regressions is market leverage ratio

or as Welch calls it the Actual Debt Ratio (ADRt). We define accounting measures in

accordance with Welch (2004). Specifically, ADR is defined as the ratio of book value

of debt (D) to the sum of book value of debt and the market value of equity (E),

tt

tt ED

DADR

+= (2.1)

3 For more detail, see Welch and Hoberg (2002).

18

Where Dt is the sum of both current liabilities and long-term liabilities at time t and Et is

the market value of equity (computed as the number of outstanding shares multiplied by

the market price) at time t. As in Welch (2004), our explanatory variables are the lagged

ADR and the IDRt,t+k. IDRt,t+k is the implied debt ratio that results if the firm does

nothing, i.e., neither issues nor retires debt or equity. It is constructed to measure the

extent to which market leverage ratios are expected to change in response to stock

returns. Specifically, IDR measure the degree to which the market leverage ratio

changes mechanically because of stock return induced changes in the market value of

equity. By design, IDR moves mechanistically with stock returns, and not with

managerial capital structure decisions. Consistent with Welch (2004) notation, the IDR

is:

tkttt

tktt DxE

DIDR

++=

++ )1.( ,

, (2.2)

Where Dt and Et is as defined above, xt,t+k is the stock return experienced by the firm’s

equity from t to t+k net of dividend, t∈ is a random error, and k is the horizon measured

in years.

Hence, the basic regression equation is:

tktttkt IDRADRADR ∈+⋅+⋅+= ++ ,210 ααα (2.3)

As a robustness checks, we also perform the analysis on short-tem debt, long-

term debt, and bank debt. As in Welch (2004), the hypothesis of this study is the

following:

Perfect readjustment hypothesis: 0,1 21 == αα (2.4)

Perfect non-readjustment hypothesis: 1,0 21 == αα

19

Under the hypothesis of optimizing behaviour, the readjustment hypothesis

should reflect a target that managers wish to achieve and hence wish to readjust to. On

the other hand, the inertia (non-readjustment) hypothesis implies that any change in

leverage between t and t+k is due to changes in stock return over the period, as opposed

to adjustment to the past debt ratio. We estimate equation 2.3 twice, with and without an

intercept. When we include the intercept 0α , it is used to capture a constant target debt

ratio. If firms follow an optimizing behaviour in which higher firm value induce higher

debt ratios, then the coefficient on ADR should be 100%. On the other hand, if debt

ratios are driven mechanistically by stock returns, then the coefficient on IDR should be

100%.

Since our focus is on the dynamics of firms capital structure choice, we express

the capital structure adjustment in equation (2.3) as follows. Leverage changes with new

debt issues, debt retirements, coupon payments, and debt value changes. As a result,

corporate debt can be expressed as

ktttkt TDNIDD ++ ++ , (2.5)

Where TDNI stands for total debt net issuing activity. As in Welch (2004), we define

TDNI as the difference in total debt value between t+k and t. Similarly, corporate equity

changes with stock returns (net of dividends), and new equity issues net of equity

repurchases. Consequently, corporate equity can be expressed as:

kttktttkt ENIxEE +++ ++= ,, )1.( (2.6)

Where ENI reflects firm’s net equity issuing and stock repurchasing activity. ENI is

then defined as the difference in total equity value between t+k and t without return and

dividend effects. Under this definition, actual debt ratios can be expressed as:

20

kttktttkttt

kttt

ktkt

ktktt ENIxETDNID

TDNIDED

DADR

+++

+

++

++ ++++

+=

+=

,,,

,, )1.(

(2.7)

More detailed data definitions are in Appendix C.

2.2.4. Descriptive Statistics

Table 2.1 presents summary statistics of basic variables after performing

modifications to address outlier values. Specifically, we trim the upper and lower two

percentile of each variable’s distribution in the normalized series. Using these criteria,

we identify 1,212 firm-years observations for the one-year regression and 612 for the 5-

year regressions, covering corporate financing behaviour from 1989 to 2003. All

variables are measured in percentages, unless otherwise indicated.

On average, Omani companies have a total accounting assets of RO 40 million,

with around 47% of the assets being short-term. These assets are employed to earn RO

8.1 million in revenue. The mean market value of sample firms is about 1.33 times

accounting assets. However, the median market value is much smaller than the

accounting assets. Similarly, the median market value is considerably smaller than the

mean market value. The actual debt ratio is around 48%, financed mostly through bank

loans.4 The mean short-term actual debt ratio is higher than long-term actual debt ratio

during the period under investigation. The standard deviation for short-term actual debt

ratio exhibits a similar pattern.

The summary statistics of Table 2.1 show the importance of the dynamic

components of debt ratios. During the period of study, the average sample firm achieves

4 This is much higher than the 29.8% reported by Welch (2004) for the US.

21

Table 2.1. Descriptive Statistics The sample consists of all publicly listed firms at the MSM from 1989 to 2003. Firm years with missing data on book value of debt or market value of equity are excluded. There are 1,212 firm-year observations in the one-year panel and 612 firm-year observations in the five-year panel. Firms are normalized by firm value (book value of debt plus market value of equity) and then wisorized at the 2nd and 98th percentiles. Variables are expressed in percentages unless otherwise indicated.

Abbreviation Description Mean1-Year Median

Std. Dev. Mean

5-Year Median

Std. Dev.

ADRt Actual Debt Ratio 48.1 49.0 26.3 IDRt,t+k Implied Debt Ratio 47.0 48.0 26.8 42.2 39.7 24.8 ADRCL Actual Debt Ratio; Current Liabilities Only 29.5 24.6 21.7 ADRLTL Actual Debt Ratio: Long-term Liabilities Only 18.6 13.4 18.9 ADR BL Actual Debt Ratio: Bank Loan Only 36.5 20.9 43.0 CA Amount of Current Assets in (million RO) 19.20 2.32 144.10 LTA Amount of Long-term Assets in (million RO) 21.33 2.49 97.05 Et +Dt Market values in (million RO) 53.91 8.32 387.63 Rev Rrevenue in (million RO) 8.11 2.41 20.33 Normalized by Market Value and Wisorized TDNIt,t+k Net Debt Issuing 6.6 3.0 16.0 5.3 12.3 60.8 ENIt,t+k Net Equity Issuing w/o Dividends 6.3 0.0 15.2 -10.6 4.5 88.5 TDNIt,t+k +ENIt,t+k Debt and Equity Issuing 14.2 4.6 32.4 -9.7 27.5 140.8Divt,t+k = (rt,t+k – xt,t+k ).Et Dividends 0.9 0.0 1.7 2.2 0.8 4.0 ENIt,t+k –Divt,t+k Activist Equity Expansion 5.0 0.0 15.8 -13.0 3.3 90.4 TDNIt,t+k +ENIt,t+k –Divt,t+k Activist Total Expansion 12.7 3.5 33.1 -12.2 24.8 143.1rt,t+k . Et Total Return in Omani Rial 1.5 0.0 13.5 2.0 1.6 13.9 Xt,t+k..Et Induced Equity Growth 0.1 0.01 12.7 4.4 2.8 14.2

22

a total return of around 1.5% of which they pay out 0.9% in dividends. This is

significantly lower than the 8.8% return reported in Welch (2004) for US firms. A

difference also exists for the stock price induced capitalization change which is about

0.1% in Oman compared to 7.0% in the US. However, a different pattern exists for

issuing activity in Oman where Omani firms seem to issue more debt and equity than

firms in the US. On average, Omani firms issue approximately 6.6% (3.7% for the US)

in debt and 6.3% (2.4 for the US) in equity. This suggests that Omani firms are not

averse to issuing activity, which is contrary to the common perception that issuing

activity is scarce. In fact, firm issuing activity is quite frequent. As a result, issuing

activity may be large enough to counteract a good part of stock return influence on

capital structure choice.5

To examine whether stock returns can explain debt ratio dynamics, we follow

Welch’s classification approach. We first sort all firms by calendar year. Then we sort

them by sales decile (to control for size). Then we allocate firms into 10 bins on the

basis of their net stock return performance where we keep a roughly equal number of

firms in each decile. The header rows in Table 2.2 report the median net stock returns

for each decile. The first three rows report actual capital structure relevance of debt

ratio dynamics. The “ending ADR” rows suggest that there is a large spread of resulting

debt ratios across firms having recently experienced different rates of return. Over a one

year horizon, the worst stock performers end up with an actual debt ratio of 60.4%

whereas firms with the best stock performance end up with an actual debt ratio of 43%.

Over five years, firms that have underperformed the MSM by 19% end up with an 5 We show later that firms do try to offset the mechanistic effect of stock return surprises but do so at a low speed.

23

Table 2.2. Corporate Activity, Equity Growth, and Capital Structure, Classified by Stock Returns (Year-Adjusted and Sales Adjusted). All variables are medians and are expressed in percentages. Firms are sorted first by year, then by sales decile, and then allocated to deciles based on their stock return rank (within each group of 10 firms). In each panel, the 4th rows through the 9th rows are normalized by firm size. Other rows are not normalized. In panel A, there are between 100 and 120 observations per decile; in panel B, between 50 and 65.

Panel A: Sort by Calendar Year, Sales, One Year Net Stock Returns. Sort Criterion, Net Return (t, t+1) -63 -30 -16 -6 -1 0 7 21 45 198 Ending ADRt+1 60.4 50.2 48.1 49.7 49.7 55.4 45.0 50.4 42.1 43.0 Starting ADRt 48.5 43.5 42.9 48.2 49.0 53.2 42.9 50.6 44.8 57.1 Return Induced IDRt,t+1 67.2 50.2 46.0 49.5 48.8 52.4 41.7 47.3 38.4 38.6 Net Debt Issuing, TDNI t,t+1 -80.3 -0.4 2.1 0.0 -5.2 3.6 -1.2 0.5 6.2 3.4 Net Equity Issuing, ENI t,t+1 3.6 2.2 -1.9 -3.2 0.2 -0.2 23.3 -0.7 0.3 -17.6 Dividends, DIV t,t+1 1.0 1.4 3.9 1.3 1.1 1.8 3.6 2.8 4.1 2.3 Activist Equity Expansion (ENI-DIV) 2.6 0.9 -5.8 -4.5 -0.9 -2.0 -26.9 -3.5 -3.8 -19.9 Activist Expansion (TDNI+ENI-DIV) -77.7 0.5 -3.7 -4.5 -6.1 1.7 -28.1 -3.0 2.4 -16.5 Induced Equity Growth, X t,t+1 -80.1 -20.1 -9.8 -3.6 -0.3 0.1 4.9 8.7 17.7 44.9

Panel B: Sort by Calendar Year, Sales, 5-Year Net Stock Returns. Sort Criterion, Net Return (t, t+5) -19 -9 -3 0 5 10 15 23 36 75 Ending ADRt+5 58.7 53.4 46.9 51.3 48.6 45.6 45.7 46.7 50.9 46.1 Starting ADRt 35.6 32.5 36.2 43.9 41.3 46.7 42.9 45.8 57.6 58.4 Return Induced IDRt,t+5 39.9 34.1 36.8 43.8 40.4 44.9 40.2 42.3 52.0 48.2 Net Debt Issuing, TDNI t,t+5 -23.0 5.3 9.7 7.7 6.0 -1.2 11.6 -17.0 -42.4 -2.9 Net Equity Issuing, ENI t,t+5 -98.6 -70.7 -43.8 -18.4 -5.7 9.5 0.4 -71.2 -145.8 52.4 Dividends, DIV t,t+5 5.0 2.5 2.4 3.7 2.3 2.7 2.3 1.7 10.9 3.8 Activist Equity Expansion (ENI-DIV) -103.6 -73.2 -46.2 -22.1 -8.0 6.8 -1.9 -72.9 -156.7 48.6 Activist Expansion (TDNI+ENI-DIV) -126.6 -67.8 -36.5 -14.5 -2.0 5.6 9.8 -89.9 -199.1 45.8 Induced Equity Growth, X t,t+5 -32.6 -9.9 -3.4 0.4 2.7 4.5 6.6 14.9 24.5 39.6

24

actual debt ratio of 58.7%, while firms that have outperformed the MSM by 75% end up

with an actual debt ratio of 46.1%.

The “starting ADR” rows demonstrate that over one year the worst stock

performers have lower starting debt ratios than the best stock performers. A similar

pattern is exhibited over the 5-year horizon. This may suggests that there is a correlation

between debt ratios and stock performance.

The “implied IDR” rows show the impact of stock returns on starting debt ratios.

Over one year, firms that have underperformed the MSM end up with higher implied

debt ratio relative to firms that have outperformed the stock market. However, the

opposite pattern appears in the 5-year horizon. This means that over one year firms with

poor stock performance have high implied debt ratio which is then reversed in the 5-year

horizon. Data rows four to eight present corporate activity, while the ninth row reports

equity growth, all divided by firm size. The results indicate that the majority of firms

are quite active with respect to their capital structures, suggesting that financing activity

is quite frequent. Over one year, firms respond to poor stock performance with more

equity issuing activity and to good performance with more debt issuing activity.6 This is

the opposite of what Welch reports for the US. However, the relationship is not clear

over the five year horizon in terms of debt issuing. Over five years, firms seem to issue

less equity regardless of stock return performance. The seventh row shows a negative

relationship between stock performance and “activist equity expansion” over an annual

horizon. This relationship disappears over the five year horizon where equity expansion

contracts regardless of stock returns. 6 This may hint that firms in our sample do try to counteract the mechanical influence of stock returns. However, the relationship is not strong.

25

The eighth row investigates whether firms intentionally expand or contract in

response to stock return performance. Over both annual and five year horizons, firms

appear to contract regardless of stock return performance. However, this contraction is

larger for firms with good stock performance compared to firms with poor performance

over five year period. As an exception, the very best decile stock price performers do

engage in some active expansion, approximately, 45.8% of their firm value. This

suggests that firms do take countermeasures to offset the impact of stock return

surprises. The last row in Table 2.2 shows a positive association between induced

equity growth and stock performance over both annual and five year horizon. For

instance, firms with good stock performance have more stock return induced equity

growth compared to firms with poor stock performance.

In summary, most of the firms are quite active in their issuing activity. This

implies that firms make quite frequent approaches to the market to raise the necessary

financing. The above results show that firm’s stock returns produce some corporate

issuing activity. Stated differently, managers may use issuing activity to counteract the

mechanistic effect of stock returns. Stock return induced equity growth moves in

tandem with stock return performance.

2.3. Estimation Results

2.3.1. Regression Specification

Table 2.3 presents the empirical results computed using the basic regression

equation (2.3). To avoid overstating significance levels by pooling the data over time,

26

we employ Fama and MacBeth (F-M) (1973) regression.7 Under this methodology, we

first run cross sectional regressions each year of the sample to generate yearly

coefficient estimates. We then report the mean coefficient estimates across time and use

the time series standard deviation of the slopes in the year-by-year cross sectional

regressions to construct standard errors for the average slopes. The main advantage of

this approach is that it circumvents the problems caused by heteroscedasticity and

correlation of residuals across firms (Lipson and Mortal (2006)). Fama and French

(2002, p. 3) describe F-M as “a simple way to obtain robust standard errors that capture

whatever contributes to the precision of the average slopes”. Another advantage of this

approach is that it enables us to have a large number of data points. This increases the

precision of the slopes and reduces their year-by-year volatility (Fama and French

(1998)). However, as Fama and French (1998) note, this approach suffers from the

problem that the sample autocorrelation of the slopes is imprecise.8 They account for

the autocorrelation of the regression slopes by requiring a t-statistic of around 3 to infer

reliability.9 In this study, we follow closely their approach. We are also concerned that

the regressions may be suffering from extreme observations. We account for that by

winsorizing the observations at the 2nd and 98th percentile for some of the explanatory

variables as in Welch (2004) shown in Appendix C. It is worth mentioning that our first 7 There are many recent papers that use Fama and MacBeth regressions in investigating capital structure including Baker and Wurgler (2002), Welch (2004), Sibilkov (2005), Acharya, John, and Sundaram (2005), Cai and Zhang (2005), Jenter (2005), Rossi (2005), Chang, Hilary, Shih, and Tam (2006), Lipson and Mortal (2006), Kisgen (2006), and Faulkender and Petersen (2006). 8Flannery and Rangan (2006) argue that F-M does not address the potential correlation between the lagged dependent variable and the residuals which can bias the estimated coefficients. To address this concern, we estimate equation (2.3) using fixed effects, random effects, and the system GMM. We find similar results to the one reported in Table 2.3. For more information on this, see Appendix D. 9 We check for multicollinearity using the Variance Inflation Factor (VIF). We find that the VIFs are less than the standard cutoff value of ten, indicating that multicollinearity does no appear to be a significant problem (Belsley, Kuh, and Welsch (1980) and Neter, Wasserman, and Kunter (1985)). See Appendix D for details.

27

concern is the economic significance, not the statistical significance. Because most of

the power comes from the cross-section, we do not need to worry about unit roots.

Panel A of Table 2.3 reports the results without a constant, to not allow for a

constant target debt ratio. For the one year horizon, all panels show that the IDRt,t+k

lines up better with the predicted ADRt+k than does the lagged ADRt. This suggests that

a large fraction of the time variation in the level of leverage stems from movements in

the stock returns. Over one year, an average firm allows its debt ratio to drift by around

62% with stock returns. The average firm show some tendency to nudge back towards

its past debt ratio. Still, the influence of stock returns through IDR dominates the effects

of readjustments. Over all horizons, the coefficient on ADR is about half of the IDR

coefficient suggesting that the impact of stock returns is twice as much as the effects of

readjustments. Now turning to the diagnostic of the regression estimates, the adjusted

R2 is strong in all cases. However, it generally exhibits an inverse relation with the

model horizon. The adjusted R2 is 93% for the 1-year regression, while it is 88%,

85.5%, 82% and 84% for the two years, three years, four years, and five years,

respectively.

Nevertheless, if we compare our results with those of Welch we see that the

impact of stock returns in Oman is much less than that for the US. In a similar vein,

Omani firms are more inclined to return to their old debt ratios compared with firms in

the US.

28

Table 2.3. Fama-MacBeth Regressions Predicting ADRt+k with ADRt and IDRt,t+k. The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the results of annual cross-sectional regressions explaining firms’ debt ratios (debt dividend by debt plus market value of equity) with the implied debt ratio IDR (where the lagged market value of equity is grossed up by the raw stock return over the period k) and the firms own lagged debt ratio ADRt. The cross-sectional regression equation is: .][ ,210 ktktttkt IDRADRADR +++ ∈+⋅+⋅+= ααα A coefficient of 100% on ADRt indicates perfect readjustment. On the other hand, a coefficient of 100% on IDRt,t+k indicates perfect lack of readjustment. Fama and MacBeth report means (across years) of the regression intercepts and slopes. The adjusted R2’s are time-series averages of cross-sectional estimates. N is the number of firm year observations and T is the number of cross-sectional regressions.10 Panel A: Without Intercept Horizon k con. ADRt IDRt,t+k s.e.c s.e.ADR s.e.IDR Adjusted R2 (%) N T

1 Year F-M 26.3 62.4 3.91 3.90 93.0 1212 142 Year F-M 37.9 61.5 5.66 5.67 88.0 1049 133 Year F-M 34.7 62.4 6.74 6.69 85.5 896 124 Year F-M 40.9 50.7 7.73 7.70 82.0 750 115 Year F-M 28.5 69.3 4.98 4.86 84.0 612 10Panel B: With Intercept Horizon k ADRt IDRt,t+k s.e.ADR s.e.IDR Adjusted R2 (%) N T

1 Year F-M 9.2 15.0 68.3 0.84 3.86 3.76 71.7 1212 142 Year F-M 15.3 18.8 53.6 1.18 5.44 5.26 53.3 1049 133 Year F-M 18.9 19.1 46.4 1.40 6.30 6.13 44.7 896 124 Year F-M 24.0 16.4 41.2 1.61 7.02 6.78 35.3 750 115 Year F-M 21.1 13.4 48.3 1.77 4.70 4.66 37.5 612 10

Panel B of Table 2.3 presents the results of equation (2.3) including an intercept.

This panel demonstrates similar results to the results obtained in Panel A. The

coefficients on ADR suggest that firms have some tendency to revert to their old debt

ratios. However, the coefficients on IDR exert more influence on firms debt ratios than

ADR. Additionally, the intercepts are all relatively similar in magnitude and exhibit a

positive association with the model horizon. This implies that all firms show a marginal

increase in debt ratios over the sample period. It is worth mentioning that the ability of

10 Note that there is fairly small number of observations in the cross-sectional regressions.

29

the model to explain variations in market leverage ratio declines as the horizon

increases. The only exception occurs in year 5 where it is higher than the prior year.

In summary, all panels show that the IDRt,t+k lines up better with the predicted

ADRt+k than does the lagged ADRt. This suggests that a large fraction of the time

variation in the level of leverage stems from movements in the stock returns, as opposed

to active financial management. Stated differently, all panels demonstrate that firm debt

ratios appear to be driven more by stock returns than by a conscious return to their past

debt ratios. This does not mean that firms do not try to rebalance. In fact, firms in our

sample show some tendency to return to their old debt ratios. However, the impact of

stock returns dominates the effects of adjustments.

2.3.2. Changes in Capital Structure

While the focus of our study is to explain the levels of capital structure, it is

interesting to see if we can explain changes in market leverage ratios. The difference

between them is that level regressions derive their power from cross-section of capital

structure while change regressions derive their power from firm’s experiencing changes

in their capital structure.

As discussed in Welch (2004), equation (2.3) can be estimated in changes and/or

with a restriction that the coefficients on IDR and ADR sum up to one:

ttkttkt ADRIDRADR ∈+⋅−+⋅+= ++ )1( 1,10 ααα (2.8)

Rearranging the above equation gives us the estimated regression equation:

30

(ADRt+1 – ADRt) = 1.23% + 76.95%(IDRt,t+1 – ADRt)11 Adjusted R2 = 24.60% (2.9)

(ADRt+5 – ADRt) = 5.12% + 28.43%(IDRt,t+5 – ADRt) Adjusted R2 = 14.89%

Consistent with our previous results, the coefficients are highly statistically

significant. Over one year, stock-return induced equity changes have the primary impact

on the debt ratio. However, the coefficient estimate is smaller over the five years,

suggesting that stock-return induced equity changes have less impact on observed debt

ratio. Similarly, the ability of the model to explain variations in market leverage ratios

declines from 24.6% in the one year horizon to 14.89% in the five year horizon.

2.3.3. Does the Form of Debt Matter?

Having documented that a firm’s stock return significantly affects its debt ratio,

we next examine whether the form of debt matters. To answer this question, we

estimate equation (2.3) by using only short-term debt, long-term debt, and bank debt in

the calculation of the variables. We would be further comforted if our results show

lower a ADR coefficient and a higher IDR coefficient when we determine a debt ratio

solely based on short-term, long-term, and bank loans.

Indeed, Table 2.4 supports this conjecture. The coefficients on IDR are still

much higher than ADR coefficients. A comparison of the coefficient estimates reported

in Table 2.4 with those reported in Table 2.3 indicates that stock return influences

dominate the effects of rebalancing regardless of the form of debt. The coefficient

estimates of stock returns do not vary much across different definitions of debt.12

11 The t-statistic is 19.9123 for the one year and 10.3877 for the 5-years. 12 Professor Richard Heaney suggested to examine whether the form of debt matters using the 5 years data. We replicated Table 2.4 with the 5 years data and we find similar results to those reported for the

31

Table 2.4. Alternative Debt Definitions The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the results of annual cross-sectional regressions explaining firms’ debt ratios (debt dividend by debt plus market value of equity) with the implied debt ratio IDR (where the lagged market value of equity is grossed up by the raw stock return over the period k) and the firms own lagged debt ratio ADRt. The cross-sectional regression equation is: tktttkt IDRADRADR ∈+⋅+⋅+= ++ ,210 ααα . A coefficient of 100% on ADRt indicates perfect readjustment. On the other hand, a coefficient of 100% on IDRt,t+k indicates perfect lack of readjustment. Fama and MacBeth report means (across years) of the regression intercepts and slopes. The adjusted R2’s are time-series averages of cross-sectional estimates. T is the number of cross-sectional regressions. There are 1,212 firm-year observations.

Type of Debt con. ADRt IDRt,t+k s.e.c s.e.ADR s.e.IDR Adjusted R2 (%) T Short-term Only 7.2 15.8 67.7 0.7 4.2 4.1 69.0 14Long-term Only 5.9 12.6 68.6 0.6 5.1 5.0 67.3 14Bank Loan Only 7.2 15.5 57.1 0.7 5.5 5.3 54.8 14

2.3.4. Can Adjustment Costs Explain the Inertia Behaviour?

In the presence of adjustment costs, firms may find it suboptimal to respond

immediately to capital structure shocks (Leary and Roberts (2005a)). Leary and Roberts

describe three types of adjustment costs namely, fixed cost, proportional cost, and a

fixed cost plus a convex cost component. The proportional cost component is relative to

the market value of raised or retired debt whereas the fixed cost is independent of the

size of the transaction. Due to the fixed cost component, it is commonly argued that

larger firms face relatively lower adjustment costs compared to smaller firms (Huang

and Ritter (2005)). Accordingly, we would expect larger firms to adjust their capital

structure more frequently (Xu (2006)). We examine the above hypothesis by splitting

our sample into two subsamples depending on whether the firms are smaller or larger

than the median firm in the same year (A similar approach is used by Huang and Ritter

one year horizon. In particular, we find that the coefficients on IDR exert more influence on firms debt ratios than ADR, indicating that stock return influences dominate the effects of rebalancing regardless of the form of debt over a five year horizon.

32

(2005)). We then estimate equation (2.3) for both subsamples. We also consider

Altman Z-score as a proxy for adjustment costs just as in Leary and Roberts. Firms with

higher (lower) Altman Z-score should be subject to lower (higher) bankruptcy costs and

thus should face lower (higher) transaction costs. This implies that these firms should

adjust more (less) frequently.

Table 2.5. Can the Results be Explained by Adjustment Costs? The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the results of annual cross-sectional regressions explaining firms’ actual debt ratios (debt dividend by debt plus market value of equity) with the implied debt ratio IDR (where the lagged market value of equity is grossed up by the raw stock return over the period k) and the firms own lagged debt ratio ADRt. The cross-sectional regression equation is: tktttkt IDRADRADR ∈+⋅+⋅+= ++ ,210 ααα . A coefficient of 100% on ADRt indicates perfect readjustment. On the other hand, a coefficient of 100% on IDRt,t+k indicates perfect lack of readjustment. The sample is split up according to whether firm specific characteristics such as size and financial distress costs is lower or higher than the year-specific sample median. Size is defined as log of assets and Altman Z-score is defined as the reciprocal of assets divided by the sum of 3.3 times earnings before interest and taxes plus sales plus 1.4 times retained earnings plus 1.2 times working capital. Fama and MacBeth report means (across years) of the regression intercepts. The adjusted R2’s are time-series averages of cross-sectional estimates. N is the number of firm year observations and T is the number of cross-sectional regressions. Superscript asterisks indicate Fama and MacBeth type t-statistic above 3(*), 4(**), and 5(***).

Variable Small Size Large Size Low Z-score High Z-score ADRt 0.111 0.120* 0.135 0.124*

IDRt,t+1 0.759*** 0.730*** 0.714*** 0.744*** Adjusted R2 0.753 0.687 0.759 0.657

N 605 607 607 605 T 14 14 14 14

We present the results in Table 2.5.13 It is clear that larger firms with supposedly

lower adjustment costs are not more eager to adjust. Similarly, firms with higher 13 We perform a two-sample t-test of the difference in means between small and large firms and we find that the difference between them is insignificant with a t-statistic of 0.2865. Similarly the difference in means between firms with low Z-score and firms with high Z-score is insignificant with a t-statistic of 0.4280.

33

Altman Z-score should be subject to less adjustment costs and thus adjust more

frequently. This is not what we observe in column 4 and 5. Firms with higher Altman

Z-score show no more tendencies to readjust compared to firms with lower Z-score. The

results are robust when the sample is split on the mean. This evidence may suggest that

adjustments costs are unlikely to be the main reason behind our results.14 These results

are consistent with Huang and Ritter (2005) who find that firms with lower adjustment

costs do not adjust faster than firms with higher adjustment costs.15 Similarly, Xu

(2006) finds that large firms do not appear to adjust more quickly than small firms for

the US. This view differs from Leary and Roberts who argue that adjustment costs can

explain the persistence effects of shocks in leverage.

2.3.5. Variance Decomposition

Table 2.6 predicts ADRt,t+k with ADRt updated for corporate issuing activity

between t and t+k (keeping other dynamic components at a constant zero). The results

suggest that past debt ratios are an important explanatory variable of debt ratios

dynamics. In particular, 64.8% of a firm’s capital structure level can be explained by

last year’s capital structure. However, the history of firm’s capital structure is able to

explain only 21.3% in the 5-year horizon. More importantly, the results show that

14 Professor Richard Heaney suggested examining whether transaction costs can explain the inertia behaviour using the 5 years data. We replicated Table 2.5 with the 5 years data and we find qualitatively similar results to those reported for the one year. Specifically, we find that large firms adjust more slowly than small firms. Similarly, we find that firms with higher Z-score adjust less frequently compared to firms with lower Z-score. We perform a t-test for the difference in means between small and large firms and we find that the difference between them is insignificant with a t-statistic of 1.211. Similarly the difference in means between firms with low Z-score and firms with high Z-score is insignificant with a t-statistic of 0.8235. 15 Huang and Ritter (2005) report evidence that firms that are likely to face lower adjustment costs adjust more slowly compared to firms that are likely to face higher adjustment costs. For example, they show that large firms adjust more slowly than small firms.

34

corporate issuing activity is more important than stock-return induced changes in capital

structure. Over annual horizons, stock returns are able to explain 22.2% of the change in

debt ratios, whereas all net issuing activities together are able to explain around 64.9%

of changes in debt ratios. This suggests that CFOs are by no means inactive in the

capital market.

Table 2.6. Explanatory Power of Components of Debt Ratios and Debt Ratio Dynamics The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the time-series average adjusted R2 from cross-sectional Fama and MacBeth regressions. In Levels, future actual debt ratio (ADRt+k) is explained by the Regressor. In Differences, change in leverage (ADRt+k – ADRt) is explained by the Regressor minus ADRt. k =1-Year, Avg. Adjust. R2 k =5-Years, Avg. Adjust. R2

Levels Differences Levels Differences Past Debt Ratio, ADRt 64.8% 21.3% Implied Debt Ratio, IDRt, t+k 71.8% 22.2% 25.5% 17.2% Implied Debt Ratio, w/dividend 70.7% 20.1% 25.4% 6.4% All issuing and dividend activity 80.7% 62.8% 49.6% 44.7% All issuing activity 87.0% 64.9% 62.5% 48.0% Net Equity Issuing Activity 68.3% 13.3% 34.0% 23.9% Net Debt Issuing (NDI) Activity 80.2% 48.0% 49.6% 44.7% NDI Short-term Only 19.9% 29.5% NDI Long-term Only 18.6% 24.3% NDI Bank Loans Only 8.9% 21.0%

Over a five year horizon, stock returns are able to explain 17.2% of debt ratio

changes, while all net issuing activities are able to explain around 48%. Table 2.6 also

suggests that debt issuing activity are more capital structure relevant than equity issuing

activities. This evidence is consistent with the findings of Hovakimian (2006). Over

both one year and five year horizons, short-term debt issuing is more capital structure

relevant. However, over five years, equity issuing activities becomes as important as

35

long-term debt issuing activities, yet still less important than short-term debt issuing

activities.

2.4. Other Determinants of Capital Structure

Having examined the impact of stock returns on capital structure dynamics, we

now turn our attention to other variables suggested by the literature and examine

whether these variables have economic relevance after controlling for the effects stock

returns. If these variables appear to have no incremental power when IDR is controlled

for, then it would have correlated with capital structure only indirectly through its

correlation with stock returns.

The selections of our other explanatory variables are primarily guided by the

results from previous empirical studies in the context of some developed and developing

countries. Furthermore, this study introduces new variables that are drawn from the

Oman unique corporate finance environment. In this section, we list various firm-

specific attributes other than stock returns suggested by capital structure literature and

mention the proxies that are used to capture their impact on capital structure.

2.4.1. Tax

One of the most important aspects of the tradeoff theory is that debt interest is a

tax deductible expense. This theory predicts a positive association between leverage and

corporate tax rate. Firms with higher marginal tax rates prior to the deduction of interest

expenditure are expected to have higher interest tax shields and hence have more debt

36

(Faulkender and Petersen (2006)). However, Marsh (1982), Bradley, Jarrell, and Kim

(1984), Long and Maltiz (1985), Titman and Wessels (1988), and Fischer, Heinkel, and

Zechner (1989) fail to find any significant effect of corporate tax on financing decisions.

MacKie-Mason (1990) comments that the reason why many studies fail to find

significant tax effects on financing decision is because debt ratios are the cumulative

result of years of separate decisions and most tax shields have a minor effect on the

marginal tax rate for most firms. MacKie-Mason (1990) examines the incremental

financing decisions using discrete choice analysis and presents evidence that the

desirability of debt financing at the margin varies positively with the effective marginal

tax rate.

In Oman, corporate income is taxed and firms are allowed to deduct interest

expense from their taxable income. Thus, there is a tax incentive for corporate

borrowing. A tax paying firm that pays an extra Rial of interest receives a partially

offsetting interest tax shield in the form of lower taxes paid. Whereas in most western

countries the tax benefit of debt has been reduced by the tax advantage of equity, this is

not the case in Oman. This even lends further support to the importance of tax in Omani

firms’ capital structure. Hence, raising the necessary financing through debt instead of

equity increases the total after-tax Rial return and hence, should have positive impact on

firm value. Thus, we should observe corporations borrowing to exploit interest tax

shields. The fact that Omani firms are highly leveraged would suggest that the Omani

firms are adding value through this strategy.

37

There are many ways to estimate the tax factor including the statuary tax rate, the

effective tax rate, etc. To capture the tax effect, we follow Welch and use the ratio of

income tax to the sum of earnings and income tax.

2.4.2. Government Ownership

Government ownership is a potential explanatory variable in the firm’s capital

structure choice. For example, firms with high government ownership may have a lower

bankruptcy costs. This is because the government may bail them out in case of trouble.

Indeed, agency theory postulates that the optimal structure of leverage and ownership

may be used to minimize total agency costs. Hence, it is expected that there is a

correlation between government ownership structures and leverage. Although

government ownership structure is believed to have impact on capital structure, there

seems no clear predication about the relationship between government ownership

structure and leverage.

Since the Omani government is a major shareholder in many companies, we will

consider it as a potential determinant of capital structure. The government ownership

would give a confidence to lenders to extend loans to a company. The percentage of

government ownership is used to capture its impact on capital structure dynamics.

2.4.3. Soft Loans

Oman is a country which depends on oil revenue as a major source of income, so

taxes are not an important source of revenue. The country is subsidizing certain

companies by giving them soft loans that are interest free. The eligibility of the

38

company to get this subsidy increases its willingness to borrow. Consequently, a

positive association between the availability of the soft loan and debt ratios should be

expected. The significance of this variable is tested via a dummy variable, which takes a

value of one if the firm receives a subsidy and zero otherwise.

2.4.4. Signaling

Signaling is used as one of the determinants of capital structure. If a firm can

credibly signal its quality to outsiders, it can avoid an information premium and thus

may access the equity market. According to pecking order theory, retained earnings are

the first source of financing. The amount of dividends distributed reduces the amount of

retained earnings. Hence, higher dividends lower retained earnings and increase the

needs for debt financing. Furthermore, agency models also draw links between dividend

payments and leverage (Jensen, Solberg, and Zorn (1992)). In particular, agency models

predict dividend payments and debt issues as substitutes in mitigating agency problems.

This study introduces the ratio of dividend payment to net income to capture the

signaling attribute. We use dividend payout ratio since many studies have argued that

dividends are used as a costly signal of earnings (John and Williams (1985) and Miller

and Rock (1985)). A firm with a reputation of dividend payment faces less asymmetric

information in accessing the equity market. Furthermore, Martin and Scott (1975) find

that it is a useful discriminator in their analysis, in part because it could have some

explanatory power over leverage

39

2.4.5. Profitability

Profitability is an important explanatory variable that has an influence on capital

structure. However, there is no clear theoretical predictions on its direction with some

theories arguing for a negative relationship with the debt ratio while, others argue the

opposite. For example, in the context of pecking order theory, profitable firms are likely

to have sufficient finance to ensure they do not need to rely on external sources. This

explanation suggests a negative relationship between profitability and leverage. In sharp

contrast, in the agency theory framework of Jensen and Meckling (1976) and Jensen

(1986), leverage alleviates the agency problems by forcing managers to pay out the

firm’s free cash flow. Debt financing ensures that management is disciplined to make

efficient investment decisions and that they do not pursue individual objectives as this

would increase the probability of bankruptcy (Harris and Raviv (1990)). In situations of

information asymmetry, increases in leverage of profitable firms can signal quality

financial management. Hence, this theory predicts a positive association between

leverage and profitability. According to the tax-based models profitable firms should

borrow more, ceteris paribus, as they have greater needs to shield income from corporate

tax. However, the interest tax shield hypothesis may not work for those firms that have

other avenues, like depreciation, to shield their taxes (DeAngleo and Masulis (1980)).

As per the pecking order predictions, most empirical studies show that leverage

is negatively related to profitability. Friend and Hasbrouck (1988), Titman and Wessels

(1988), and Frank and Goyal (2004) obtain these findings in US firms. Kester (1986)

documents that leverage is negatively associated with profitability in both the US and

Japan. In an Australian time series study, Sharpe and Pooley (1991) also find a

40

significant long run relationship between profitability and leverage. Recent studies

using international data also confirm this finding (Rajan and Zingales (1995) and Wald

(1999) for developed countries, and Booth et al. (2001) for developing countries). Frank

and Goyal (2003) also present evidence in favour of pecking order theory but argue that

this theory is not the only explanation for the obtained results.

In contrast, Long and Maltiz (1985) report evidence that leverage is positively

associated with profitability, but the relationship is not statistically significant. Jensen et

al. (1992) find a positive relationship between leverage and profitability. Wald (1999)

even claims that “profitability has the largest single effect on debt/asset ratios”. We use

three different measures of profitability. Our first measure of profitability is operating

income scaled by total assets, the second is the ratio of earnings after tax to total assets,

and the third is the ratio of operating income to sales. Furthermore, Welch (2004)

suggests that firm’s capital structure dynamics may be affected by profitability changes.

We use his definition to capture profitability changes impact on capital structure

dynamics as described in Appendix C.

2.4.6. Tangibility

In an uncertain world with asymmetric information, the asset structure of a firm

has a direct impact on its capital structure since firms tangible assets are the most widely

accepted sources for bank borrowings and raising secured debt. According to the

tradeoff theory, tangible assets act as collateral and provide security to lenders in the

event of financial distress. In the same vein, Jensen and Meckling (1976) suggest that

the agency cost of debt exists as the firm may shift to riskier investment after the

41

issuance of debt, and transfer wealth from creditors to shareholders to exploit the option

nature of equity. If a firm’s tangible assets are high, then these assets can be used as

collateral, diminishing the lender’s risk. Thus, a positive relationship is expected

between leverage and tangibility. Williamson (1988) and Harris and Raviv (1990)

report evidence that leverage is positively associated with tangibility.

Other studies that report a positive relationship between tangibility and leverage

include Bradley et al. (1984), Rajan and Zingales (1995), Graham et al. (1998), Shyam-

Sunder and Myers (1999), Hovakimian et al. (2001), Frank and Goyal (2003), and

Korajczyk and Levy (2003). Some indirect evidence was reported by Marsh (1982) who

conducts a time series study and finds that larger firms with a large tangible asset base

tend to use more debt. Grossman and Hart (1982), however, show that a firm’s tangible

assets can be negatively correlated with leverage. According to them, a firm with

tangible assets has less collateralized debt and more difficulty monitoring the

extravagance of its employees because of asymmetric information. In this case a firm

can attempt to reduce its agency costs by increasing leverage. In a similar vein,

Aivazian, Booth, and Cleary (2003b) argue that firms in emerging markets face more

financial constraints where the main source of debt is short-term bank financing. Hence,

firms with more tangible assets will have fewer short-term assets that can be used as

collateral for short-term bank financing. This implies a negative relationship between

leverage and tangibility.

Still other studies report a different relationship between tangibility and leverage

depending on whether debt is short-term or long-term. For example, Stohs and Mauer

(1996) find a positive correlation between tangibility and long-term debt, but a negative

42

relationship between tangibility and short-term debt. We define tangibility as the

fraction of total assets attributable to property, plant, and equipment (Titman and

Wessels (1988), Rajan and Zingales (1995), Frank and Goyal (2004), De Jong, Kabir,

and Nguyen (2005), Haung and Ritter (2005), De Haas and Peeters (2006), Flannery and

Rangan (2006), and Alti (2006)).

2.4.7. Size

Most empirical studies point out that debt ratios are related to firm size.

However, the effect of size on leverage is ambiguous. On the one hand, Warner (1977)

and Ang, Chua, and McConnell (1982) assert that bankruptcy costs are relatively smaller

for large firms. Marsh (1982) provides evidence that small firms more often choose

short-term debt while large firms choose long-term debt. Large firms may be able to

take advantage of economies of scale in issuing long-term debt. This suggests a

negative association between the cost of issuing debt and firm size. In the same vein,

Titman and Wessels (1988) articulate that larger firms face lower probability of financial

distress than smaller ones because they are more diversified. Similarly, Flannery and

Rangan (2006) suggest that larger firms are more transparent and have better access to

public debt markets. Consequently, larger firms should have more leverage.

On the other hand, size can be regarded as a proxy for information asymmetry

between firm insiders and the capital market. Large firms are more closely observed by

analysts and therefore should be more capable of issuing equity, and have lower debt.

Accordingly, pecking order theory predicts a negative association between leverage and

size.

43

Ferri and Jones (1979) group firms into six leverage classes and test different

measures of size across these groups. Their study reports evidence that firm size had a

significant impact on leverage. Fama and Jensen (1983) claim that smaller firms tend to

provide less information to lenders than larger ones. Empirical studies, such as Marsh

(1982), Friend and Hasbrouck (1988), Crutchley and Hansen (1989), Rajan and Zingales

(1995), Graham et al. (1998), Wald (1999), Booth et el. (2001)), Korajczyk and Levy

(2003), and Frank and Goyal (2003, 2004) show a positive association between leverage

and company size.

Conversely, Wald (1999) finds that larger firms tend to borrow less. To capture

the size effect on the leverage of firms we use two alternative definitions; the natural

logarithm of sales and the natural logarithm of total assets.

2.4.8. Non Debt Tax Shields (NDTS)

Omani tax laws allow certain tax deductions to be made from a company’s

taxable income. These deductions are often associated with interest payments on debt

and depreciation expense for machinery, buildings and equipment. Firms will exploit

the tax deductibility of interest to reduce their tax bill. Hence, firms with other tax

shields such as depreciation and investment tax credits will have less need to exploit the

debt tax shield. In the context of tradeoff theory, NDTS minimize the use of debt by

providing tax advantage similar to debt. According to Modigliani and Miller (1958),

NDTS create strong incentives for firms to increase leverage. DeAngelo and Masulis

(1980) develop a model where optimal leverage depends on firm’s NDTS, such as

depreciation. Larger NDTS imply a larger chance of having no taxable income, a lower

44

expected corporate tax rate, and a lower expected payoff of interest tax shields, and

thereby lower leverage. In a similar vein, Ross (1977) argues that if a firm issues

excessive debt, it may become tax exhausted in the sense that it is unable to use all its

potential tax shields. Empirical studies generally confirm their prediction. Bradley et al.

(1984) regress leverage against, among other things, a proxy for NDTS. The proxy is

the sum of annual depreciation charges and investment tax credits scaled by the sum of

annual earnings before depreciation, interest, and taxes. They report evidence of a

positive association between leverage and NDTS. However, NDTS is highly correlated

with tangibility and they do not include proxy of tangibility in their studies, which is

also expected to affect firm’s leverage. Similarly, Gardner and Trzcinka (1992) find a

positive relationship. Long and Maltiz (1985) conduct a similar study and find a

negative but insignificant relationship. Studies on the dynamic capital structure by

MacKie-Mason (1990) and Sharpe and Pooley (1991) also report results which

contradict the hypothesized relationship.

Titman and Wessels (1988) analyze the relationship between six kinds of debt

ratios and explanatory variables including NDTS, using Compustat data and structural

modeling. Using the ratio of tax credits over total assets and the ratio of depreciation to

total assets as proxies for NDTS, they find no evidence to support the prediction that

debt ratios are significantly related to NDTS. On the other hand, Fama and French

(2002) find that firms with more NDTS (deductions for depreciation and R&D

expenditures) have less leverage. Similarly, Shenoy and Koch (1996) and Korajczyk

and Levy (2003) find that firms with large NDTS have lower target leverage. Wald

(1999) uses the ratio of depreciation to total assets and Chaplinsky and Niehaus (1993)

45

employ the ratio of depreciation expense plus investment tax credits to total assets to

measure NDTS. Both studies find that leverage is negatively correlated with NDTS.

Following Titman and Wessels (1988), Chen (2004), Deesomsak, Paudyal, and Pescetto

(2004), Akhtar (2005), De Haas and Peeters (2006), and Flannery and Rangan (2006),

we use the ratio of annual depreciation expense to total assets as our empirical measure

for NDTS.

2.4.9. Growth

Galai and Masulis (1976), Jensen and Meckling (1976), and Myers (1977) claim

that when a firm issues debt, managers have an incentive to engage in asset substitution

and transfer wealth from bondholders to shareholders. The associated agency costs are

higher for firms with substantial growth opportunities. Hence, tradeoff theory predicts

firms with more investment opportunities will borrow less because they have stronger

incentives to avoid underinvestment and asset substitution that arise from stockholder-

bondholder conflicts. This prediction is strengthened by Jensen (1986) free cash flow

theory, which predicts that firms with more investment opportunities have less need for

the disciplining effect of debt payments to control free cash flows. In this context,

Titman and Wessels (1988) propose that equity controlled firms have a tendency to

invest sub-optimally hence the cost associated with this agency relationship is likely to

be higher for firms having higher growth. This means that expected future growth

should be negatively related to long-term debt levels. Jung, Kim, and Stulz (1996)

show, when management pursues growth objectives, management and shareholder

interests coincide for firms with strong investment opportunities. On the other hand, for

46

firms without strong investment opportunities, debt serves to limit the agency costs of

managerial discretion as explained by Jensen (1986), Stulz (1990), and Berger, Ofek,

and Yermack (1997).

On the other hand, pecking order theory posits a positive association between

leverage and growth opportunities. In this framework, a firm’s leverage should increase

as investments opportunities exceeds retained earnings, and vice versa. Hence,

maintaining profitability level constant, we should expect higher leverage for those firms

with better growth opportunities.

Previous empirical results are mixed. For example, Bradley et al. (1984), Kester

(1986), Kim and Sorensen (1986), Smith and Watts (1992), Wald (1999), Fama and

French (2002), and Frank and Goyal (2003) find a negative relationship between

leverage and growth opportunities, while Titman and Wessels (1988), Rajan and

Zingales (1995), and Booth et al. (2001) find a significant positive relationship.

Researchers use different proxies for growth opportunities with different implications.

Wald (1999) uses a five-year average of sales growth. Titman and Wessels (1988) use

the ratio of capital investment to total assets as well as the ratio of research and

development to sales to measure growth opportunities. Rajan and Zingales (1995) use

Tobin’s Q as a proxy for growth opportunities. Welch (2004) uses the ratio of book-to-

market equity as a proxy for growth opportunities. We follow Welch (2004).

2.4.10. Volatility

Firms with more volatile assets are expected to have higher probabilities and

expected costs of financial distress (Faulkender and Petersen (2006)). These firms

47

should borrow less and are more likely to raise financing through banks (Cantillo and

Wright (2000)). There are different proxies for volatility such as the standard deviation

of the return on sales (Booth et al. (2001)) or standard deviation of the percentage

change in operating income (Titman and Wessels (1988)). All these studies report

evidence that volatility is negatively associated with leverage. In a recent study, Welch

(2004) uses the log of standard deviation of returns to capture equity volatility and the

log of equity volatility times the ADR to capture firm volatility. In this study, we adopt

the same measures.

2.4.11. Interest Coverage

The interest coverage ratio is another potential determinant of capital structure.

It measures the firm’s ability to meet contractual interest payments. The financial

structure of the firm improves as the interest coverage ratio increases. We follow Welch

and define interest coverage as the ratio of operating income to interest expense.

2.4.12. Industry

Unique features of an industry may be an important determinant of capital

structure. Each industry may have industry-specific patterns of financing because of

differences in product market structure. Ferri and Jones (1979) test the hypothesis that

industry classification is an important determinant of a firm’s capital structure. They

report evidence of a weak relationship between industrial classification and leverage.

On the other hand, Bowen, Daley, and Huber (1982) find a strong relationship between

industrial classification and leverage. Similarly, Bradley et al. (1984) find that there are

48

strong industry effects across leverage ratios. Specifically, they find that leverage ratios

range from a low of 9.1% for drugs and cosmetics to a high of 58.3% for airlines. They

show that 54% of the cross sectional variance in firm leverage can be explained by

industrial classification. In addition, Long and Maltiz (1985) and Kester (1986) show

that pharmaceutical, technological and food and beverages companies have a lower

mean value of leverage compared to firms that came from construction, wood, clothes,

and steel industrial sectors.16 More recently, Welch (2004) finds that industry deviation

have some incremental explanatory power on capital structure dynamics. We follow

Welch’s approach by employing industry deviation to capture industry effects. We

define industry deviation as ADR of a firm minus the ADR average of the sector.

2.4.13. Liquidity

Liquidity of a firm is a measure of internal funds available for financing

investments and is generally regarded as one of the determinants of capital structure.

Pecking order theory suggests that firms prefer internal funds (retained earnings) to

external funds (debt). Hence, they would like to create liquid reserves from retained

earnings to finance future investments. Firm with sufficient liquid assets do not require

external capital (debt). Therefore, the firm’s liquidity position should exert a negative

impact on its leverage ratio. In addition, as Prowse (1990) argues, the liquidity of the

company’s assets can be used to show the extent to which these assets can be

manipulated by shareholders at the expense of bondholders. However, Jensen (1986)

suggests that the management of firms with highly liquid assets (cash) may invest it in 16 MacKay and Phillips (2005) report evidence that most of the variations in financial structure arises within industries rather than between industries.

49

any unprofitable project without the watchful eye of investors and regulatory bodies. In

this case, firms should use debt to prevent managers from wasting resources. The

introduction of debt increases external repayments and thus reduces the firm’s free cash

flow. An implication of Jensen’s theory is that firms should issue debt to discipline

management into working efficiently. We use the ratio of current assets to current

liabilities as a proxy for the liquidity of a firm.

2.4.14. Future Stock Return Reversals

Stock return reversal may be a potential determinant of capital structure

dynamics. Firms that reverse their stock prices may behave differently from firms that

experience stock price continuation (Welch (2004)). To measure the impact of this

variable on capital structure dynamics, we follow the approach in Welch as described in

Appendix C.

2.5. Determinants of Change in Leverage

In order to examine the impact of other variables on capital structure choice, we

follow Welch (2004) by using two estimation models, namely, multivariate and four-

variate. The multivariate model estimate

∈+×⋅+⋅+⋅+=− ++=

++ ∑ )( ,121

2,10 kttccc

C

ccktttkt XVVXADRADR

ttαααα , (2.10)

Where tkttktt ADRIDRX −= ++ ,, . The purpose of this variable is to measure the extent to

which it can explain changes in market leverage ratio. Stated differently,

50

kttX +, measures the change in leverage that arises purely from stock returns. 1V through

cV are named third variables (described in detail in Appendix C). As explained in

Welch (2004), a significantly positive coefficient on cV helps explain the actual debt

ratio. On the other hand, when the coefficient on kttc XV +× , is positive, then cV

incrementally helps to explain firms rebalancing tendencies towards their target. In

addition, we run a four-variate regression with one cV variable at a time. The objective

of the four-variate model is to avoid multicollinearity. The four-variate model estimates

∈+×⋅+⋅+⋅+=− +++ kttccktttkt XVVXADRADRtt ,32,10 αααα . (2.11)

Table 2.7 provides estimates of the magnitudes of the changes in capital structure that

are generated from both the multivariate and four-variate models. The coefficients are

unit-normalized where the coefficients are multiplied by the standard deviation of the

variable. As mentioned earlier in the chapter, our first concern is the economic

significance. As in the US, return-induced debt ratio changes have the largest effect on

capital structure dynamics over one year.17 In economic terms, a one-standard deviation

higher ∆IDR is associated with 1.18% increase in debt ratio. Over an annual horizon,

most of the variables included in the regression are statistically significant. However,

these variables do not have much economic importance. None of the variables other

than return-induced debt ratio changes have a coefficient greater than one percent.

Return-induced debt ratio changes continue to have the largest effect on capital structure

dynamics over a 5-year horizon. However, the magnitude of the effect of return-induced

debt ratio changes over the 5-year horizon is much higher (8.08%) than the one year 17 We define return induced debt ratio as the change in debt ratios that are driven by changes in stock returns.

51

Table 2.7. F-M Regressions Explaining Debt Ratio Changes (ADRt+k, -ADRt) Adding Variables Used in Prior Literature. The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the results of annual cross-sectional regressions explaining change in leverage by adding variables used in the prior literature. Except for the intercept, variables were unit normalized (coefficients were multiplied by the standard deviation of the intercept). The multivariate columns are the coefficients from one big specification,

∈+×⋅+⋅+⋅+=− ++=

++ ∑ )( ,121

2,10 kttccc

C

ccktttkt XVVXADRADR

ttαααα . The four-variate columns are the coefficients from

individual specifications, one variable V at a time, ∈+×⋅+⋅+⋅+=− +++ kttccktttkt XVVXADRADRtt ,32,10 αααα . The

regressions are run for each year t. Fama and MacBeth report means (across years) of the regression intercepts and slopes. The adjusted R2’s are time-series averages of cross-sectional estimates. N is the number of firm year observations and T is the number of cross-sectional regressions. Superscript asterisks indicate Fama and MacBeth type t-statistic above 3(*), 4(**), and 5(***). Variable Multivariate Four-variate Std. Dev. Multivariate Four-variate Std. Dev. Intercept (0.004) varies 0.359 varies

(Flow Variables Measured from t to t+k) ∆IDR =IDRt,t+k - ADRt 1.181*** varies 0.102 8.084*** varies 0.043 Stock Return -0.039 -0.010 0.829 -0.015 -0.029 0.269 ____× ∆IDR -0.057 -0.080 0.106 -0.010 -1.987* 0.012 Equity Volatility 0.146*** -0.002 0.630 0.001 -0.015 0.528 ____× ∆IDR -0.078 -0.121 0.105 -0.013 -0.212 0.047 Firm Volatility -0.185*** -0.004 0.713 -0.015 0.027*** 0.592 ____× ∆IDR 0.046 -0.082 0.138 -0.994 -0.579 0.063 Profitability, Sales 0.045*** 0.006 1.137 -0.147 0.031 0.583 ____× ∆IDR 0.034 0.083 0.117 0.207 -0.565 0.024 Profitability, Assets -0.011 0.018 0.231 0.428 0.139** 0.156 ____× ∆IDR -0.006 0.060 0.021 0.009 -2.199 0.007 Future Stock Return Reversal -0.042** -0.015 0.513 -0.032 -0.119 0.084 ____× ∆IDR 0.022 0.083 0.025 -0.017 -4.561*** 0.004 PROF -0.004 0.001 1.941 0.029* 0.004 1.191 ____× ∆IDR 0.036 0.060* 0.171 0.041 0.064 0.079

52

(Stock Variables Measured at t) Soft Loans 0.023*** 0.008 0.454 0.074* 0.049 0.392 ____× ∆IDR 0.054 0.207*** 0.049 0.024 0.210 0.017 Government Ownership -0.038*** -0.043 0.127 0.031 0.071 0.152 ____× ∆IDR 0.041 0.406 0.014 0.010 -0.153 0.005 Dividend Payout Ratio 0.019** 0.003 1.026 0.014 0.001 1.439 ____× ∆IDR -0.022 -0.024 0.090 0.045 0.150 0.061 Return on Assets 0.027*** 0.039 0.188 0.114 0.191*** 0.118 ____× ∆IDR 0.004 0.079 0.018 1.032 -2.744 0.005 Fixed Assets/Total Assets -0.006 0.002 0.426 -0.020 -0.024 0.314 ____× ∆IDR -0.041 0.040 0.049 0.022 -0.205 0.018 Log Sales 0.041*** 0.008 0.762 -0.016 0.020 0.652 ____× ∆IDR -0.253* -0.049 0.649 0.345 0.556 0.278 Depreciation/Total Assets -0.013* -0.014 0.112 0.010 -0.421 0.027 ____× ∆IDR -0.004 -0.088 0.008 0.001 -2.922*** 0.001 Current Assets/current Liabilities -0.028*** -0.005 0.598 -0.415*** -0.113*** 0.579 ____× ∆IDR -0.051 0.299** 0.071 -0.027 0.046 0.023 Industry Deviation -0.031*** -0.015 0.254 0.001 -0.042*** 0.245 ____× ∆IDR -0.026 0.637*** 0.026 -0.030 0.133 0.020 Tax Rate -0.014 0.006 0.053 0.167 0.177*** 0.126 ____× ∆IDR 0.001 0.037 0.006 -0.141 -3.336*** 0.005 Book/Market Ratio -0.032*** -0.004 1.617 -0.194*** 0.005 1.489 ____× ∆IDR 0.050 0.053 0.163 -0.349 -0.252 0.051 Log Assets -0.031*** -0.008 0.655 -0.093 0.031 0.633 ____× ∆IDR -0.489*** -0.040 0.709 -1.333 -0.636 0.301 Interest Coverage 0.021 0.001 2.314 -0.250 0.001 2.18 ____× ∆IDR -0.028 -0.001 0.184 -0.357*** -0.001 0.089 N,T 1,142,14 Varies 586,10 Varies Adjusted R2 23.0 % varies 50.6% Varies

53

horizon (1.18%) indicating larger economic importance. Three other interaction

variables18 are both statistically and economically significant namely, future stock return

reversal, depreciation, and the tax rate. However, their economic significance is far less

than that of return induced debt ratio changes.

Over one year, the inclusion of almost all variables discussed in the literature

seems to have small impact on the ability of the model to explain the variation in change

in leverage as indicated by the adjusted R2. The adjusted R2 increases by only around

0.8% from 22.2% when only IDR is used to 23% when all other variables are included.

Over a 5-year horizon, the increase became more evident (17.2% in the IDR-only

regression, 50.6% when all other variables are included).

Having discussed the overall results, we briefly discuss the statistical significant

variables included in the estimation.

A. Oman Unique Variables

As discussed before, our analysis includes some unique variables taken from the

Oman economy. These variables include government ownership and soft loans. Over

both annual and five year horizons, the coefficients on soft loans are statistically

significant and positively correlated with the debt ratio. However, the magnitude of the

effect of this variable is small indicating little economic importance. On the other hand,

government ownership is statistically significant only over the one year horizon.

Surprisingly, firms with one standard deviation higher government ownership decrease

debt over one year by 0.04%.

18 Welch (2004) refers to this as a "cross" variable

54

B. Other Statistically Important Variables

Future Stock Return Reversal

Future stock return reversal has some incremental explanatory power for capital

structure dynamics over one year. This suggests that firms that reverse their stock price

after the period under examination behave differently from firms that experience stock

price continuation. The interaction variable shows some economic significance over

five years, but it is far less than that of return induced debt ratio changes.

Industry

Industry deviation has some incremental explanatory power for capital structure

dynamics over both one and five years. The sign on the proxy is negative. The negative

coefficient indicates that firms are inclined to correct towards their industry’s debt ratio.

Again, the magnitude of the effect of this variable is small, suggesting a modest

economic effect on capital structure dynamics.

Equity and Firm Volatility

Over annual horizons, equity and firm volatility are statistically important in firm

capital structure dynamics. The regressions indicate that firms experiencing high equity

volatility increase their leverage. Firm volatility has the opposite impact. Although this

effect does not moderate the importance of stock returns, it does indicate that firms may

not rebalance towards their past debt ratios but towards debt ratios conservative enough

to be in line with the experienced volatilities. While this variable has some statistical

significance over five years, there is little economic significance.

55

Profitability

Three variables are used as proxies for profitability. Return on assets shows

statistical significance over both annual and 5-year horizon. Sales based profitability

shows some incremental explanatory power over one year and assets based profitability

is statistically significant over five years. However, their magnitude is small. An

increase of one standard deviation in return on assets is likely to take on an additional

0.03% in debt ratio over one year. Sales and assets based profitability have similar

effects on the debt ratio.

Liquidity

Liquidity seems to be statistically important in capital structure dynamics over

both one and five years. The negative coefficient suggests that liquid firms are less

levered. As with other variables, the statistical significance is not accompanied by

economic importance, evidenced by the small coefficient on the current ratio.

Size

Both of the proxies used to measure the size effect show statistical significance

over one year.19 The log of assets has a negative coefficient indicating an inverse

relationship between the leverage ratio and the log of assets. A different sign is obtained

with the other size proxy, log of sales, implying that higher debt ratios are associated

with higher sales. However, the statistical significance on both of size proxies vanishes

over the 5-year horizon. Even though there may be statistical significance for these

variables, there is no economic significance.

19 Professor Richard Heaney suggested reporting the correlation estimates between the two size proxies. The correlation estimate is 0.0018 for the one year and it is 0.1144 for the 5 years.

56

Tax

Taxes are neither statistically nor economically important in capital structure

dynamics over one year. However, this variable is statistically significant over five

years. This implies that in the long-run taxes are an important determinant of capital

structure dynamics. Firms are likely to take on an additional 0.177% in leverage per one

standard deviation increase in tax rates over five years. The interaction effects

coefficient is economically important. However, its importance is still much less than

return induced debt ratio changes.

NDTS

NDTS is statistically significant over one year. The negative coefficient implies

that firms with higher NDTS employ less debt. Again, there is little economic

significance, even though there is some statistical significance. However, the interaction

variable is both statistically significant and economically important over five year

horizon. Nevertheless, the impact of it is still far less than that of return induced debt

ratio changes.

Growth

Firms with high book-to-market are associated with lower debt ratio. This

variable has some incremental explanatory power over both one and five years. With

regard to the magnitude effect of this variable on change in leverage, it is in line with

other variables where the impact is small.

57

Signaling

Dividends show some incremental explanatory power in explaining capital

structure dynamics over an annual horizon. The positive coefficient indicates that firms

that pay high dividends are the ones that have higher borrowings.

In summary, the results in Table 2.7 demonstrate that return-induced debt ratio

changes have the largest impact on capital structure dynamics. Though there are other

variables that are statistically significant, they do not have much economic importance.

Previous studies featured some variables as important explanators of capital structure

dynamics. Our explanation is that this importance was caused by the correlation of these

variables with the IDR. Once we include our mechanistically implied debt ratio, these

variables lose their power.

2.6. Are the Results Sensitive to the Use of Bank Debt?

The evidence presented so far has shown that the impact of stock returns on

capital structure dynamics dominates other factors. A natural question is to examine

whether these results hold on bank debt, given that there are some studies that argue

differences between the determinants of bank debt and non-bank debt (Denis and Mihov

(2003) and Faulkender and Petersen (2006)).20

To examine this issue, we estimate the models in Table 2.7 using only bank debt.

The results are presented in Table 2.8. Over one year, as with the results in Table 2.7,

return-induced debt ratio changes subsume other determinants of capital structure. The

20 Faulkender and Petersen (2006) show that the source of a firm’s debt and whether it has access to public debt markets strongly affects its capital structure choice. In particular, they find that firms that have access to the pubic bond markets have significantly more debt.

58

economic importance of this variable is slightly higher than its counterpart in Table 2.7.

In economic terms, a one-standard deviation higher ∆IDR is associated with 1.21%

increase in debt ratio. There are some variables that are statistically significant but the

magnitude of the effect is economically small. For example, the negative coefficient on

liquidity and profitability suggests a negative association with bank debt. Likewise,

firms with growth opportunities tend to have lower bank debt and larger firms do not use

much bank debt. On the other hand, equity volatility is associated with higher bank

debt. Firm volatility has the opposite influence on bank debt.

Over five years, return-induced debt ratio changes continue to have the largest

impact on debt ratio. The economic significance is much larger compared to the one

year horizon. The statistical significance of some of the variables over one year

disappears over five years with some new variables starting to have statistical

importance. The negative coefficient on industry deviation suggests that firms that

wander away from their industry debt ratio are eager to nudge back to it, and that firms

that have higher firm volatility are borrowing more from banks. The positive coefficient

on government ownership indicates that firms with higher government ownership obtain

more bank loans. As with the one year horizon, larger firms are less dependent on bank

debt. The future stock return reversibility proxy is both statistically and economically

significant. This suggests that firms with large stock price reversals behave differently

from firms that do not experience a reversal. Taxes have some incremental explanatory

power over five years. However, the coefficient on this variable is economically small.

59

Table 2.8. F-M Regressions Explaining Bank Debt Ratio Changes (ADRt+k -ADRt) Adding Variables Used in Prior Literature. The sample are all publicly listed firms at the MSM between 1989-2003. The table presents the results of annual cross-sectional regressions explaining change in bank leverage by adding variables used in the prior literature. Except for the intercept, variables were unit normalized (coefficients were multiplied by the standard deviation of the intercept). The multivariate columns are the coefficients from one big specification,

∈+×⋅+⋅+⋅+=− ++=

++ ∑ )( ,121

2,10 kttccc

C

ccktttkt XVVXADRADR

ttαααα . The four-variate columns are the coefficients from

individual specifications, one variable V at a time, ∈+×⋅+⋅+⋅+=− +++ kttccktttkt XVVXADRADRtt ,32,10 αααα . The

regressions are run for each year t. Fama and MacBeth report means (across years) of the regression intercepts and slopes. The adjusted R2’s are time-series averages of cross-sectional estimates. N is the number of firm year observations and T is the number of cross-sectional regressions. Superscript asterisks indicate Fama and MacBeth type t-statistic above 3(*), 4(**), and 5(***). variable Multivariate Four-variate Std. Dev. Multivariate Four-variate Std. Dev. Intercept 0.068 varies 0.359 varies

(Flow Variables Measured from t to t+k) ∆IDR = DRt,t+k - ADRt 1.211* varies 0.093 6.308*** varies 0.037 Stock Return -0.056 -0.011 0.829 -0.053 -0.029 0.269 ____× ∆IDR 0.001 -0.027 0.041 -0.036 -0.780 0.014 Equity Volatility 0.072* 0.001 0.630 -0.064 -0.024 0.528 ____× ∆IDR 0.113 0.121 0.045 -0.114 -0.232 0.046 Firm Volatility -0.084* -0.013 0.713 1.587*** 0.055*** 0.592 ____× ∆IDR -0.157 0.040 0.090 0.114 0.343 0.068 Profitability, Sales -0.034*** -0.004 1.137 -0.039 0.021 0.583 ____× ∆IDR -0.065 -0.047 0.104 0.296 0.155 0.025 Profitability, Assets 0.038 0.027 0.231 -0.265 0.095 0.156 ____× ∆IDR 0.116 0.407* 0.023 -0.055 -0.268 0.007 Future Stock Return Reversal -0.011 0.002 0.513 0.079 0.296*** 0.084 ____× ∆IDR 0.092 0.142* 0.121 0.104 1.743*** 0.003 PROF 0.003 -0.001 1.941 -0.011 0.003 1.191 ____× ∆IDR -0.036 -0.004 0.154 -0.008 -0.029 0.044

60

(Stock Variables Measured at t) Soft Loans -0.015 -0.001 0.454 -0.032 0.005 0.392 ____× ∆IDR 0.014 -0.037 0.052 0.008 0.378 0.014 Government Ownership 0.011 0.020 0.127 0.045*** 0.064 0.152 ____× ∆IDR -0.038 -0.729 0.009 0.060 1.522*** 0.006 Dividend Payout Ratio -0.007 -0.001 1.026 0.045 0.008 1.439 ____× ∆IDR 0.029 0.034 0.095 -0.017 -0.057 0.061 Return on Assets 0.018 0.030 0.188 -1.299*** 0.143 0.118 ____× ∆IDR 0.029 0.019 0.035 -0.401*** 0.701 0.006 Fixed Assets/Total Assets -0.012 0.005 0.426 -0.033 -0.027 0.314 ____× ∆IDR 0.025 -0.002 0.053 -0.081 -0.595 0.018 Log Sales 0.009 0.004 0.762 0.050 0.036 0.652 ____× ∆IDR 0.028 0.007 0.595 0.429 0.556 0.241 Depreciation/Total Assets -0.027 -0.053 0.112 0.021 0.249 0.027 ____× ∆IDR 0.019 0.318 0.006 0.042 2.351*** 0.001 Current Assets/Current Liabilities -0.037* -0.015 0.598 0.018 0.004 0.579 ____× ∆IDR -0.031 -0.018 0.048 0.064 0.700 0.027 Industry Deviation 0.016 0.002 0.254 -0.015 -0.120** 0.245 ____× ∆IDR 0.042 0.539** 0.026 -0.066 -0.857 0.011 Tax Rate -0.008 -0.174 0.053 0.217 0.087** 0.126 ____× ∆IDR -0.015 -0.751 0.006 -0.139*** -1.272*** 0.005 Book/Market Ratio -0.015* -0.001 1.617 -0.044 0.005 1.489 ____× ∆IDR -0.022 -0.021 0.148 0.039 0.149 0.058 Log Assets -0.046*** -0.004 0.655 -0.903* 0.038 0.633 ____× ∆IDR -0.047 -0.059 0.644 -0.091 0.069 0.254 Interest Coverage 0.035 0.001 2.314 1.052 0.001 2.180 ____× ∆IDR -0.026 0.001 0.195 0.202 -0.001 0.096 N,T 1,142,14 Varies 586,10 Varies Adjusted R2 9.70% Varies 14.90% Varies

61

In summary, stock-return induced debt ratio changes have the largest impact on

bank debt ratio. Other variables have minor economic significance on capital structure

dynamics.

2.7. Comparisons with the Current Literature

There is an extensive debate on whether firm rebalances their capital structure

with some studies reporting evidence supporting rebalancing and others failing to do so.

A recent paper by Leary and Roberts (2005a) argues that firms respond to equity

issuances and equity price shocks by rebalancing their leverage to stay within an optimal

range. They argue that the persistence effects of shocks on leverage documented by

Welch is more likely due to optimizing behaviour in the presence of adjustment costs, as

opposed to indifference towards capital structure.21 However, Chen and Zhao (2005a)

examine thoroughly Leary and Roberts findings and they report evidence that

contradicts their results. Leary and Roberts demonstrate through simulation that a firm’s

market leverage ratios can be driven by equity valuations because these firms do not

rebalance constantly due to adjustment costs. It follows from this argument that we

should observe firms with higher equity returns issuing more debt relative to equity than

other firms when the adjustment boundaries are reached. Chen and Zhao (2005a) find

the opposite – firms with higher equity returns are relatively more likely to issue equity.

In general, Chen and Zhao find that tradeoff theory does a poor job of explaining the

issuance decisions, contradicting Leary and Roberts. In particular, they find both the

key variables in tradeoff theory and the transaction cost variable predict issuance 21 As we show in Section 2.3.4, adjustment costs are unlikely to be the main reason behind our results.

62

decisions the wrong way. They conclude that dynamic tradeoff theory with transaction

costs is not likely to be the main interpretation for Welch’s results.22 Further, Chen and

Zhao find little evidence that suggests that firms adjust their leverage ratios toward

target leverage through issuance decisions. Most importantly, Chen and Zhao report

evidence that stock returns are an important determinant of capital structure decisions

which is consistent with Welch and this study. In a similar vein, Haung and Ritter

(2005) find that the effects of debt and equity issues on both book and market leverage

last for more than ten years, which is inconsistent with Leary and Roberts. They

attribute the difference in the results to the fact that their regression approach controls

for determinants of target leverage. Titman and Tsyplakov (2005) develop a dynamic

model of capital structure and report evidence that firms adjust their capital structure

quite slowly. Similarly, Kayhan and Titman (2006) find that stock returns have a strong

effect on capital structure and these effects are at least partially persistent for at least ten

years.

In a different paper, Chen and Zhao (2005b) find no evidence that equity

issuance is driven by target leverage ratio adjustments. Similar to Chen and Zhao,

Hovakimian (2004) examines whether security issues and repurchases adjust the capital

structure towards their target. He documents that only debt reductions are initiated to

offset the accumulated deviations. He suggests that the importance of target leverage in

earlier studies is driven by the subsample of equity issuers accompanied by debt

reductions.

22 In a number of instances, Chen and Zhao (2005a) report evidence that contradicts Leary and Roberts (2005a).

63

Using a similar argument to that of Leary and Roberts (2005a), Flannery and

Rangan (2006) report evidence that firms do target a long-run capital structure and the

typical firm converges towards their long-term target at a rate of more than 30% per

year. Further, they report evidence that stock price changes have only transitional

effects on capital structure. Flannery and Rangan suggest that Fama and MacBeth

regression employed by Welch fails to recognize the data’s panel characteristics. They

argue that panel regression with unobserved (fixed effects) is more appropriate if firms

have relatively stable unobserved variables influencing their capital structure targets. To

examine whether our results are robust to their model, we estimate their partial

adjustment model using Fama and MacBeth (F-M) and fixed effects. The plain

variables in Table 2.7 are included in all estimation models, but not reported here. The

first column in Table 2.9 reports F-M estimates. The coefficient on lagged ADR implies

that firm close 17.96% of the gap between current and desired leverage.23 Stated

differently, it takes around three years to close half the gap between a typical firm’s

current and desired leverage. This slow adjustment is consistent with our previous

findings. This suggests that convergence towards a long-run target is unlikely to explain

much of the variation in firm’s debt ratios. The coefficient on SPE indicates that firms

adjust 14.94% of stock return surprises in the year they occur. This indicates that firms

do try to counteract the influence of stock return. While this result is different from the

23 Our results are in line with that reported by Fama and French (2002) where they find that the speed of adjustment is between 7 and 10% for dividend payers and between 15 and 18% for dividend non-payers.

64

findings of Welch, it still suggests that the speed of adjustment to the stock price

surprises is slow.24

Following Flannery and Rangan, we estimate the partial adjustment model with

fixed effects.25 The results are reported in column 2. The estimated coefficients on the

determinants of target leverage generally resemble their F-M counterparts. However,

the estimated coefficient on ADR now implies a faster adjustment speed of 24.21%.

While this speed of adjustment is higher than that reported using F-M, it is still

considerably less than that reported by Flannery and Rangan of 34% for the US.

However, Hsiao (2003) and Baltagi (2005) demonstrate that fixed effects give

biased estimates for the coefficients of the partial adjustment model. In particular, the

estimated coefficient of the lagged dependent variable using fixed effects is biased

downward. In other words, fixed effects models tend to overestimate the speed of

adjustment.26 In this vein, Huang and Ritter (2005) find that there is a substantial bias

associated with the use of the fixed effects with a within-group estimator for a short

panel. In essence, the estimated coefficients of the lagged dependent variable with firm

fixed effects are biased downward, especially when the time dimension is short. They

evaluate the magnitude of the bias and find that it is critically important to correct for the

short time dimension bias.

24 Welch (2004) shows that firms do not counteract the mechanistic effects of stock returns on their debt-equity ratios. 25 Following Flannery and Rangan, we use an instrumental variable for SPE where we regress SPE on the regression’s predetermined variables and the realized returns to the average firm in the same industry. 26 Bond (2002) documents that the bias of a fixed effect estimator can be very severe.

65

Table 2.9. Flannery and Rangan Model Explaining Actual Debt Ratio (ADRi,t+1) Adding Variables Used in Prior Literature. The sample are all publicly listed firms at the MSM between 1989-2003. The table reports the results of the estimated partial adjustment model explaining ADR by adding variables used in the prior literature. The model is:

1,,11.2,101, )()1()1( +++ ++−+−+= tititititi XBSPEADRaADR μλλλ where ADR is the actual debt ratio. IDR is the actual debt ratio at time t augmented by the firms return in (t,t+1). SPE = IDR – ADRi,t measures the impact of price changes on ADR during (t,t+1). The lagged “X” variables determine a firm long-run target debt ratio and include the plain variables in Table 2.7 as described in Appendix C. T-statistics are presented in parentheses below the corresponding estimate. The first column is estimated using Fama-MacBeth methodology. The second column is using fixed effects and the last column is using system General Method of Moments. Reported R numbers for models including fixed effects are “within” R2 statistics. m1 and m2 are tests for first-order and second-order serial correlation, asymptotically N (0, 1). Sargan is a test of the overidentifying restrictions for the GMM estimators, asymptotically χ2. P-values are reported for m1, m2, and Sargan test. There are 1,142 firm-year observations.

Method F-M Fixed Effects System GMM ADR 0.8204 0.7579 0.7995

(49.3698) (36.7177) (50.2737) SPE =IDRt,t+k - ADRt 0.8506 0.7986 0.8454

(17.1700) (14.885) (28.9119) Adjusted R2 0.7188 0.6088 - Sargan test27 0.6750

m1 0.0002 m2 0.8713

A more appropriate method to deal with the problem of short panel is to use

GMM estimators (Anderson and Hsiao (1981), Arellano and Bond (1991), and Arellano

and Bover (1995)). However, Blundell and Bond (1998) suggest that the standard GMM

can result in large finite-sample biases and poor precision in the estimators when used

with highly persistent data series. They show that these biases could be dramatically

reduced by applying the system GMM proposed by Arellano ad Bover (1995).28

27 The reported p-value indicates that we are unable to reject the validity of the instruments which suggest that these estimates are consistent. 28 Blundell and Bond (1998) show that the biases can be dramatically reduced by exploiting reasonable stationary restrictions on the initial conditions process. These yields a system GMM estimator in which

66

Similarly, Blundell and Bond (2000), Blundell, Bond, and Windmeijer (2000), and

Baltagi (2005) demonstrates that the system GMM produces more efficient results in

finite samples than standard GMM estimators.29 We adopt this method and we report

the results in column three. According to the system GMM approach, the speed of

adjustment is 20.05%.30 This speed is slower than that reported using fixed effects.

Most importantly, all results from the three estimation methods suggest that firms move

towards target capital structure slowly. This evidence is in line with our previous results

from Table 2.3. Thus, our results are robust to various method of estimation. Our

results are similar to those reported by Huang and Ritter who document that the speed of

adjustment on market leverage decays at between 11% and 25% per year which they

interpret as evidence of a slow adjustment.

In summary, we study the determinants of capital structure dynamics in a country

with unique financing arrangements. We report evidence that stock returns are a

primary determinant of capital structure. This evidence is in line with many concurrent

studies such as Chen and Zhao (2005a), Cai and Zhang (2005), and Kayhan and Titman

(2006). The slow adjustment we find is consistent with Jalilvand and Harris (1984),

Fama and French (2002), Baker and Wurgler (2002), Welch (2004), Kayhan and Titman

(2006), Huang and Ritter (2005), and Titman and Tsyplakov (2005). Moreover, we

provide new evidence that firms do try to counteract the mechanistic impact of stock

returns, but do so at a low speed. lagged first-differences of the series are used as instruments for the level equations, in addition to the usual lagged levels as instruments for equations in first-differences (Arellano and Bover (1995)). 29 See Baltagi 2005, Chapter 8 and Xu (2006) for a description of the system GMM. 30 For the US, Lemmon, Roberts, and Zender (2006) find that the speed of adjustment is 35% using firm fixed effects. However, the system GMM shows a much slower speed of adjustment of 21.4%. Likewise, Xu (2006) documents that firms that rebalance over time adjust to their target capital structure slowly at 16% using the system GMM.

67

2.8. Conclusion

We examine the determinants of corporate capital structure in a unique financing

environment. The study has several advantages over earlier studies in the context of the

data used. First, the data avoid the complexity of tax rates faced by previous studies,

and as a result may help us to provide clearer results on the impact of taxes on capital

structure. Second, we introduce new variables that are unique to the country under

analysis. Third, we distinguish between bank and non-bank debt.

Our main findings are as follows. First, we find strong evidence that equity price

shocks have a primary effect on corporate capital structure dynamics. Second, the

average firm in our sample shows some tendency to rebalance their capital structure in

response to shocks in the market value of equity. Still, stock returns exert more

influence on the market leverage ratio compared to the effects of rebalancing. Third,

when included with other proxy variables (e.g., profitability, tangibility, etc.), stock

returns dominate other terms in the regression. Some of the other variables discussed in

the literature have statistical significance; however, the magnitude of their effect on the

debt ratio is modest. For instance, taxes show some incremental explanatory power but

it is far less than the impact of stock return over five years. Fourth, when used with

bank debt, the impact of stock returns continues to subsume other factors. Fifth, we

examine Leary and Roberts findings and we report evidence that adjustment costs are

unlikely to be the main interpretation for our results. Finally, we show that our results

are robust to the adjustments suggested by Huang and Ritter (2005) and Flannery and

Rangan (2006).

68

There are some important differences between the findings of this study and

Welch (2004). First, the impact of stock returns seems to be much less compared to the

US. Similarly, firms appear to have a higher inclination to readjust their capital

structure in Oman. Second, in contrast to Welch, we find short-term debt issuing

activity is the most capital structure relevant corporate activity. Third, we find new

evidence that firms do try to counteract the mechanistic effect of stock return. However,

the speed of adjusting to offset the impact of stock return surprises is slow, with an

average of around 15% per year. Our conclusion is that stock price effects are more

important in explaining leverage ratios than previously identified factors.

In sum, the empirical results highlight the distinctive features of the Omani

business environment and could therefore be of particular value for policy makers. For

example, the apparent narrow choice over sources of finance for corporate investment

should be of interest to policy makers as expansion of these sources may contribute to

economic growth. Second, the limited size of bond market in Oman constrains firm

choices over sources of financing, forcing them to take loans from banks which charge

higher interest rate. The development of a market for corporate bonds will give firms

more room in choosing sources of financing. Thus polices that are concerned with the

development of the bond market may need to be considered if firms are to be

encouraged to optimize their capital structure.

Data availability is a major limitation in capital structure and other finance

studies in emerging markets. For example, the R&D expenditure data are not available

for companies in Oman. Similarly, no data on selling expense are available. There are

also no data on insider ownership and institutional ownership at the firm level. Further,

69

data on adjustment costs proxies such as underwriter spread and credit rating are not

available. Researchers spend a considerable amount of time in data collection and

processing because of the lack of validated databases in emerging markets like Oman.

In future, as more data become available, one could explore additional variables that

may have an impact on capital structure dynamics of firms in Oman.

70

Chapter 3: Ex-Dividend Day Behaviour in the Absence of Taxes and

Price Discreteness

3.1. Introduction

In a frictionless market with no transaction costs and no taxes, the drop in stock

price when a stock goes ex-dividend should equal the value of dividend paid on that

stock. However, it is well documented that on average stock prices do not drop by the

full amount. In particular, numerous studies have shown that stock prices drop by less

than the amount of the dividend. Several interpretations are advanced in the literature to

explain ex-dividend day behaviour. For example, Elton and Gruber (1970) interpret this

as a reflection of the tax differential between dividends and capital gains. Many other

studies share the same interpretation. However, as discussed in Frank and Jagannathan

(1998), the complexity of the U.S. tax system makes it difficult to validate whether this

interpretation is indeed correct.31

Other interpretations include price discreteness, transaction costs and bid-ask

bounce. Bali and Hite (1998) suggest that tick sizes can explain ex-dividend price ratios

which are not equal to one. They argue that the drop in price less than the dividend is

due to discreteness in prices rather than taxes. According to them, because stock prices

trade in discrete ticks but dividend amounts are continuous and, on average, fairly small

in amount, the ex-day premium will be less than one even in the absence of differential

tax rates. Since investors are not willing to pay more than the dividend amount for the 31 For a description of how complex the U.S. tax system, see Callaghan and Barry (2003).

71

dividend received, the ex-day price drop will be rounded down to the nearest tick, so that

the change in stock price on the ex-dividend day is always less than the amount of the

dividend. Similarly, when a dividend received is between ticks, there will be positive

abnormal returns. Frank and Jagannathan (1998) offer another market microstructure

interpretation where they argue that collection and reinvestment is bothersome for

individual investors but not for market makers. In other words, market makers have a

comparative cost advantage to collecting and reinvesting dividends, so they buy shares

before a stock goes ex-dividend and resell them after the stock goes ex-dividend. Most

of the trades occur at the bid price before the stock goes ex-dividend and at the ask price

on the ex-dividend day. The resulting shift from bid to ask causes positive ex-day

returns. In their model, the resulting bid-ask bounce contributes, if not totally explains

the ex-dividend day behaviour.

The third interpretation concentrates on how the interaction of transaction costs,

taxes, and risk impacts ex-dividend day return and trading volume (e.g., Kalay (1982a),

Lakonishok and Vermaelen (1986), Heath and Jarrow (1988), Karpoff and Walking

(1988, 1990), Grammatikos (1989), Boyd and Jagannathan (1994), Michaely and Vila

(1995, 1996), and Michaely, Vila, and Wang (1996), among others). A common

prediction among these papers is that transaction costs and risk exposure inhibit

arbitrage opportunities and dividend capture beyond some point, and consequently in

equilibrium, the drop of stock price on the ex-dividend day may not be equal to the

dividend amount.

In this chapter, we use a unique data set from Oman where the above factors are

either absent or limited. These data offer significant advantages over data used by

72

previous studies. First, the absence of taxation of dividends and capital gains in Oman

provides an ideal opportunity to examine ex-dividend behaviour without any ambiguity

regarding effective marginal tax rates on dividends and capital gains. Hence, these data

allow us to avoid the complexities of the U.S. tax system where the population of US

investors includes many different types of traders subject to a variety of tax structures.

Second, another major advantage of examining ex-dividend behaviour in Oman is that

the confounding effects of stock price discreteness on ex-day behaviour are much

smaller compared to other market where prices are not decimalized (until recently the

minimum tick size was one-eighth of a dollar in the US). Kadapakkam (2000, p. 2843)

states that the “coarseness in U.S. price data hinders the evaluation of the magnitude of

ex-dividend day price drop relative to the typically small quarterly dividends”. Price

discreteness is less of a problem in Oman, because stock prices are decimalized. In

addition, dividends are usually paid once a year in Oman, whereas in many other

countries (e.g., US, UK, Australia) dividends are paid quarterly or semi-annually. These

factors increase the size of the dividends relative to the minimum tick size for the stock

compared to other countries, and this reduces the importance of the tick size as a driver

of ex-day behaviour. Third, transaction costs become more important when dividends

are relatively small, and act like a barrier against short-term trading. However, since

dividends are usually distributed annually rather than quarterly, this suggests that

transaction cost models may not be as important in Oman. Fourth, in addition to daily

stock prices, the data set contains intra-daily data which allow us to directly test the

Frank and Jagannathan (1998) market microstructure model. Because of these data

73

advantages, we can examine the ex-dividend day behaviour in a less noisy and a more

powerful manner than previous studies.

We find that stock prices on ex-dividend days fall by significantly less than the

amount of dividends and ex-day abnormal returns are significantly positive when we use

daily data. We examine whether transaction costs and risk inhibit arbitrage. Our results

show that neither is significant. We also examine abnormal volume around the ex-days

and find a reduction in volume around the ex-day. These results do not support the

short-term trading hypothesis which predicts a positive abnormal volume around the ex-

days. We also test Frank and Jagannathan’s (1998) model which argues that the ex-day

premium deviates from one due to the effects of the bid-ask bounce. This is what we

find. In particular, we find that when midpoint prices are used instead of transaction

prices, stock prices drop by the full amount of the dividend on the ex-day. We also find

that the ex-day abnormal return is insignificantly different from zero. Similar results

emerge from using bid-to-bid and ask-to-ask prices. In general, our results demonstrate

that the microstructure of the Omani stock market explains the ex-day pricing anomaly.

This finding supports the views of Kalay (1982a), Miller and Scholes (1982), Frank and

Jagannathan (1998), and Liano, Hardin, and Huang (2003) who question the importance

of taxes as a key factor driving ex-dividend day pricing.

The remainder of the chapter is organized as follows. Section 3.2 discusses the

relevant theories and empirical literature for this study. This section also summarises

the empirical literature for each of the theories and develops testable hypotheses about

what should happen on the ex-day, according to these theories. In Section 3.2.1, tax

explanations are presented. Transaction cost models are discussed in Section 3.2.2.

74

Section 3.2.3 reviews market microstructure models. Section 3.3 describes the

institutional settings in Oman. It also discusses the specific data sources used in this

chapter, describes our data sample and provides summary statistics. Section 3.4 presents

empirical results and Section 3.5 concludes the chapter.

3.2. Theory, Hypothesis, and Empirical Evidence

As described in Graham, Michaely, and Roberts (2003), the explanation of the ex-

dividend day return can be categorized into three groups: pure tax explanation,

transaction costs and risk, and market microstructure. We next review each group in

details.

3.2.1. Tax Explanations

An investor who has decided to sell his stock in a corporation faces a timing

decision of whether to sell on the cum-day or the ex-dividend day. If a US investor

decides to sell his stock on the cum-day, he receives the cum dividend price (Pcum) and

he pays tax at the capital gain tax rate (tg) on excess of the cum dividend price over the

original purchase price of the stock (Po). If he were to sell on the ex-dividend day, he

receives the ex-dividend price (Pex), and pays tax on the excess of the ex-dividend price

over the original purchase price of the stock at the capital gains tax rate. In addition, on

the ex-dividend day he will receive the dividend (D) and pays tax at the ordinary tax rate

(to). For him to be indifferent between selling stocks on or before the ex-dividend date

Elton and Gruber (1970) show that,

75

)1()()( ooexgexocumgcum tDPPtPPPtP −+−−=−− (3.1)

Rearranging equation (3.1), we obtain

g

oexcum

tt

DPP

−−

=−

11

(3.2)

The left-hand-side of this expression is called the ex-day premium or the dividend drop

off ratio. This ratio will be referred to as the ex-day premium henceforth. The right-

hand-side variable captures the differential tax treatment of dividends versus capital

gains and is called the ex-day tax preference ratio (Chetty, Rosenberg, and Saez (2005)).

Elton and Gruber (1970) argue that equation (3.2) can be used to infer clientele effects

(originally proposed by Miller and Modigliani (1961)); if investors with high marginal

tax brackets hold low dividend yield stocks, then these stocks should have relatively

small premiums, reflecting the tax bracket of their median shareholder. Equation (3.2)

predicts that the higher the dividend yield, the higher the premium. This is the intuition

underlying the tax clientele hypothesis.

For the case of Oman, there are neither taxes on dividends nor on capital gains,

therefore tg and to in equation (3.1) is zero and it simplifies to:

DPP excum += (3.3)

Rearranging terms:

1=−

DPP excum (3.4)

Based on the above equation, the premium is expected to be equal to one: the price drops

by the exact amount of dividends.

Hypothesis 1: we expect the ex-dividend day premium to be one in the case of Oman.

76

3.2.1.1. Empirical Evidence

In one of the earliest published studies on ex-dividend day pricing, Campbell and

Beranek (1955) document that ex-dividend behaviour of stock prices has an impact on

the portfolio decisions of investors. They report evidence that on average, ex-day stock

prices drop by less than the amount of dividends. Barker (1959) and Durand and May

(1960) report similar results. Elton and Gruber (1970) provide more detailed evidence

of a tax differential effect and of a tax-induced clientele. Using U.S. data for the period

April 1966 to March 1967, they document a premium of 0.78. In addition, they report

evidence that the premium on the ex-day is positively associated with the dividend yield.

In fact, for the highest yielding decile of stocks, the price actually drops more than the

amount of dividend. Their conclusion about the importance of tax effects is confirmed

by Barclay (1987), who presents evidence that the ex-day premium is equal to one prior

to the adoption of income taxes in 1913. He also documents that the amount of stock

price decrease is approximately equal to one for all dividend yield levels. He interprets

these results to support the hypothesis that in the pretax period investors viewed

dividends and capital gains to be perfect substitutes and that differential tax rates on

dividends and capital gains have caused investors to discount the value of taxable cash

distributions relative to capital gains. Poterba (1986) re-examines the ex-day price drop

for two classes of Citizens Utilities originally studied by Long (1978), one of which

distributed only a cash dividend while the other distributed only a stock dividend of

equal size. He documents that the ex-day drop for cash dividend shares’ is only 77% of

the dividend yield. The ex-day drop for stock dividends is 97% of the dividend yield.

77

On average, the fall in stock price on the ex-day is the same the value of dividends for

stock dividends. This evidence is consistent with the tax hypothesis.

Further evidence of the tax affect is reported by Callaghan and Barry (2003)

who examine ex-dividend day trading of American Depositary Receipts using a sample

of 1,043 dividends over the period 1988 to 1995. They report evidence that is consistent

with tax-motivated trading. Recently, Elton, Gruber, and Blake (2005) analyze the ex-

day pricing under different tax regimes of two mutual funds for the 1988-2001 period.32

What makes their sample interesting is that it contains a set of securities (municipal

bond funds) for which the ex-dividend price drop should be greater than the dividend if

taxes matter as well as a set of securities (taxable bonds) for which the drop should be in

general less than the dividend. For taxable closed ended mutual funds, they report

evidence that drop in price on the ex-date is smaller than the amount of dividends when

dividends are taxed higher than capital gains. In the case of non-taxable closed end

municipal bond funds, they document that stock prices drop by more than the amount of

dividends on the ex-date. This is consistent with a tax argument and inconsistent with

the standard microstructure arguments. For the case where dividends and capital gains

are taxed at the same rate, they find that stock prices fall by the exact amount of the

dividend. Their findings are consistent with the hypothesis that taxes determine the

value of dividends relative to capital gains.33

32 Elton et al. (2005) test whether the observed drop off is greater than one, however this is a rather weak test because their theoretical model makes predictions as to what the drop off ratio should be, given the capital gains tax rate. A test of whether the observed drop off was equal to the predicted drop off would be a much stronger experiment. 33 Jain (2006) re-examines Elton et al. (2005) results and finds that ex-day price changes of closed-end funds are not always consistent with the tax hypothesis. He shows that the ex-dividend day drop off ratios and ex-day abnormal returns do not vary significantly from one tax regime to the next.

78

In a similar vein, Li (2005) examines whether institutions and individuals react to

ex-dividend events and how their reaction impacts ex-day excess returns. The results

show that both type of investors trade around ex-days to relieve their tax burdens. The

results reported are consistent with differential taxation of dividends and capital gains

influencing the ex-day price behaviour. Dhaliwal and Li (2006) analyze the effect of the

interaction between dividend yield and institutional ownership on excess trading volume

around ex-dividend days. They hypothesize that ex-dividend day trading is motivated

by tax heterogeneity among investors. Their cross-sectional tests provide strong support

for their hypothesis. Brown and Zhang (2006) provide further evidence supporting the

tax explanation. They examine the effect of the 2003 dividend tax cut which removes

the preferential tax treatment of capital gains over dividends. Consistent with the tax

hypothesis, they find that the ratio of the change in price over the dividend on the ex-day

increases significantly from 0.749 in 2002 to 0.946 in 2004, which is close to one as

predicted by the Elton and Gruber (1970) when there is no differential taxation between

dividends and capital gains. They also find that the average ex-day abnormal return of

taxable distributions decreases after the tax cut. Whitworth and Rao (2006) test the tax

explanation of the ex-day stock price behaviour over a continuous sample period dating

back to the inception of income tax. They find that ex-day price changes are related to

personal dividend and capital gains tax rates in the manner suggested by Elton and

Gruber. Similar to Elton and Gruber (1970), they also find that tax clienteles exist and

that they influence ex-dividend stock price behaviour. Graham and Kumar (2006)

investigate the trading behaviour of more than 60,000 households. Their results are

consistent with dividend clienteles.

79

Tax-related behaviour has also been tested as an explanation of ex-dividend day

behaviour in countries other than the U.S, but with mixed success. In Canada,

Lakonishok and Vermaelen (1983) use the Elton and Gruber (1970) approach to study

the effect of major tax reform on the ex-day behaviour. They find that the ex-day drop

was less correlated to dividend yields and was not affected by the change in taxation

differences of ordinary income and capital gains. They conclude that the effects are

more likely to be a short-term trading effect than a tax clientele effect. Booth and

Johnston (1984) extend the work of Lakonishok and Vermaelen (1983) and investigate

ex-dividend day behaviour using the Elton and Gruber methodology over four distinct

tax regimes between 1970 and 1980. They provide evidence of equity pricing with a

premium that is significantly less than one. However, unlike Elton and Gruber (1970),

they were unable to find any evidence of a tax driven clientele effect with respect to

investors’ preference for dividend yield. More recently, Dutta, Jog, and Saadi (2005) re-

examine ex-dividend day price and volume behaviour in the Canadian stock market.

Unlike previous studies, they provide evidence on the co-existence of both tax and short-

term trading effects. By examining the abnormal returns as well as abnormal volumes

around ex-day, they find strong evidence of short-term trading which is consistent with

the dividend capturing activities around the ex-dividend day.

Bartholdy and Brown (1999) examine the same issues using data from New

Zealand where companies could pay either or both taxable and nontaxable dividends.

They report evidence consistent with the presence of a tax clientele effect. In a

comprehensive empirical analysis of stock price behaviour around the ex-day in Japan,

Kato and Loewenstein (1995) find that tax considerations associated with dividends are

80

able to explain the ex-day behaviour. However, the tax effect appears to be of secondary

importance. Hietala (1990) analyzes the stock market in Finland, which has a tax

structure similar to the post 1987 U.S. system, and documents price movements

consistent with the tax clientele hypothesis.

Further evidence supporting the tax interpretation is provided by McDonald

(2001) who examines ex-dividend day behaviour in Germany which has an imputation

dividend system. He finds that the ex-day price drop of German stock is approximately

126% of the value of dividend, thereby concluding that the market values the tax credit

at about 50% of the amount of credit. This supports the tax-based interpretation. For

the U.K., Bell and Jenkinson (2002) investigate the effects of a July 1997 tax reform

under the imputation system and report evidence that taxation affects the valuation of

companies, and that pension funds were the effective marginal investors for high-

yielding companies. In a similar environment, Bellamy (1994) examines the imputation

system in Australia. He also finds evidence consistent with the tax hypothesis. Clarke

(1992) also investigates the ex-dividend day behaviour for Australia and reports similar

results to Bellamy (1994). Prior to the imputation, Brown and Walter (1986) report an

average drop off ratio of 0.74 suggesting that the Australian stock market has been

discounting dividends to capital gains by approximately 25%. They report weak

evidence that the drop off ratio is related to the dividend yield. They conclude that

several confounding effects and the wide dispersion of tax status in Australia prevent

them from concurring with the tax clientele hypothesis.

Green and Rydqvist (1999) took advantage of Swedish lottery bonds to examine

the ex-day affects. In this environment, cash distributions are tax advantaged relative to

81

capital gains. In addition, there are barriers to short-term trading. They find that the

ratio of price drop to coupon averages 1.30 for Swedish Lottery bonds, implying that the

relative tax advantage of coupons relative to capital gains are impounded into bond

prices. Green and Rydqvist (1999) conclude that bonds are priced around the ex-day to

reflect the differential tax rates on income and capital gains. Florentsen and Rydqvist

(2001) find a premium greater than one for similar lottery bonds in Denmark. Michaely

and Murgia (1995) investigate the effect of taxation on stock price and trading volume

around the ex-day in Italy. By examining block trading activity, they present evidence

consistent with tax-related trading around the ex-dividend day. As predicted by a tax

effect hypothesis, abnormal volume is higher for securities with greater tax

heterogeneity. In addition, trading activity is higher for stocks with lower transaction

costs. Lasfer and Zenonos (2003) investigate the ex-dividend behaviour in four

European countries namely France, Germany, Italy and U.K. They provide evidence

that supports the tax hypothesis. Milonas, Travlos, Xiao, and Tan (2006) study ex-

dividend day price behaviour in China where dividends can be either taxable or non-

taxable. For the non-taxable sample, they find that stock prices fall by an amount that is

not statistically different from the dividend. For taxable stocks, stock prices of small

dividend yield stocks drop proportionally to the dividend paid, while the price

adjustment for large dividend yield stocks depends on the effective tax rate of dividend

income. The overall findings are consistent with the tax hypothesis.

On the other hand, some studies directly challenge the tax-based interpretations

of ex-dividend day behaviour. For example, Eades, Hess, and Kim (1984) find that

abnormal rates of returns were not confined to taxable distributions. For instance, non-

82

taxable stock dividends and splits were found to offer positive abnormal returns over the

ex-dividend day period. Similarly, Woolridge (1983) and Grinblatt, Masulis, and

Titman (1984) also report positive excess returns on the ex-days of non-taxable stock

distributions. Likewise, Shaw (1991) reports evidence of positive abnormal returns for

the days preceding the ex-day and negative excess returns on the ex-day and for the

following days for non-taxable master limited partnership distributions. They also find

that dividend yield is negatively correlated with the ex-day price movements and

positively correlated with abnormal volume. These results question whether the price

and volume reactions observed around the ex-day are totally tax motivated.

Evidence against the tax-based explanation is not confined to the U.S. For

example, Kadapakkam and Martinez (2005) examine ex-dividend day behaviour in

Mexico where the tax laws are such that a dividend imputation system is in place and

capital gains on stock market transactions are tax free. They find positive abnormal ex-

day return which is inconsistent with the tax-based explanation. In a similar vein,

Daunfeldt (2002) analyzes how changes in the Swedish tax system have influenced

stock prices and trading volume around the ex-dividend day. His findings are

inconsistent with the tax clientele hypothesis. The results are not all together supportive

of the short-term trading hypothesis as they do not confirm the positive association

between abnormal volumes and dividend yields. Weak evidence for tax based

explanations is reported also by Hu and Tseng (2004) who examine order flows around

ex-dividend dates using a unique data set from Taiwan stock exchange where the tax

code allows them to separate the tax hypothesis from other explanations. They report

weak evidence in favour of the tax hypothesis and strong evidence that tax-neutral

83

institutions play the role of short-term arbitrageurs around ex-dividend dates; they buy

before the ex-date and sell afterwards. Milonas and Travlos (2001) also report results

that are at odds with the tax interpretations. They examine the ex-dividend day stock

behaviour in the Athens stock exchange where neither dividends nor capital gains are

taxed. They report a premium less than one which can not be attributed to tax effects.

3.2.2. The Interactions of Taxes, Transaction Costs and Risk

Kalay (1982a) argues that the tax hypothesis has a major flaw because it is

consistent with positive trading profits for various short-term traders. By focusing on

the impact of transaction costs, Kalay shows that, in a world of certainty, investors not

subject to differential taxation of dividends and capital gains, referred to as short-term

traders, will capture dividends and eliminate any excess returns on the ex-dividend

day.34 In this case, ex-day returns, if any, will reflect transaction costs of short-term

traders. Kalay’s argues that ex-dividend day premium is bounded by transaction costs:

⎟⎟⎠

⎞⎜⎜⎝

⎛+≤

−≤⎟⎟

⎠

⎞⎜⎜⎝

⎛−

cum

excum

cum PD

DPP

PD αα 2121 (3.5)

where 2α represents transaction costs of a round trip. The above equation gives the

range, in the presence of transaction costs, in which the ex-day premium can be situated

without profitable arbitrage opportunities arising for any investor. As can be seen, if

transaction costs are zero, the premium would be constrained to unity. The allowable

range of the premium which is consistent with the no profit opportunities is inversely

34 Elton, Gruber, and Rentzler (1984) argue that when Kalay estimated the transaction costs of trading securities, he omitted several important components, including transfer taxes, registration fees, clearance costs, and bid-ask spreads. They claim that when all costs are considered, transaction costs prevent even the lowest costs traders from affecting the ex-dividend day price through short-term trading.

84

proportional to the dividend yield, with the range of variation being narrower when the

dividend yield is greater. Consequently, the presence of transaction costs might result in

the ex-dividend premium deviating from one without the possibility of arbitrage. Koski

(1996, p. 318) succinctly observes, “Short-term traders can eliminate abnormal ex-

dividend returns caused by tax clientele trading only up to the bounds imposed by

transaction costs”.

Another factor that may inhibit arbitrage is the uncertainty about the ex-dividend

day price. In this regard, Heath and Jarrow (1988) demonstrate that when arbitragers are

uncertain whether the change in price from the cum-day to ex-day will be above or

below the dividend, then the equilibrium premium may deviate from one. They argue

that the actual ex-day price drop is unknown and short-term trading around the ex-day is

risky. Michaely and Vila (1996) show that this risk is not trivial. Their analysis implies

that ex-dividend day returns must include a risk premium. Boyd and Jagannathan

(1994) allow for the risk by adding a risk premium to the discount rate when they model

the ex-dividend day return.


There is extensive empirical evidence that is consistent with transaction cost

models. Numerous studies document that the premium is closest to one and abnormal

ex-day volume is highest among high dividend yield and low transaction cost stocks.

This evidence is in line with arbitrage or dividend capture activity. In this regard,

Grundy (1985) investigates both prices and trading volume around ex-days to

distinguish between tax-clientele effects and short-term trading (as cited in Koski and

85

Scruggs (1998, p. 59)). He reports evidence of positive abnormal volume on and around

the ex-day. Similarly, Lakonishok and Vermaelen (1986) find that trading volume

increases significantly around the ex-dividend day. They document that abnormal

volume is highest among high dividend yield stocks and that it increased after the

reduction in transaction costs as measured by commissions. They interpret this as an

evidence of the presence of short-term traders. Grammatikos (1989) confirms the

importance of short-term trading by reporting that the average market-adjusted ex-

dividend day return after the introduction of the U.S. 1984 Tax Reform Act is

significantly lower than before the Act. The increased premium is consistent with the

inability of short-term traders to remove all risk of engaging in dividend trading strategy.

Karpoff and Walking (1988) provide further support for the short-term trading

hypothesis. Using four proxies for transaction costs, they find that excess ex-day returns

are positively related to transaction costs. They also find that this relationship primarily

exists among high yield stocks and after the introduction of negotiated commissions. In

a follow-up paper, Karpoff and Walking (1990) examine the relationship between

trading costs and ex-day behaviour for NASDAQ firms. They document that ex-day

returns increase in transaction costs, as measured by the bid-ask spread. They also find

that this relationship becomes stronger as the dividend yield increases, and is most

significant in high yielding stocks. In a similar vein, Michaely and Vila (1995) report

evidence of positive abnormal trading volume around the ex-dividend day. In a

subsequent study, Michaely and Vila (1996) show that risk and transaction costs reduce

the volume of trades around the ex-dividend date, while heterogeneity in investors’ taxes

86

increase volume.35 Eades, Hess, and Kim (1994) and Naranjo, Nimalendran, and

Ryngaert (2000) also report evidence that dividend capturing is affecting ex-day returns.

Prices adjust to a full ex-dividend drop off in the most liquid, highest yielding stocks,

which are the securities arbitrageurs and dividend capturers are most likely to trade, and

an incomplete drop off is found in stocks that are less likely to be traded. Further

evidence on the presence of short-term traders is provided by Koski and Scruggs (1998)

who analyze the identity of traders around ex-dividend days and find strong evidence of

dividend capture trading by security dealers, some evidence of corporate dividend

capture trading, but little evidence of tax clientele trading.

On the other hand, Poterba and Summers (1986) analyze short-term trading

activity in the U.K. by comparing ex-day returns before and after the introduction of

legislation against dividend capture and provide weak evidence of this activity. Lasfer

(1995b) extends the work of Poterba and Summers (1986) and investigates the relevance

of short-term trading to the U.K. He concludes that “unlike the U.S. market, ex-day

returns in the U.K. are not affected by short-term trading”. In contrast, he shows that

taxation regime in the U.K. does affect ex-dividend day prices. Using Canadian data,

Athanassakos and Fowler (1993) test the short-term trader hypothesis employing a

modified version of the model of delay and acceleration of trade over different tax and

transaction costs regimes from 1970 to 1984. Their findings are consistent with short-

term trading hypothesis where short-term traders transact around ex-dividend days with

35 In a related vein, Admati and Pfleiderer (1988) and Foster and Viswanathan (1990) develop models which predict that trading costs are low when trading volume is high. Foster and Viswanathan (1993) find that for actively traded firms, trading volume is low and adverse selection costs are high on Monday which is consistent with the predictions of the Foster and Viswanathan (1990) model.

87

the intention of capturing or avoiding dividends, subject to the prevailing tax and

transaction cost regime.

3.2.3. Market Microstructure Theories

These theories argue that taxes are not the main driver of ex-dividend day

behaviour. Rather, ex-dividend day behaviour can be explained by market frictions such

as price discreteness and bid-ask bounce. Focusing on price discreteness, Bali and Hite

(1998) argue that if share prices are constrained to trade in discrete ticks while dividend

amounts are continuous, then the ex-dividend premium can not, in most cases, be equal

to the dividend amount. They claim that the market always will round down the value of

the dividend to the tick just below the dividend. Bali and Hite argue that differential

taxation is not necessary to explain why observed ex-day premium are, on average, less

than one. According to them, price discreteness can explain whether premium is less

than one and when positive ex-day returns are observed.

Bali and Hite imply that the greater the tick size, the further from one the

premium will be. This suggests that the tick size is not important in Oman as stock

prices have been decimalized; the tick size is RO 0.01. In fact, Graham et al. (2003) test

the Bali and Hite argument after decimalization and they report evidence that the tick

size is not an important driver of ex-dividend day behaviour. Kadapakkam and Martinez

(2005) also suggest that the tick size effect is not applicable in countries where stock

prices are decimalized.

Another market microstructure model is proposed by Frank and Jagannathan

(1998). In their model, buyers and sellers find dividends to be a nuisance because of

88

their collection and reinvestment and therefore of less value than they are to market

makers. Market makers, for whom collection costs are lower, will buy shares before a

stock goes ex-dividend and resell them after the stock goes ex-dividend. Most of the

trades occur at the bid price before the stock goes ex-dividend and at the ask price on the

ex-dividend day. This results in stock prices rising on average on ex-dividend days quite

independent of the amount of dividend, with the rise being related to the magnitude of

the bid-ask spread. In other words, the bid-ask price movement can lead to premiums

less than one and positive ex-dividend day returns that are positively associated with the

magnitude of the bid-ask spread.36 As described in Graham et al. (2003) and Cloyd, Li,

and Weaver (2004), the Frank and Jagannathan model implies that, if price are measured

at the midpoint of the bid-ask spread, the premium should be one or close to one

compared to when it is measured with closing prices.

Hypothesis 2: we expect the premium to be closer to one when we measure it using the

midpoint of the bid-ask spread. Likewise, we expect the ex-day returns to be closer to

zero when measured using the midpoint of the bid-ask spread.


Using a sample of stocks from NYSE and AMEX, Dubofsky (1992) provides

evidence that ex-dividend day excess returns arise from the mechanics of NYSE Rule

118, AMEX Rule 132, and the fact the prices constrained to discrete tick multiples.

36 Frank and Jagannathan (1998) report evidence consistent with their argument on Hong Kong, where the average premium was approximately one-half during 1980-1993, even though there are no taxes on dividends and capital gains. Kadapakkam (2000) strengthens this argument by documenting that after Hong Kong switched from physical settlement procedures to electronic settlement, which enabled short-term arbitrage trades, ex-day abnormal returns were no longer significantly different from zero.

89

They find that abnormal ex-day returns are induced by rules, which dictate that

specialists lower all outstanding limit buy orders by the dividend. Overall, Dubofsky

(1992) results support the hypothesis that market microstructure affects ex-dividend day

returns.

Jakob and Ma (2004) conduct direct empirical tests of Bali and Hite (1998) and

Dubofsky (1992) models in which market microstructure affect the ex-day price

behaviour. They test these models by examining the ex-day price drop during the one-

eighth, one-sixteenth, and decimal tick size regimes. They report that as discreteness is

eliminated the price drop anomaly actually increases. In addition, they find that for the

most common dividend amounts, the ex-day price drop is just as likely to be the tick

above the dividend as to be the tick below the dividend. This is evidence against the

Bali and Hite (1998) model which predicts that the ex-day price drop will always equal

the tick below the dividend. In a subsequent paper, Jakob and Ma (2006) devise a new

approach to determine whether microstructure or taxes influence ex-dividend day prices

changes. They base their analysis on the techniques employed by Fama and French

(1992) that investigates whether beta or other factors explain the cross-section of

expected stock returns. They find that within a tick multiple, as dividend size increases,

dividends yields increase, but the premium decreases. For dividends that are less than a

tick, they find no relationship between the premium and dividend yield, and for

dividends that are less than half a tick, the premium is higher than one. These results are

qualitatively consistent with Dubofsky’s argument that the limit order mechanism

affects ex-day price behaviour.

90

Further evidence consistent with the limit order market microstructure model is

reported by Jakob and Ma (2005). Jakob and Ma examine the ex-day behaviour for

stocks on the Toronto Stock Exchange (TSX). In contrast to the NYSE, the TSX does

not automatically adjust limit orders on the ex-dividend date. They document that the

lack of an automated TSX limit order adjustment is consistent with the unusually small

ex-day premium in Canada. All of these papers support Dubofsky’s findings that the

limit order adjustment mechanism is affecting the ex-day behaviour.

Graham et al. (2003) also examine the effect of tick size reduction on the ex-

dividend price drop in the US. Similar to Jakob and Ma (2004), they find that the

premium fell as the pricing grid changed from 1/8 to 1/16 to decimals. They interpret

this as evidence against the ex-day premium deviating from one due to price discreteness

and bid-ask bounce. Their results also are inconsistent with an implication of the

transaction cost models. Graham et al. (2003) find evidence consistent with the original

Elton and Gruber tax hypothesis. They find that the ex-day premium fell in conjunction

with the 1997 reduction in capital gain tax rates. They conclude that their results

support the tax-effect explanation.

Cloyd et al. (2004) study the joint effects of prices discreteness and taxation on

ex-dividend day returns using a longer time period than Graham et al. (2003) and Jakob

and Ma (2004). Their findings are in contrast to Graham et al. (2003) and Jakob and Ma

(2004). In particular, they find that decimalization significantly decreased the

relationship between dividend yield and ex-day abnormal returns which is consistent

with microstructure-based arguments that price discreteness is at least partially

responsible for positive ex-day abnormal returns. Moreover, they find that equalization

91

of the Federal statutory tax rates on dividend income and long-term capital gains in May

2003 further reduced the relationship between dividend yield and ex-day abnormal

returns. They interpret this as evidence that is consistent with the tax hypothesis. In

general, their findings indicate that both price discreteness, differential taxation and

transaction costs all play a role in determining ex-dividend day stock price behaviour.

3.3. Oman Stock Market: Institutional Aspects

3.3.1. Trading Rules and Practices

Trading in the MSM was computerized in 1997. MSM is a pure auction market

where trades are facilitated through brokerage firms. It is very different from the NYSE

in that there are no specialists or market makers. Trading in the market is conducted by

stockbrokers, who can not trade on their own account, which means that they have no

role in setting cum- and ex-day prices. Orders are initiated from brokerage firms via

computer terminals in their offices or on the exchange floor. Brokerage firms match buy

and sell orders. Investors intending to buy or sell stocks execute their transactions

through these brokerage firms that charge them a commission or transaction fees. The

minimum fee that can be charged by a brokerage firm is 0.4% and the maximum is

0.75% (0.015% of the fee is revenue for the MSM).

As Oman is a petroleum producing country, taxes play a minor role in generating

income for the economy. As a result, shareholders are not subject to any taxes on

dividends. Likewise, there are no taxes on capital gains. The only taxes are the 12% flat

tax rate on corporate income. This makes Oman taxing system one of the simplest in the

world.

92

During the period of study a number of trading rules and practices were

effective; (1) trades are cleared in three days after the day of transaction, (2) a tick size

of RO 0.01 for all shares traded, (3) short selling of securities is not permitted, and (4)

there are no derivative securities such as options and futures.

3.3.2. Dividends

Firms listed at the MSM distribute dividends in two forms namely, cash

dividends and stock dividends. Paying dividends in one form or another is not

compulsory. If the board of directors proposes to distribute dividends, the details must

be published in the daily newspapers. The proposed dividend is subject to the final

approval of shareholders at the Annual General Meeting (AGM). Generally, most

dividend propositions are accepted at the AGM as the board of directors usually

represents the majority of the share capital. The date when the AGM is held is the

record date. Investors whose names are recorded as stockholders on this date are

entitled to receive the declared dividend. The following date is the ex-dividend date.

Firms usually pay dividends once a year. Some firms complement their cash dividends

with stock dividends.

3.3.3. Data

Our sample consists of the universe of Omani stocks paying cash dividends

between January 1, 1997 and July 31, 2005. All cash and stock dividends and their cum-

dates and ex-dates are obtained from the Muscat Depositary and Registration Company

Database. We have two sources of stock prices data, namely MSM prices and RASP

93

(Research Application Service Provider) database.37 The MSM provided us with the

stock price data, volume data, and the MSM index from 1997 to July 2005. The RASP

database covers Oman for the period 1997 to June 2003. Similar to MSM data, the

RASP database contains daily stock price data, volume data, and the MSM index. In

addition, the RASP database contains intra-daily data for the same period. To maintain

accuracy, the data supplied by the MSM were randomly selected and compared with the

prices provided by RASP; the comparison reveals no difference. As MSM data covers a

longer period, we decide to use the MSM data as the main source of data for this

chapter. However, we also use the intra-daily data from RASP to examine Frank and

Jagannathan market microstructure model.

We restricted attention only to cash dividend payments in this sample period. To

avoid potential confounding effects of other announcements, a concern first raised by

Miller and Scholes (1982), an ex-dividend day is excluded if it coincides with other

corporate events such as stock dividends, splits, or subscription rights. Also, if a

security did not trade on its ex-dividend day, that observation is eliminated from the

sample. The premium is notorious for its extreme values so it is trimmed by excluding

0.5% of the upper and lower values. This filter ensures that our results are robust and

not driven by outliers. The final sample contains 507 cash dividend distributions. The

annual number of observations varies from a low of 50 to a high of 105.

37 The RASP database is supplied by SIRCA (Securities Industry Research Center of the Asia-Pacific). SIRCA is an industry-sponsored financial markets research center consisting of a consortium of Australian universities. SIRCA receives MSM data from Reuters.

94

Table 3.1. Sample Characteristics The sample contains 507 observations for all cash dividend paying firms listed on the MSM during the period from January 1997 to July 2005. The stock price (Pc) denotes the stock price on the cum-day. D denotes the dividend per share.

Statistic Dividend (D, RO) Stock Price (Pcum, RO) Dividend Yield

(D/Pcum) Mean 0.1760 2.7963 0.0735

Median 0.1300 2.2500 0.0615 Standard Deviation 0.1468 1.8681 n/a

Minimum 0.0200 0.3900 0.0129 Maximum 1.0000 11.2100 1.1223

Table 3.1 describes the sample. The average dividend is RO 0.176 and the

average stock price on the cum-day is RO 2.8. The average dividend yield is 7.35%

which is much higher than many countries such as the U.S. (e.g., Lakonishok and

Vermaelen (1986) and Graham et al. (2003)) and Hong Kong (e.g., Frank and

Jagannathan (1998) and Kadapakkam (2000)). This is, however, not surprising since

dividend are not paid annually in these countries.

3.4. Empirical Results

3.4.1. Price Behaviour on Ex-Dividend Day

Table 3.2 presents summary statistics for ex-day premium. We calculate the

premium using close cum-day prices and open ex-day prices. The price adjustment

between the cum- and the ex-day should occur between the cum-day close and the ex-

day open. Measuring the premium using the opening ex-day price rather than ex-day

close can eliminate noise associated with daily price movements. Elton and Gruber

(1970) suggest that opening price is not a market price, but reflects the specialists’

adjusted closing price. While this is not a factor on the MSM, we also provide the

95

premium using closing prices on both cum and ex-dividend days, both adjusted and

unadjusted for MSM market movements. We adjust the closing prices using the same

approach used by Elton et al. (2005) and Jakob and Ma (2006). The market adjustment

is designed to compensate for returns during the ex-dividend day.

In all three cases, we test the null hypothesis that the premium is equal to one

(Hypothesis 1). The results show that in all cases the premium is significantly less than

one. This implies that the average decline in the stock price on the ex-dividend day is

less than the dividend per share. The average decline in stock price on the ex-dividend

day ranges from 0.65 to 0.69. This evidence is consistent with previous findings by

Frank and Jagannathan (1998) on Hong Kong which has similar tax treatment for

dividends and capital gains as in Oman and Milonas and Travlos (2001) on the Athens

Stock Exchange where taxes on dividends and capital gains are also absent.

Table 3.2. Premium Summary Statistics The sample consists of 507 observations for all cash dividend paying firms listed on the MSM during the period from January 1997 to July 2005. The premium is defined as (Pcum - Pex )/ D. T-statistics are for the null hypothesis that the mean premium is equal to one. Adjusted premium uses the MSM index.

Unadjusted Adjusted Statistic Close-Open Close-Close Close-Close Mean 0.6460 0.6919 0.6628

T-statistic -4.8474 -4.1668 -4.5426 Median 0.2500 0.4000 0.3917

Minimum -5.1667 -5.1667 -5.0428 Maximum 13.7000 13.7000 13.7403

3.4.2. Abnormal Returns on Ex-Dividend Day

Although premium measures are intuitively appealing, they suffer from

heteroscedasticity (See Eades et al. (1984), Lakonishok and Vermaelen (1986), Barclay

96

(1987), and Michaely (1991)).38 The heteroscedasticity problem is caused by the fact

that price changes are divided by dividend amounts which are not equal across

securities.39 Our second measure of ex-day price change, AR, avoids this problem. The

ex-day raw return is (Pex – Pcum + D)/Pcum such that, if the price drops equal D, then the

raw return is zero. Following Graham et al. (2003), Liano et al. (2003), and Cloyd et al.

(2004), we calculate the ex-day abnormal return (AR) as

AR = ),(,

,,it

itcum

ititcumitex REP

DPP−

+− (3.6)

where E(Rit) is the expected return for firm i on event day t, as calculated from the

market model:

).)(()( ftmtititit RRERE −+= βα (3.7)

where E(Rmt) is the expected return on the market at time t and Rft is the risk-free rate of

return at time t. We use the MSM value-weighted return as a proxy for the market

return and one-month rate of Treasury bills as a proxy for the risk-free rate.40 We

estimate the parameters for the market models using daily returns from -240 through -41

relative to the ex-dividend day.

Table 3.3 presents the results for abnormal returns on the ex-dividend day. We

are testing the null hypothesis that the abnormal return on the ex-dividend day is zero.

Our results show that the mean abnormal returns are significantly greater than zero. In

particular, we find that the average abnormal return on the ex-day is 4.45% which is

38 A complete discussion of the problems caused by heteroscedasticity in the price change to dividend ratio is contained in Michaely (1991). 39 Clustering is not an important issue for our sample as there are very limited cases where firms go ex-dividend on the same calendar date. 40 The risk-free rate of return is obtained from the Central Bank of Oman.

97

highly significant with a t-statistic of 7.50. The median abnormal return is 3.43%.

These abnormal returns are substantially higher than those reported by Graham et al.

(2003) for the U.S. and by Lasfer and Zenonos (2003) for France, Italy, Germany, and

U.K. However, this is not surprising since dividend yields are much lower in these

countries. In general, these results are similar to those reported by Eades et al. (1984),

and Grinblatt, Masulis, and Titman (1984) who document abnormal return behaviour

around ex-days of non-taxable distributions such as stock splits and stock dividends.

Table 3.3. Ex-Day Abnormal Returns Summary Statistics The sample includes 507 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to July 2005. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + D)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that the mean abnormal return is equal to zero. Statistic Ex-Day Abnormal Return Mean 0.0445 T-statistic 7.5008 Median 0.0343 Minimum -0.4420 Maximum 1.1208

As a robustness check and to test the sensitivity of our results to beta estimation,

we calculate abnormal return, ARit, by subtracting the market’s (MSM) daily return, Rmt,

from the observed stock’s return over a given period t. That is,

mtitit RRAR −= (3.8)

Under this technique, stocks are assumed to have a beta of 1.0.

Our result from employing this approach is very similar to those reported previously. In

particular, we find that the ex-day abnormal return is 0.0482 with a t-statistic of 7.2751.

98

A possible explanation behind the positive abnormal returns (and premium less

than one) may be market frictions. However, the tick size effect proposed by Bali and

Hite (1998) is not applicable, since stock prices are decimalized in Oman. However, we

examine whether the bid-ask bounce drives our results in a section below.

3.4.3. Transaction Costs and Risk

Since abnormal returns are not eliminated, the implication is that arbitrage may

be inhibited by transaction costs and risk. To examine this issue, we run the following

regression model:

AR = iMiiCUMii ePDVYLD ++++ σσββββ ε //1 3210 (3.9)

Where,

ARi: is the abnormal return as estimated in equation (3.6),

DVYLDi: the dividend yield for stock i,

1/PCUMi: the inverse of stock i’s closing price on the last cum dividend day as a proxy for

transaction costs,

Mii σσε / : the standard deviation of the residuals from estimating equation (3.7),

normalized by market risk (a proxy for idiosyncratic risk).

Kalay (1982a) argues that stock prices should drop by the full amount of the

dividend. Otherwise, short-term traders, who face no differential taxes on dividends

versus capital gains, could make excess returns. On the other hand, transaction costs

could inhibit the ability of short-term traders to make arbitrage profits. Higher

transaction costs should act like a barrier against short-term trading in the period around

the ex-dividend day, and thereby reduce the volume of trading and the ex-dividend day

99

premium. To capture this affect, we follow previous research (e.g., Karpoff and

Walking (1988), Naranjo et al. (2000), and Cloyd et al. (2004)) and include the inverse

of the closing stock price on the last cum-dividend day (1/Pcum) as a proxy for

transaction costs. Previous studies report evidence of a positive association between ex-

day abnormal returns and transaction costs which is usually interpreted as evidence of

dividend capture. This is because transaction costs prevent ex-day abnormal return

being arbitraged away (Kalay (1982a)). Karpoff and Walking (1988, 1990) argue that

ex-day abnormal returns are eliminated up to the marginal cost of trading around the ex-

day, which implies a positive association between ex-day returns and transaction costs.

Therefore, if dividend capture trading occurs, the resulting ex-day returns will be

positively correlated with the cost of trading. Consequently, we expect a positive

association between abnormal returns and the transaction costs proxy (Lakonishok and

Vermaelen (1986), Karpoff and Walking (1988, 1990), Michaely et al. (1996), and

Naranjo et al. (2000)).

Another factor potentially limiting dividend capture is risk. Heath and Jarrow

(1988) demonstrate that the ex-dividend day stock price may differ arbitrarily from the

dividend for each individual stock: consequently, short-term traders can not generate

riskless arbitrage profits. As a result, ex-dividend returns must include a risk premium

because ex-day share prices are unknown (see also Michaely and Vila (1996)).

Grammatikos (1989) and Boyd and Jagannathan (1994) argue that risk exposure is a

major cost faced by short-term traders. Empirical evidence supporting the existence of

such risk premia is provided by Grammatikos (1989) in his study of the effects of the

Tax Reform Act of 1984. Fedenia and Grammatikos (1993) also report evidence

100

consistent with the risk premium. To capture this affect, we use a risk measure similar

to that used by Michaely and Vila (1996) and Cloyd et al. (2004). We measure Mii σσε /

as the standard deviation of the residuals from a market model regression of daily

returns for the dividend paying stocks on daily market returns, divided by the standard

deviation of daily market returns. Since a short-term trader has to be compensated for

taking extra risk, we expect a positive relationship between the ex-day abnormal returns

and our risk proxy.

Table 3.4 reports the results on the relationship between ex-day abnormal returns

and transaction costs and risk. Following previous research (Kadapakkam (2000)), we

include dividend yield as a control variable.

Table 3.4. The Effect of Dividend Yield, Transaction Costs, and Risk on Ex-Day Abnormal Returns The regression results are based on 507 observations for all cash dividend paying firms listed on the MSM during the period from January 1997 to July 2005. The dependent variable is the ex-day abnormal return. The explanatory variables are the stock’s dividend yield (measured as the dividend per share over the cum-day price), transaction costs measured as the inverse of the cum-day price, and stock’s variance relative to market variance (σεi/σMi). T-statistics are heteroscedastic consistent (White (1980)). Statistic Coefficients T- statistics Intercept 0.0352 1.9745 DVYLD -0.1301 -3.0314 1/Pc -0.0386 -1.4814 σεi/σMi 0.0015 0.5534 Adjusted R2 0.0695

Contrary to our expectations, there is no significant relationship between

transaction costs and abnormal returns indicating that transaction costs do not prevent

arbitrage activity. Our risk proxy is also insignificant suggesting that risk considerations

do not deter arbitrage activity. The fact that the transaction cost and risk proxies are

101

insignificant suggests that a high level of ex-day transaction costs and trading risks do

not prevent short-term traders from arbitraging away the ex-day abnormal returns and a

full adjustment of stock price to the amount of dividends, which is inconsistent with

Kalay (1982a) and Michaely and Vila (1995). The significant negative coefficient on

dividend yield suggests that short-term traders are eliminating or reducing abnormal

returns in high dividend yield stocks.

3.4.4. Behaviour of Trading Volume around Ex-Days

To investigate the presence of short-term trading around the ex-dividend day, we

analyze volume data. Lakonishok and Vermaelen (1986) argue that the influence of

short-term traders around the ex-day can best be investigated by examining abnormal

volume around the ex-day. The presence of short-term traders would be shown through

positive abnormal volume around the ex-day. Green’s (1980) analysis suggests that this

abnormal trading volume will be highest on the cum-day and ex-day. There are many

studies that report abnormal trading volume around ex-days. For the U.S., Lakonishok

and Vermaelen (1986) find positive abnormal volume around the ex-day for taxable

securities which supports the presence of short-term traders for those securities.

However, they document negative abnormal volume for nontaxable stock splits and

stock dividends. Grundy (1985), Michaely and Vila (1995, 1996), and Michaely et al.

(1996) also report abnormal trading volume around ex-days. Further evidence of short-

term trading around ex-days is reported by Michaely and Murgia (1995) for Italy, Kato

and Loewenstein (1995) for Japan, and Green and Rydqvist (1999) for Sweden.

102

We examine abnormal trading volume over the 11-day period centered on the ex-

day. In doing so, we follow the methodology of Graham et al. (2003) where turnover is

computed as the aggregate number of shares traded on a given day divided by the

number of outstanding shares. We estimate normal turnover as the average daily

turnover for the 80 days from day -45 to day -6 and day 6 to day 45 relative to the ex-

dividend day. Abnormal trading volume (ATV) for each day in the event window is

defined as the ratio of a stock’s trading turnover on a particular day to that stock normal

trading turnover, minus one.

Table 3.5 presents evidence on trading volume around ex-dates. Significant

positive abnormal volume around the ex-day will be clear evidence of presence of short-

term trading activities.

Table 3.5. Daily Abnormal Trading Volume The sample contains 495 observations for all cash dividend paying firms listed on the MSM during the period from January 1997 to July 2005. Abnormal trading volume is presented for a 11-day window centered on the ex-day. Abnormal trading volume for each day in the event window is defined as the ratio of a stock’s trading turnover on a particular day to that stock normal trading turnover, minus one. Turnover is computed as the aggregate number of shares traded on a given day divided by the number of outstanding shares. Normal turnover is estimated as the average daily turnover for the 80 days from day -45 to day -6 and day 6 to day 45 relative to the ex-dividend day. Event Day ATV Standard Error

-5 -0.0291* 0.0145 -4 -0.0336* 0.0090 -3 -0.0272 0.0147 -2 -0.0347* 0.0099 -1 -0.0383* 0.0142 0 -0.0821* 0.0049 1 -0.0618* 0.0076 2 -0.0612* 0.0060 3 -0.0614* 0.0056 4 -0.0528* 0.0092 5 -0.0550* 0.0064

*denotes significance at the 5% level using a two-tailed test.

103

The results indicate that the abnormal volume prior to the ex-day is uniformly

negative. That is, on each of the five days prior to the ex-day, trading volume decreases

substantially. In most cases, the reduction in volume is significantly different from zero.

There is also a significant drop in trading volume on the ex-day and on each of the

following five days. These results are inconsistent with the hypothesis that short-term

traders have a significant impact on ex-day behaviour. Rather, it is consistent with the

market microstructure model by Frank and Jagannathan (1998) which predicts negative

abnormal volume around the ex-days due to a shortage of buyers in the cum-period and

a shortage of sellers in the ex-period (Cloyd, Li, and Weaver (2002)). These results are

very similar to those reported by Lakonishok and Vermaelen (1986) for stock splits and

stock dividends. They are also consistent with the findings of Copeland (1979), who

studied trading volume behaviour of 25 NYSE firms around stock splits during the

period 1963-1973. He reports evidence that trading volume decreased in anticipation of

the stock split and continued to be lower following the split. In general, unlike the U.S.

markets where short-term traders affect ex-day prices (e.g., Lakonishok and Vermaelen

(1986), Karpoff and Walking (1990), and Michaely (1991)), our volume results do not

provide support for the short-term trading hypothesis.

3.4.5. Midpoint Pricing Using RASP Data

Until now we have been using MSM daily closing prices to conduct our analysis

using the standard methodology in prior research. In this section, we repeat our analysis

and calculate the ex-day premium and ex-day abnormal return utilizing the RASP intra-

daily data to test the market microstructure argument proposed by Frank and

104

Jagannathan (1998). Frank and Jagannathan (1998) argue that the premium, to a large

extent, is an artifact of bid-ask spread. Their model implies that if prices are measured

at the midpoint of the bid-ask spread, the premium should be one, or at least closer to

one compared to when closing daily prices are used. Similarly, the ex-day abnormal

return should be zero or closer to zero when measured using the midpoint of the bid-ask

quotes relative to when measured by transaction prices (Hypothesis 2). As discussed in

Graham et al. (2003), these hypotheses can not be tested using daily closing prices

because bid-ask bounce may cause a bias in the ex-day premium and abnormal returns.

In order to see if our previous results hold when using the RASP data, we first

use the RASP closing transaction prices and recompute the ex-day premium and

abnormal returns.

Table 3.6. Premium and Ex-Day Abnormal Return (AR) Using RASP Closing Transaction Prices. The sample contains 382 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The premium is defined as (Pcum - Pex )/ D. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + Div)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that (1) the mean premium is equal to one and (2) the mean ex-day abnormal return is equal to zero. The Pcum and Pex are calculated using RASP closing transaction prices. Statistic Premium AR Mean 0.6532 0.0422 T-statistic -3.1659 6.9010

Our results reported in Table 3.6 show that there is almost no difference with the

MSM analysis reported in Table 3.2 and 3.3. For instance, we find the mean ex-day

premium is 0.65 and the mean ex-day abnormal return is 0.04. These results are almost

identical to those reported in Table 3.2 and 3.3. Next, we follow the methodology of

105

Graham et al. (2003) and measure Pex and Pcum at the close of the trading day using the

midpoint of the bid and ask quotes (rather than transaction prices).41 As explained in

Graham et al. (2003), the use of the midpoint prices should attenuate bid-ask bounce that

might impact traditional ex-day analysis and allow us to test Frank and Jagannathan bid-

ask bounce hypothesis. If bid-ask bounce is the primary cause of the ex-day behaviour,

we should find that the ex-day premium is closer to one and ex-day abnormal return is

closer to zero when we use the midpoint prices (Hypothesis 2). This is exactly what we

find.

Table 3.7. Premium and Ex-Day Abnormal Return (AR) Using RASP Closing Quote Midpoints The sample includes 382 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The premium is defined as (Pcum - Pex )/ D. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + Div)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that (1) the mean premium is equal to one and (2) the mean ex-day abnormal return is equal to zero. The Pcum is calculated using the midpoint of bid-ask spread of the closing quote on the cum-day. Pex is calculated using the midpoint of the bid-ask spread of the closing quote on the ex-day. Statistic Premium AR Mean 0.9816 0.0001 T-statistic -0.1211 1.3909

In particular, Table 3.7 indicates that the premium is slightly less than one and

the abnormal return is slightly greater than zero, but as expected the differences are not

statistically different from one and zero at any reasonable level of significance. These

results are very different to those reported in Table 3.2 and 3.3 based on closing daily

stock prices. Consequently, using midpoint prices to eliminate bid-ask bounce makes a

41 For more information on the methodology, see Graham et al. (2003).

106

huge difference compared to using transaction pricing. This clearly indicates that bid-

ask bounce in transaction prices is an important driver of ex-day pricing in our sample.

This finding support the prediction that the premium being different from one is due to

bid-ask bounce, and the ex-day abnormal return being different from zero for the same

reason.

Eades et al. (1994) and Boyd and Jagannathan (1994) point out that price

noisiness is a major obstacle in the examination of ex-dividend day behaviour. Graham

et al. (2003) suggest that the use of closing prices in the examination of ex-dividend day

behaviour is adding noise to the ex-day analysis which makes it hard to make accurate

inferences. To avoid this problem, we repeat our analysis using the opening quotes on

the ex-dividend day. The use of opening quotes should eliminate noise associated with

daily price movements (Graham et al. (2003)).

Table 3.8. Premium and Ex-Day Abnormal Return (AR) Using RASP Opening Quote Midpoints The sample consists of 382 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The premium is defined as (Pcum - Pex )/ D. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + Div)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that (1) the mean premium is equal to one and (2) the mean ex-day abnormal return is equal to zero. The Pcum is calculated using the midpoint of bid-ask spread of the closing quote on the cum-day. Pex is calculated using the midpoint of the bid-ask spread of the opening quote on the ex-day. Statistic Premium AR Mean 1.0238 0.0001 T-statistic 0.1504 1.1528

We find that the premium is very close to and not statistically significantly

different from one (Table 3.8). The abnormal return is very close to zero and the

107

difference from zero is not statistically significant. These results are almost identical to

the one reported using the closing prices on the ex-day. This indicates that the noise of

using the closing prices is not an important driver for our results.

Another implication of Frank and Jagannathan model is that bid-to-bid and ask-

to-ask prices should drop by the amount of dividend in the absence of taxes and discrete

tick size effects. We repeat our analysis using bid-to-bid and ask-to-ask quotes.

We find that stock prices fall by almost the exact amount of the dividend using

these prices (Table 3.9). These results are evidence that systematic bid-ask bounce

around ex-dividend days bias closing transaction prices for this sample. The results

from cum-day close ask to ex-day close ask is slightly smaller than the average drop

from cum-day bid to ex-day close bid. Most importantly, in both cases, we can not

reject the null hypothesis that ex-day premium is equal to one and ex-day abnormal

returns are equal to zero.

Table 3.9. Premium and Ex-Day Abnormal Return (AR) Using RASP Closing Bid and Ask Quotes The sample includes 382 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The premium is defined as (Pcum - Pex )/ D. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + Div)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that (1) the mean premium is equal to one and (2) the mean ex-day abnormal return is equal to zero. The Pcum is calculated using (1) bid quote of the closing quote on the cum-day and (2) the ask quote of the closing quote on the cum-day. Pex is calculated using the (1) bid quote of the closing quote on the ex-day and the (2) ask quote of the closing quote on the ex-day.

Statistic Premium bid Premium ask AR bid AR ask Mean 0.9916 0.9716 0.0001 0.0001 T-statistic -0.0381 -0.1015 1.1654 1.0994

108

To avoid the noise of using closing prices on the ex-day, we also repeat our

previous analysis using the opening quotes. We present the results in Table 3.10.

Table 3.10. Premium and Ex-Day Abnormal Return (AR) Using RASP Opening Bid and Ask Quotes The sample consists of 382 observations for all dividend cash paying firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The premium is defined as (Pcum - Pex )/ D. The Ex-Day Abnormal Return is defined as ((Pex – Pcum + Div)/Pcum) – ER, where ER is the expected return defined by the Market Model. T-statistic is for the null hypothesis that (1) the mean premium is equal to one and (2) the mean ex-day abnormal return is equal to zero. The Pcum is calculated using (1) bid quote of the closing quote on the cum-day and (2) the ask quote of the closing quote on the cum-day. Pex is calculated using the (1) bid quote of the opening quote on the ex-day and the (2) ask quote of the opening quote on the ex-day. Statistic Premium bid Premium ask AR bid AR ask Mean 1.0343 1.0133 0.0001 0.0001 T-statistic 0.1491 0.0456 0.9666 0.9076

We find that the premium is very close to one whether we use the bid price or the

ask price. The abnormal return also is very close to zero. In both cases, the ex-day

premiums are not statistically different from one and the abnormal returns are not

statistically different from zero. In general, the results using the midpoint quotes show

that the inferences based on premium are very similar to those based on returns, and

results for bid quotes are virtually identical to those for ask quotes. Overall, inferences

based on quotations are different from those based on transaction prices.

In summary, the above results indicate that market microstructure explanations

are the dominant cause of the ex-day premium deviating from one and the ex-day

abnormal returns deviating from zero. Once these market microstructure effects are

109

taken into account, at the margin, a Rial of dividends and a Rial of capital gains are

valued equally in Oman.

3.4.6. Volume Analysis Using RASP Data

In order to see if our previous results hold when using the RASP data, we repeat

our previous volume analysis using the RASP data. The results are reported in Table

3.11.

Table 3.11. Daily Abnormal Trading Volume Using RASP Data The sample includes 364 observations for all cash dividend paying firms listed on the MSM during the period from January 1997 to June 2003. Abnormal trading volume is presented for a 11-day window centered on the ex-day. Abnormal trading volume for each day in the event window is defined as the ratio of a stock’s trading turnover on a particular day to that stock normal trading turnover, minus one. Turnover is computed as the aggregate number of shares traded on a given day divided by the number of outstanding shares. Normal turnover is estimated as the average daily turnover for the 80 days from day -45 to day -6 and day 6 to day 45 relative to the ex-dividend day. Event Day ATV Standard Error -5 -0.0163 0.0163 -4 -0.0333* 0.0095 -3 -0.0207 0.0173 -2 -0.0267* 0.0101 -1 -0.0474* 0.0156 0 -0.0827* 0.0052 1 -0.0636* 0.0083 2 -0.0620* 0.0070 3 -0.0590* 0.0066 4 -0.0514* 0.0089 5 -0.0532* 0.0064

*denotes significance at the 5% level using a two-tailed test.

Similar to our previous findings using the MSM data, our results show that the

abnormal volume is generally negative around the ex-dividend days. Volume is below

normal on each of the five days prior to the ex-day. There is also a reduction in volume

110

on the ex-day and on each of the following five days. In most cases, the drop in volume

is statistically significantly different from zero. These results are practically identical to

those reported using the MSM data (see Table 3.5). This is evidence against the short

term trading hypothesis which predicts a positive abnormal volume around ex-dividend

days. Our failure to find positive abnormal volume is not surprising. If there are no

arbitrage opportunities (i.e., the price drop equals the dividend) then no arbitrage trading

will be observed.

3.5. Conclusion

In this chapter, we examine ex-dividend day behaviour in a unique setting which

is characterized by less frictional trading, i.e., no taxes on dividend and capital gains,

dividends are paid annually, and prices are decimalized. While one would expect that in

this market stock prices should drop by an amount equal to the dividend, our evidence

shows that stock prices drop by less than the amount of dividends when we construct the

test using standard daily returns. Similarly, we find significant positive abnormal

returns on the ex-day. These results can not be explained by taxes and price

discreteness.

We examine whether transaction costs and risk inhibit arbitrage trading around

ex-days. We find neither of these variables is significant, which suggests that these

variables do not hinder investors’ ability to trade and arbitrage any excess returns. We

also examine abnormal trading volume around the ex-days. Our results reveal that there

is a significant reduction in trading volume around ex-days. The reported results show

that, unlike the U.S. market, ex-day behaviour in Oman is not affected by the short-term

111

trading. Finally, we test the Frank and Jagannathan (1998) model which predicts that

bid-ask bounce is the primary factor behind the ex-dividend day behaviour. Our results

indicate that when midpoint prices are used instead of transaction prices, stocks prices

drop by the full amount of dividends on the ex-day and the ex-day abnormal return is

insignificantly different from zero. Our analysis of bid-to-bid and ask-to-ask prices

reveals similar results.

In sum, the results indicate that market microstructure strongly influence the ex-

dividend day premium and ex-day return. Once market microstructure effects are taken

into account, dividends and capital gains are valued equally at the margin.

112

Chapter 4: The Information Content of Cash Dividend Announcements

in a Unique Environment

4.1. Introduction

Numerous studies have documented that announcements of changes in dividends

convey specific information to the market (Pettit (1972), Charest (1978), Aharony and

Swary (1980), Woolridge (1982), Aharony, Falk, and Swary (1988), Ghosh and

Woolridge (1988, 1991), Lang and Litzenberger (1989), John and Lang (1991), Marsh

(1993), Abeyratna, Lonie, Power, and Sinclair (1996), Firth (1996), Nissim and Zin

(2001), Hanlon, Myers, and Shevlin (2006), among others). The majority of these

studies are conducted using U.S. data. One natural question is whether these dividend

effects are peculiar to the U.S. or they are also prominent in countries where the tax

regime and/or institutional and economical characteristics are significantly different.

The purpose of this chapter is to investigate the stock price reaction to the

announcement of cash dividends of the Muscat Securities Market listed companies to

identify whether or not dividends contain information. There are several important

economic and institutional features that make Oman a unique and interesting

environment to examine the market reaction to cash dividend announcements.

First, Oman has a unique tax system that allows us to examine the tax-based

signaling hypothesis related to Black’s (1976) dividend puzzle. He raised the question

of why companies pay dividends, despite the fact that they are taxed at higher rates than

113

capital gains.42 Tax-based signaling models provide an answer to this question. The

higher tax on dividends relative to capital gains makes dividends informative about the

companies’ future prospects and cash flow (Bhattcharya (1979) and John and Williams

(1985)).43 These models argue that dividends would not have information and be

informative if it is not for the higher taxes on dividends relative to capital gains that they

apply to shareholders (Amihud and Murgia (1997)). In Oman, there are no taxes on

dividends and capital gains. Under this scenario, tax-based signaling models predict that

dividends are not informative or at least have less information. If we find that the stock

price reacts to cash dividend announcements, then this suggests that the higher taxation

on dividends relative to capital gains is not a necessary condition for them to have

information and be informative. It would also suggest that there are other factors,

beyond higher taxation, that makes dividends informative.

Second, Omani companies rely heavily on bank financing. If bank monitoring is

effective, then dividend payments may not be necessary to reduce mangers’ tendency to

overinvest free cash flow. This should reduce the announcement effects of dividend on

stock prices. Moreover, Omani companies are owned by a small number of investors

who have controlling interests. This concentration of ownership structure should reduce

the agency cost between managers and shareholders. If the concentration of ownership

leads to less information asymmetry between managers and shareholders, dividend

42 Fama and French (2001) document that the number of firms paying dividends has dramatically declined from 66.5% in 1978 to 20.8% in 1999. They also find a surge in share repurchases. Similarly, Grullon and Michaely (2002) report that over the last 20 years or so share repurchase activity (relative to total earnings) has experienced a significant growth which increased from 4.8% in 1980 to 41.8% in 2000. 43 There are also other signaling models, i.e., the information content for future earnings/cash flows. These models argue that managers are portrayed as intentionally communicating their expectations of future firm earnings and cash flows via dividend changes. We present the studies that test these models in Section 4.2.2.

114

announcements should have a smaller pricing effects compared to countries where

companies are owned by a diverse group of investors. Both of these arguments, together

with the absence of taxes on dividends and capital gains, suggest that dividends do not

act as a signal of information or as a disciplinary mechanism or at least suggest a

diminished role for dividends in Oman.

Third, transparency in Oman is low and corporate disclosure requirements are

loose (Islam (2002)). There is a scarcity of professional financial analysts and there are

no management forecasts provided. Investors have few other sources of information on

Omani companies which makes cash dividend announcements an important piece of

information that can assist investors in pricing Omani shares. The above analysis

implies that dividends may contain information as they can be an important source of

information that allows market participants to evaluate management expectations and

confidence as to the future performance and prospects of the firm. It is an empirical

issue as to how the Omani market balances the negative pricing effect of non-taxability

of dividends, bank leverage, and ownership concentration, and the positive pricing effect

of low transparency on dividends.

Furthermore, a feature of Omani listed firms is the variability in cash dividend

payments. As we will show later, the majority of Omani firms change their dividends

almost every year. This contrasts with the practices observed in the U.S. and other

developed countries where most stocks experience relatively few changes in their

dividends. In fact, Aharony and Swary (1980) find that about 87% of all firms had no

change in quarterly dividend payments in the U.S. In the samples of Eades et al. (1985),

and Bajaj and Vijh (1990), more than 80% of announcements involve no change in

115

dividends. More recently, Hallock and Mashayekhi (2003) find that 80% of firms do not

change their dividends in the U.S. during the period 1970-2000. When a dividend

increase is made, the evidence suggests that managers are reluctant to return to previous

levels of dividends, because dividend decrease announcements result in significant share

price declines.

Just as in the U.S., our evidence shows that the market reacts strongly to

announcements of changes in cash dividends. Investors do care about the information

transmitted by dividend announcements. Firms that increase (decrease) their dividends

are associated with an increase (decrease) in stock prices. Firms that have no change in

their dividends experience insignificant negative average abnormal returns, consistent

with no change in dividends being, on average, a disappointment. These findings

support the view that dividends convey unique and valuable information to investors.

These results are in sharp contrast to the tax-based signaling models which argue that tax

differences are a necessary condition for dividends to have information and be

informative about a firm’s future prospects and cash flows.

We also use trade and quote prices to examine the effects of market

microstructure during dividend announcements. In particular, we investigate whether

the observed returns are affected by bid-ask bounce. Our results show that the bid-ask

bounce does not affect our results.

The remainder of the chapter is organized as follows. Section 4.2 discusses the

relevant theories and empirical literature for this study. Section 4.3 describes the

specific data sources used in this chapter, and describes our data sample. Section 4.4

describes the methodology employed in the chapter and Section 4.5 presents empirical

116

results. Section 4.6 examines whether bid-ask bounce affect our results and Section 4.7

concludes the chapter.

4.2. Theoretical and Empirical Studies

It is well established that the market does react to dividend announcements

which implies that dividends contain information. The capital markets react favorably to

“good news” announcements (dividend increases) and adversely to “bad news”

announcements (dividend decreases). The implication is that dividend increases

represent positive information about the company’s prospects and thus are associated

with an increase in stock prices. Conversely, a dividend decrease is a negative signal

about the company’s future prospects which results in a reduction in stock prices. The

most frequently cited explanation for the above empirical regularity is the information

content of dividends or the signaling hypothesis. This hypothesis states that the firm

uses dividends as a signaling device to convey valuable information to the market. We

next go into these issues in more detail.

4.2.1. Theoretical Studies

The signaling or the information content of dividend hypothesis postulates that a

firm’s management often possesses inside information about the firm’s future prospects

and communicates this to outsiders by changing dividends. The difference between the

actual dividends declared and expected by the market is a signal to investors which they

use to reassess their estimates of a stock’s value. These models predict that dividend

announcements convey information about a firm’s current performance or/and its future

117

prospects. Accordingly, a dividend increase should be perceived by investors as a

positive signal regarding future prospects of the firm, whereas a dividend decrease

should be perceived as a negative signal.

The concept of signaling was introduced into the financial literature by Ross

(1977). He posits a formalized theory to explain how the market response to a dividend

announcement may provide the occasion for share revaluation. Under the Ross scenario,

investors interpret signals from management and adjust the value of the firm

accordingly. In addition, through a disciplinary mechanism that holds management

accountable for its actions, the market is capable of discerning whether such signals are

valid. In this model, Ross relaxes the full information assumption and allows an

information asymmetry between managers and outsiders. Under Ross’s signaling

model, there is an incentive for managers to issue the correct signal regarding firm type

when establishing the firm’s dividend policy. He shows how managers will choose to

establish unambiguous signals about the firm’s future if they have the proper incentives

so that managers whose firms have inferior prospects will not have an incentive to signal

falsely.

Bhattacharya (1979) develops a theoretical model of dividend signaling which is

similar in many aspects to the Ross (1977) model, particularly in the signaling cost

structure. In this model, dividends are a costly mean of removing information

asymmetries in the market concerning a firm’s true value. Signaling costs are a function

of the differential tax treatment of dividends versus capital gains and the financing costs

of raising unexpected funds to fulfill dividend obligations. In Bhattacharya’s model,

taxes are an important factor in determining their signaling effect. Dividends have

118

information and are informative due to the higher tax rates on dividend relative to capital

gains.

Kalay (1982b) provides evidence consistent with the Ross model for

announcements relating to dividend policy. He derives the hypothesis that the size of

the signal value would vary positively with the firm’s true value and vary negatively

with the risk of firm value. Kalay (1982b) argues that managerial reluctance to decrease

dividends is a necessary condition for the existence of the signaling equilibrium in which

dividends are used as a signaling device. His findings from the examination of dividend

reductions are consistent with his signaling model.

Eades (1982) develops the so called “Relative Signaling Strength” by combining

the Ross financial signaling model with Bhattcharya’s dividend signaling model. This

model specifies that, ceteris paribus, for a given dividend change, firms with high risk

will display stronger changes in firm value compared to firms with low risk.

Additional theoretical developments are provided by John and Williams (1985)

and Miller and Rock (1985) who provide a more complete explanation for market

responses to announced dividend changes. The main assumption of these models is that

there is an asymmetry in information between insiders (management and directors) and

outside shareholders. Asymmetric information leads to dividend announcement effects

where stock price increases result from investors’ realization that insiders have superior

information on the firm.

The John and Williams (1985) model is similar to Bhattacharya with respect to

the cost of signaling as both models utilize a tax penalty on dividends relative to capital

gains as the primary cost of signaling. In both models, dividends are informative

119

because of the higher taxes on dividends relative to capital gains. In addition to the

personal tax rates, John and Williams (1985) also demonstrate that stock price reactions

to announced dividend changes are a function of the demand for liquidity and corporate

cash and investment. They explain why it may be optimal for a firm to pay cash and

raise new equity in the same planning period. Firms pay dividends to reduce the

underpricing of the securities issued to raise new outside financing.

Miller and Rock (1985) show through the sources and uses of funds that dividend

decisions can reveal information about current earnings. Their signaling approach

suggests that as a result of information asymmetry between investors and managers,

dividend changes can result in market price reactions to these dividend announcement

changes. They show theoretically that under certain conditions dividends and earnings

announcements can serve as perfect substitutes for each other. Their model implies that

larger (smaller) dividends are associated with larger (smaller) price increases after the

announcements. Bar-Yosef and Huffman (1986) employ a reward penalty managerial

incentive scheme to provide rationality in corporate dividend decision behaviour. They

observe a trend that the higher the level of expected cash flow, the lower the managerial

effects of cash flow on dividends. In a more recent study, Bar-Yosef and Sarig (1992)

employ a new approach to identify dividend surprises. They report evidence that the

unexpected dividend payments bring about a statistically significant market reaction.

Their results indicate that dividends have information content even for closely monitored

large corporations.

120

4.2.2. Empirical Literature

There are numerous studies that examine the stock price reaction to dividend

announcements. These studies generally report that stock prices follow the same

direction as the dividend change announcements. Dividend increases and dividend

initiations (decreases and omissions) are associated with significant increases

(decreases) in stock prices.

Fama, Fisher, Jensen, and Roll (1969) document that firms announcing stock

splits accompanied by increases in cash dividends have a statistically significant positive

average risk-adjusted stock return during the announcement months. On the other hand,

firms announcing stock splits accompanied by dividend reductions realize a significant

negative return. An early extensive empirical study that attempted testing the

information content of dividend announcements is Watts (1973). His analysis suggests

that dividends convey little if any information about stock valuations, once current

earnings are controlled for in the experiment. Gonedes (1978) has similar results. In

particular, Gonedes (1978) provides evidence that is uniformly inconsistent with the

view that annual dividend signals reflect information beyond that reflected in

contemporaneous annual income signals. As a result, he rejects the dividend

information content hypothesis. Conversely, Kane, Lee, and Marcus (1984) and

Venkatesh and Chiang (1986) suggest that dividend and earnings announcements are not

prefect substitutes.

Penman (1983) finds that after controlling for management’s future earnings

forecast, there is not much information conveyed by the dividend changes themselves.

In contrast, Pettit (1972) came to the opposite conclusion. He demonstrates that stock

121

prices react significantly to dividend announcements. Pettit (1972, p. 1005) concludes

that there is “no obvious tendency for the market to either under or over-react.” Pettit

(1972) documents that new information is fully reflected in stock prices by the end of

the month. Similar to Pettit (1972), Pettit (1976) and Laub (1976) also shows that

dividends convey information about future earnings prospects beyond those predicted by

past earnings. Charest (1978) examines a larger number of firms announcing dividends

over a long period and finds that the abnormal returns are observed beyond the next

quarter. He concludes that his evidence does not necessarily reveal the presence of

information in dividend announcements since he made no effort to isolate the effect of

contemporaneous earnings announcements. These results are in contrast with the

findings of Dielman and Oppenheimer (1984) who find little evidence of systematic

price adjustment beyond the immediate post-announcement month. Eades (1982) and

Woolridge (1982), using dividend announcements made apart from other firm news,

report a positive association between dividend changes and abnormal returns. These

results are consistent with the information content of dividends hypothesis.

The two most frequently cited studies in this area are Aharony and Swary (1980)

and Asquith and Mullins (1983). Both papers used a naïve dividend forecasting model.

Aharony and Swary (1980) investigate the effects of dividends announcements which

were made at different dates than earnings announcements. Similar to Pettit (1972), they

document that cash dividend announcements do provide information beyond that

provided by corresponding quarterly earning announcements. They also provide

evidence supporting the semi-strong form of the efficient market hypothesis. Asquith

and Mullins (1983) re-examine the stock price reaction to dividend announcements

122

using daily stock price data to control for other contemporaneous information

announcements. They investigate the impact of initial dividend payments and the

initiation of dividends after a 10-year hiatus. Their results show significant positive

abnormal returns at dividend initiation announcements. In another empirical study,

Asquith and Mullins (1986) reinforce their earlier findings and offer more support to the

information content of dividend hypothesis. Richardson, Sefcik, and Thompson (1986)

test a sample of 192 U.S. firms that initiated dividends for the first time during the

period 1969 through 1982 and report results similar to those reported by Asquith and

Mullins (1983).

Healy and Palepu (1988) confirm the significantly positive effect of dividend

initiations and negative effect of omissions on stock returns. They also note that

earnings change significantly around a dividend initiation and omission. These findings

indicate that the information transmitted by dividend initiations and dividend omissions

is associated with the earnings changes following the announcement of dividend

changes. These results are in line with those reported by Fama and Babiak (1968) and

Watts (1973) that show dividend initiation and omissions can, in part, be predicted by

changes in past and current earnings. In addition, Healy and Palepu (1988) also claim

that dividends could signal expected earnings whereas stock issues could signal changes

in risk. In contrast, Jain (1992) documents that change in systematic risk is unrelated to

offer announcement effects.

Benesh, Keown, and Pinkerton (1984) examine the market reaction to substantial

shifts in dividend policy. They investigate the aggregate market response to (1) omitted

dividends, (2) dividends decreases of at least 25%, (3) dividends increase of at least

123

25%, and, (4) initial dividend payment. Their results indicate that announcements of

dividends do contain information to the market. Ofer and Siegel (1987) also provide

support for the dividend signaling model. They indicate that there is a positive

systematic association between announcements of unexpected changes in the level of

earnings and dividend levels. Michaely, Thaler, and Womack (1995) examine abnormal

returns after dividend initiations and omissions using a firm size based expected returns

model. They document that the short-term price impact of a dividend omission is

negative and for a dividend initiation it is positive. However, Michaely et al. (1995)

provide evidence of a lagged price adjustment to dividend omissions. Similar results are

obtained by Van Eaton (1999) who examines abnormal stock returns in the three year

period around changes in dividends for NYSE/AMEX firm over the 1971-1990 period.

The results show statistically and economically significant negative post-announcement

abnormal returns of -11% and -17% over the post-announcement year for firms which

decrease or omit their dividends. On the other hand, firms increasing or resuming their

dividends do not show significant abnormal returns over the post-announcement year.

More recently, Bali (2003) examines the long run drifts of stock prices reaction to

dividend increases and decreases and reinforces the Michaely et al. (1995) findings.

Brickley (1983) and Jayaraman and Shastri (1988) examine specially designated

dividends (SDD) and report evidence that is consistent with the information content of

dividend hypothesis. More recently, Mitra (1997) investigates the stock price reaction to

SDD and finds similar results to Brickley (1983) and Jayaraman and Shastri (1988).

Divecha and Morse (1983) examine both the informational content of dividend

hypothesis and the tax effects hypothesis. Focusing on dividend increases over a short

124

period of time, they report evidence consistent with the existence of both an

informational effect and a tax effect. Further evidence supporting the information

content of dividend hypothesis is reported by Handjinicolaou and Kalay (1984) who

analyze returns to bondholders and stockholders. They find that bond prices are not

affected by dividend increases but react negatively to dividend reductions. This

evidence indicates that there is an informational content about firm value in dividend

announcements.

Significant abnormal returns around dividend announcements were reported also

by Kalay and Lowenstein (1985). In this paper, they document that during the three-day

period surrounding dividend announcements, the actual returns, on average, significantly

exceed both the returns predicted by the market model and the average daily returns

realized over a recent period. In addition, the abnormal returns persist for up to four

trading days after the dividend announcement date. Similar to Kalay and Loewenstein

(1985), Bajaj and Vijh (1995) investigate the price formation process during dividend

announcements. Using daily closing prices as well as transactions data, they find that

the average excess return to all dividend announcements increases as the firm size and

stock price decrease. These results are similar to those reported by Kalay and

Loewenstein (1985), and Eades et al. (1985).

Bartov (1991) investigates the nature of the information conveyed by open-

market stock repurchases announcements. He documents that open-market repurchase

announcements convey information about both earnings and risk changes. Likewise,

Leftwich and Zmijewski (1994) report that quarterly dividend announcements convey

information beyond that contained in contemporaneous quarterly earnings

125

announcements. They conclude that there are some interactions between

contemporaneously announced cash dividends and earnings. Hallock and Mashayekhi

(2003) also report evidence consistent with the information content of dividend

hypothesis. They also find little evidence supporting the idea that “news is less

newsworthy” over the past few decades. Jin (2000) reports similar results on a sample

of dividend initiating announcements.

More recently, Wang (2005) employs a propensity score matching approach and

shows that dividend initiations have significantly positive effects on stock returns. Nam,

Thornton, Viswanath, and Wang (2005) examine the relation between the market

reaction to dividend announcements and the information asymmetry between firm

insiders and the market. They find a positive relationship between information

asymmetry and the market reaction which they interpret as an evidence of dividend

signaling. In the same vein, Hanlon et al. (2006) examine whether dividends provide

information to the market about future earnings. In particular, they investigate the

association between current-year stock returns and future earnings for firms that pay

dividends in the current year as compared to firms that do not pay a dividend. They find

that dividend paying firms have significantly higher future earnings response

coefficients than non-dividend paying firms. These results are consistent with dividends

providing valuable information about future earnings prospects beyond that contained in

current earnings. They also document that this information is incorporated into stock

prices. Johnson, Lin, and Song (2006) test the predictions of dividend signaling models

using a sample of closed-end equity funds that adopt policies committing them to pay

minimum dividend yields. They find that funds that adopt minimum dividend policies

126

experience significant discount reductions and have smaller discounts than do funds

without such policies, which is consistent with the dividend signaling models.

In contrast, there are a number of recent studies which fails to find support to the

proposition that divided changes transmit information about future earnings. For

example, DeAngelo, DeAngelo, and Skinner (1996) document that firms respond to

stalled earnings growth by increasing dividends. They fail to provide any evidence that

dividends provide valuable information about future earnings prospects. Similarly,

Benartzi et al. (1997) examine the relationship between firms’ future earnings and

dividend changes. They were unable to find any evidence to support the view that

changes in dividends have information content about future earnings changes. These

results are consistent with Watts’ findings. In contrast, Nissim and Zin (2001) document

that dividend changes are positively related to future earnings. Their findings provide

strong support to the information content of dividend hypothesis. In a related vein,

Guay and Harford (2000) examine the information content of dividend increases versus

repurchases. They find that the stock price reaction to dividend increases is more

positive than the reaction to repurchases after controlling for payout size and market’s

expectations. In a more recent study, Grullon and Michaely (2004) examine the

information content of share repurchase programs and fail to find any evidence that

repurchasing firms experience growth in future profitability. Koch and Sun (2004)

report that investors use dividend changes as signals to corroborate the persistence of

past earning changes.

Examination of stock price reactions to dividend announcements has also been

extended to countries outside the U.S. For example, Liljeblom (1989) investigates the

127

effect of the announcement of stock dividends and stock splits in the Stockholm Stock

Exchange. He documents a corroboration effect between earnings and dividend

announcements. Lonie, Abeyratna, Power, and Sinclair (1996) examine capital market

reactions to a variety of combinations of simultaneous dividend and earnings

announcements made by U.K. firms. Their results are consistent with the dividend

signaling hypothesis. Also in the U.K., Balachandran (2003) investigates the price

reactions to interim and final dividend reductions. His results show that the market

reacts negatively to the final dividend reduction announcements. Interim dividend

reductions lead to a stronger price reaction than final dividend reductions. Similar to

Lonie et al. (1996), these results support the role of the dividend as a market signal.

Easton’s (1991) tests of Australian data provide evidence of an interaction between

earnings and dividend announcements on stock prices, indicating that investors are

influenced by the interplay of signals in reaching their buying and selling decisions. In

an earlier study using Australian data, Brown, Finn, and Hancock (1977) study the

information content of dividend hypothesis. They report evidence that the larger the

change in dividends or profit, the greater the associated change in stock prices. They

also find a positive relationship between dividends and profit changes. In a related vein,

Ball, Brown, Finn, and Officer (1979) examine dividends and the value of the firm in

Australia. They document a positive relationship between dividend yields and post-

announcement rates of return over the period 1960 to 1969. However, they argue that

this relationship is too large to be explained by extant hypothesis pertaining to market-

wide preferences for or against dividends. Dewenter and Warther (1998) provide

evidence that the effect of dividends as a signaling device in Japan is significantly lower

128

as compared to the U.S. They examine 420 U.S. firms and 194 Japanese firms. The

two-day abnormal returns for dividend omissions are -2.53% and -4.89%, while for

dividend initiations 0.03% and 2.38% for Japanese and US firms, respectively. In a

recent study, Conroy, Eades, and Harris (2000) also study Japanese firms and report

evidence consistent with Dewenter and Warther’s (1998). Using data for German firms,

Amihud and Murgia (1997) report evidence consistent with the information content of

dividend hypothesis. In this study, Amihud and Murgia use a sample of 200 firms listed

in the Frankfurt Stock Exchange and find an average abnormal return of 0.965% for

dividend increases and -1.73% for dividend decreases. Similar results are reported by

Travlos, Trigeorgis, and Vafeas (2001) who examine the stock price reaction to both

cash dividends and stock dividends using data from Cyprus Stock Exchange. They

document positive and significant abnormal returns for both cash dividend increases and

stock dividend announcements. They interpret these results as consistent with the

signaling hypothesis. Sponholtz (2004) investigates the simultaneous announcement of

current dividends, current earnings, and the management’s forecast of next year’s

earnings in Denmark. He documents that the stock market reaction to the simultaneous

announcements can be explained by the component of surprise contained in the current

dividend and management’s forecast of next year’s earnings.

The support of the information content of divided hypothesis is not limited to

cash dividend announcements. There are several studies that examine stock dividends

and stock splits and report evidence consistent with this hypothesis. For example, Foster

and Vickrey (1978) and Woolridge (1983) document small, but significant stock price

adjustments on the declaration dates of stock dividend announcements for a sample of

129

concurrent announcement recorded in the Wall Street Journal Index. While the previous

two studies focus on small stock dividend announcements, a study by Grinblatt, Masulis,

and Titman (1984) examines the effect of both stock split and large stock dividend

announcements. They provide evidence that indicates that stock prices, on average,

react positively to stock dividends and stock split announcements that are

uncontaminated by other simultaneous announcements. Moreover, they find

significantly positive abnormal returns on and after the ex-dates of stock dividend and

stock splits. The abnormal returns are higher for stock dividends compared to stock

splits. They offer several signaling based explanations for their results.

Similar results are reported by Lamoureux and Poon (1987), McNichols and

Dravid (1990), Maloney and Mulherin (1992), Ikenberry, Rankine, Stice (1996), and

Masse, Hanrahan, and Kushner (1997) who document a significant positive abnormal

returns around the split announcement day. Ball, Brown, and Finn (1977) examine stock

price reaction around the announcement of stock capitalization changes in Australia for

the period 1960 and 1969 using monthly data. They document abnormal returns of

20.2% for 13 months up to and including the month of bonus issue announcement.

Rankine and Stice (1997) confirm the positive signaling role of stock dividends. In

particular, they find that for stock distributions of the same size, those accounted for as

stock dividends are associated with a significantly larger announcement abnormal return

compared to those accounted for as stock splits. Balachandran, Faff, and Tanner (2004)

investigate the stock price reaction to the announcement of bonus shares in Australia

over the period 1992-2000. They find that the risk-adjusted price reaction from day 0 to

day 1 is positive and statistically significant. These results are consistent with the

130

information content of dividend hypothesis. In contrast, Leledakis, Papaioannou,

Travlos, and Tsangarakis (2005) examine the valuation effects of stock splits undertaken

by Greek firms traded on the Athens Stock Exchange. They find no evidence of a price

reaction on the announcement day. In an earlier study, Papaioannou, Travlos, and

Tsangarakis (2000) also examine the price reaction to stock dividends made by firms

listed on the Athens Stock Exchange on both the announcement date and the ex-dividend

day. They find insignificant abnormal returns on both the announcement and the ex-

dividend day. For India, Mishra (2005) examines the stock price reaction to the

information content of bonus issues with a view of examining whether the Indian Stock

Market is semi-strong efficient. His results indicate that there are significant positive

abnormal returns for a five-day period prior to bonus announcement. On the

announcement day firms experienced an insignificant abnormal return of -0.10%.

Similar results emerge from the stock market reaction to dividend cuts and

omissions by commercial banks. For example, Keen (1983) documents a negative

abnormal returns using weekly data for the period 1974-1977. Black, Ketcham, and

Schweitzer (1989) examine the stock price reaction using NASDAQ-listed banks. They

report evidence of negative reactions to dividend cuts. Bessler and Nohel (1996)

analyze the stock market reaction to dividend cuts and omissions by 56 commercial

banks in the U.S. using daily data. They find significant negative abnormal return in the

two-day event window (-8.02%) which is stronger than those reported in studies for

dividend reductions of non-financial firms. They interpret these results as consistent

with the information content of dividend hypothesis.

131

In summary, the consensus is that dividends announcements do convey

information to capital markets.

4.3. Data

Our sample consists of the universe of Omani companies announcing cash

dividends between January 1, 1997 and August 31, 2005. Announcement dates of the

cash dividend, stock dividend, splits, and earnings are obtained from the Muscat

Depositary and Registration Company Database, the MSM website and Alwatan

newspaper. We also obtain earnings data from the “Share-Holding Guide of MSM

Listed Companies”. We have two sources of stock prices data, namely MSM prices and

the RASP database. The MSM provide us with the stock price data and the MSM index

from 1997 to August 2005. The RASP database covers Oman for the period 1997 to

June 2003. Similar to MSM data, the RASP database contains daily stock price data and

the MSM index. In addition, the RASP database contains intra-daily data for the same

period. To maintain accuracy, the data supplied by the MSM were randomly selected

and compared with the prices provided by RASP; the comparison reveals no difference.

As MSM data covers a longer period, we decide to use the MSM data as the main source

of data for this chapter. However, we also use the intra-daily data from RASP to

examine whether bid-ask bounce affects our results.

We exclude observations that accompany other corporate events such as stock

dividends, splits, or subscription rights. Moreover, we eliminate observations if rights or

stock dividend announcements are made during the event study period. After this

screening the final sample consists of 501 cash dividend announcements. Of the total

132

sample, 251 companies increase their dividends, 178 decrease their dividends while the

remaining 72 cases have no change in dividends (Table 4.1).

Table 4.1. Frequency of Firm-Year Observations The table reports the number of firm-year observations for each year of the sample for dividend decrease, no change, and dividend increase.

Year Dividend Decrease No change Dividend Increase Total 1997 17 7 21 45 1998 12 3 31 46 1999 21 8 27 56 2000 14 13 26 53 2001 26 2 24 52 2002 31 9 17 57 2003 31 8 31 70 2004 21 16 34 71 2005 5 6 40 51 Total 178 72 251 501

We examine the trends in dividend payout policy by utilizing aggregate data by

calendar year on total cash dividends, aggregate earnings, and total market value of

equity. Table 4.2 shows that firms distribute most of their earnings as dividends. For

example, Omani firms distribute around 44% of their earnings in dividends in 1997.

However, the amount of earnings distributed through dividends increased sharply in

2003 to reach 150% which then declined to 50% in 2005. The figures presented in

Table 4.2 also show that Omani firms distribute around 3.57% of their market value in

dividends in 1997. This ratio increased to 17.24% in 2003 and then declined to 5.02% in

2005.

133

Table 4.2. Cash Dividend Distributions The table presents the annual information on cash dividend distributions to stockholders for a sample of Omani firms. The sample consists of all firm-year observations that has data in the Share-Holding Guide of MSM Listed Companies over the period 1997 to 2005 that have available information on the following variables: DIV, EARN and MV. DIV is the total amount of dividends declared on the common stock. EARN is the earnings after taxes. MV is the market value of common stock. The sample contains 512 firm-year observations. ∑i represents the aggregation of data by calendar year. The aggregate numbers are expressed in million of Rials.

Year ∑i DIV ∑i EARN ∑i MV ∑i DIV/∑i EARN

(%) ∑i DIV/∑i MV

(%) 1997 60.511 137.294 1,692.623 44.07 3.57 1998 38.027 76.020 824.484 50.02 4.61 1999 50.702 75.648 835.341 67.02 6.07 2000 59.249 137.365 747.740 43.13 7.92 2001 45.382 54.218 610.507 83.70 7.43 2002 81.488 124.951 937.844 65.22 8.69 2003 210.298 140.304 1,220.041 149.89 17.24 2004 237.674 169.240 1,728.093 140.44 13.75 2005 98.501 198.490 1,961.265 49.63 5.02

We also obtain data on the announced dividend per share in Rials, DIVit, and the

stock price ten days before the announcement day, Pit. We use these data to calculate

dividend yield DIVit/Pit, the change in dividend, ∆DIVit = (DIVit – DIVi,t-1), and the

change in earnings per share, ∆EPSit = (EPSit – EPSi,t-1), for both dividend increases and

decreases.44 The figures presented in Table 4.3 show that the average dividend yield for

the dividend increase sample is 8.20%. The change in dividends is around 8.39% and

the change in earning per share is 8.47% for the same sample. For the dividend decrease

sample, the average dividend yield is 6.15%, the change in dividends is -4.75%, and the

change in earning per share is -5.68%.

44 This is similar to the approach in Amihud and Murgia (1997).

134

Table 4.3. Descriptive Statistics The table reports DIV/P, ∆DIV, and ∆EPS for dividend increases and decreases. DIV/P is the dividend yield, where DIV is the announced dividend per share and P is the stock price 10 days before the announcement day. ∆DIV is change in dividend per share from the previous year. ∆EPS is change in earning per share from previous year.

Category DIV/P (%) ∆DIV (%) ∆EPS (%) Observations Dividends Increase 8.2033 8.3896 8.4714 234 Dividends Decrease 6.1505 -4.7525 -5.6784 145

4.4. Methodology

The methodology used in this study is the standard event study methodology.45

In this method, the expected return is estimated using the following market model:46

jtmtjjjt RRE εβα ++=)( (4.1)

where

αj, βj = the intercept and slope, respectively, of the linear relationship between the return

for stock j and the returns of the MSM,

Rjt = actual returns on stock j on day t,

Rmt = return on the MSM index on day t, and

εjt = the error term of stock j at period t and is expected to have a value of zero.

The abnormal return (ARjt) for stock j on day t is defined as the difference between the

actual return on day i and the expected return predicted from the market model:

,ˆˆ mtjjjtjt RRAR βα −−= (4.2)

45 Refer to Campbell, Lo and MacKinlay (1997), Fama (1976), Dyckman, Philbrick, and Stephan (1984), MacKinlay (1997), Binder (1998), and Kothari and Warner (2006) for excellent surveys of the event study methodology. 46 Brown and Warner (1980) compare the performance of various models, which include Mean adjusted model, Market adjusted, and Market model. They recommend against using complicated methodologies. They state “We have presented evidence that more complicated methodologies can actually make the researcher worse off” (Brown and Warner (1980, p. 249)). In addition, Brown and Warner (1985) find the market model to be well-specified under a variety of conditions when using daily returns.

135

Where Rjt is the actual returns on stock j on day t which is defined as:

1

1

−

− +−=

jt

jtjtjtjt P

DPPR , (4.3)

where Pjt is the closing price of stock j on day t, Pjt-1 is the closing price of stock j on day

t-1, and Djt is the dividends per share for stock j on day t.

The coefficients jα̂ and jβ̂ are ordinary least squares (OLS) estimates of αj, and

βj estimated from a regression of daily stock returns on daily market returns from 250 to

41 days before the announcement date (t = -250 to t = -41, where t = 0 is the

announcement date).

The daily average abnormal return for day t is calculated as

∑=

=n

j

jtjt

NAR

AR1

, (4.4)

where N is the number of events in the sample.

The cumulative average abnormal return in the days surrounding the dividend

announcement dates is formed by summing average ARs over time as follows:

∑=

=L

Ktjtt ARCAR (4.5)

where the CARt is for the period from t = K days until t = L days.

As a robustness check and to test the sensitivity of our results to beta estimation, we also

follow Charest (1978) and Woolridge (1982) and calculate abnormal return, ARjt, by

subtracting the market’s (MSM) daily return, Rmt, from the observed stock’s return over

a given period t. That is,

mtjtjt RRAR −= (4.6)

136

Under this technique, stocks are assumed to have a beta of 1.0.

4.5. Empirical Results

In this study, we are testing the null hypothesis that the daily mean abnormal

return is zero. In other words, cash dividend announcements have no systematic impact

on corresponding stock prices. We test this hypothesis by performing a parametric t-test

where the t-statistics are calculated using the cross-sectional standard deviation.47,48

This test has been used in many studies including Divecha and Morse (1983), Grinblatt

et al. (1984), Healy and Palepu (1988), Ghosh and Wooldridge (1991), Korajczyk,

Lucas, and McDonald (1991), Hand, Holthausen, and Leftwich (1992), Bajaj and Vijh

(1995), Kato and Loewenstein (1995), Lonie et al. (1996), Papaioannou et al. (2000),

Anderson, Cahan, and Rose (2001), Graham et al. (2003), Uddin (2003), Jones and

Danbolt (2005), Kadapakkam and Martinez (2005), Leledakis et al. (2005), and

Muradoglu and Huskey (2005).

4.5.1. Dividend Increase

Table 4.4 provides the daily mean abnormal returns and the t-statistic (testing

that the mean abnormal returns are equal to zero) for five days surrounding the dividend

announcement date (Day 0) using both the market model and the market adjusted return. 47 A detailed description of this method is in Boehmer, Musumeci, and Poulsen (1991) and Seiler (2000). Boehmer et al. show that this test rejects the null at about the appropriate significance level. 48 To check the robustness of the conclusions based on our parametric tests, we also employ nonparametric sign test. Our results are insensitive to this new method. In particular, the z-statistic on the announcement day is 7.5745 for dividend increase and -8.6410 for dividend decrease. For no change sample, the z-statistic is -1.4142 which is insignificant at any conventional level of significance. For detailed description of the test, see Boehmer et al. (1991), Brown and Warner (1980, 1985), Campbell et al. (1997), and MacKinlay (1997).

137

Table 4.4. The Stock Market Reaction to Dividend Increase in the Muscat Securities Market. The sample consists of 251 increasing cash dividend announcements in the period January 1, 1997 to August 31, 2005 for firms listed at the Muscat Securities Market.

The Abnormal Return is defined as (1) )(1

1jt

jt

jtjtjtjt RE

PDPP

AR −+−

=−

− , where E(Rjt) is the

expected return defined by the Market Model and, (2) the market adjusted return. T-statistics are for the null hypothesis that mean abnormal return is equal to zero. Pjt is calculated using the closing price at day t. The Pjt-1 is calculated using the closing price on the day t-1. Event AR(Market Model) T-statistics AR(Market Adjusted Return) T-statistics

-5 0.5306 0.2863 0.5699 0.2541 -4 0.4765 0.2233 0.4331 0.1629 -3 0.1355 0.7301 0.0824 0.4230 -2 0.2935 0.2109 0.2515 0.1699 -1 1.3026 3.9654 1.3774 3.9865 0 5.7826 6.0339 5.8807 6.1021 1 0.3720 1.1594 0.4323 1.3323 2 0.1447 0.5275 0.1155 0.4065 3 0.0970 0.4039 -0.0363 -0.1489 4 -0.6311 -0.7421 -0.6149 -0.7247 5 -0.2750 -1.5972 -0.3780 -1.2118

The positive dividend declaration dates are preceded by positive returns for the

five days before the announcement. Interestingly, the abnormal return earned on day -1

by dividend increasing companies is 1.3%, with a t-statistic of 3.9654. The presence of

significant positive abnormal returns on day -1 shows a somewhat earlier market

reaction to the cash dividend announcement which may suggest that there is some

information leakage into the market. A further 5.78% abnormal return occurs on the

announcement date. The results show that the markets major reaction takes place on day

0. This average abnormal return is the largest abnormal returns in the event period

studied. These mean abnormal returns are highly significant especially on the

announcement date. These results demonstrate that investors who hold companies

stocks during this period, on average, earned positive abnormal return. These results

138

show that announcement of dividend increases is associated with stock price increases.

These findings support the hypothesis that the market reacts positively to a dividend

increase. The results are consistent with an information effect in dividend increase

announcements. These findings imply that relevant information is transmitted to the

market when increases in dividends are announced. These results are in line with those

found in the U.S and strongly contradict the tax-signaling model which argue that higher

taxes on dividends is a necessary condition for dividends to have information and be

informative.

Similar results emerge using the market adjusted returns. There is a significant

positive market reaction to dividend increase. The announcement date average

abnormal return is 5.88% which is very similar to the one reported using the market

model. These results suggest that the estimation and stability of the betas are unlikely to

be a driver of our results.

4.5.2. Dividend Decrease

Table 4.5 gives the results for the dividend decrease sample. These results show

that the abnormal returns are significantly negative on the announcement of a dividend

decrease. The largest t-statistic occurs on dividend announcement day.

139

Table 4.5. The Stock Market Reaction to Dividend Decrease in the Muscat Securities Market. The sample consists of 178 decreasing cash dividend announcements in the period January 1, 1997 to August 31, 2005 for firms listed at the Muscat Securities Market.

The Abnormal Return is defined as (1) )(1

1jt

jt

jtjtjtjt RE

PDPP

AR −+−

=−


expected return defined by the Market Model and (2) the market adjusted return. T-statistics are for the null hypothesis that mean abnormal return is equal to zero. Pjt is calculated using the closing price at day t. The Pjt-1 is calculated using the closing price on the day t-1. Event AR(Market Model) T-statistics AR(Market Adjusted Return) T-statistics

-5 0.0863 0.0886 0.1669 0.1698 -4 0.5818 0.5841 0.5015 0.5010 -3 0.8056 0.7919 0.6266 0.6108 -2 0.1858 0.1898 0.9992 1.0156 -1 -1.0206 -1.0683 -0.8038 -0.8365 0 -2.4904 -4.1037 -2.4161 -4.0225 1 -0.3666 -0.3368 -0.5830 -0.5343 2 0.9777 1.0376 0.9077 0.9564 3 0.6026 0.6440 0.4017 0.2872 4 -0.2302 -0.1889 -0.1317 -0.1072 5 0.5173 0.5018 0.1869 0.1813

The results again support the hypothesis that dividend decreases impart negative

information about the firm’s prospects. However, the mean abnormal returns for the

dividend decrease announcements are of much smaller magnitude than those of the

corresponding dividend increase announcements.49 These results are at odds with many

previous findings which show that dividend decreases generate price responses that are

larger in absolute magnitude than those of dividend increases (Pettit (1972), Charest

(1978), Aharony and Swary (1980), Kwan (1981), Woolridge (1982), among others).

For instance, results using daily stock prices report that the mean abnormal negative

returns on the announcement day that ranges from -3% to -10% for unfavorable dividend

49 It is worth noting that the size effects for dividend decrease are smaller than those for dividend increase. See Table 4.3.

140

announcements while the mean abnormal returns for favorable news is around 1%. Just

as with dividend increases, the results obtained here are at odds with the tax-signaling

models which argue that taxes are a necessary condition for dividends to have

information. The results using the market adjusted returns are almost identical to those

reported using the market model.

4.5.3. No Change

Table 4.6 reports the results for companies that did not change their dividends. If

no news is being signaled to the stock market, then, logically one might assume that no

abnormal stock price movements are expected. Our results are in line with this

proposition.

Table 4.6. The Stock Market Reaction to No Change in Dividends in the Muscat Securities Market. The sample consists of 72 no change cash dividend announcements in the period January 1, 1997 to August 31, 2005 for firms listed at the Muscat Securities Market. The

Abnormal Return is defined as (1) )(1

1jt

jt

jtjtjtjt RE

PDPP

AR −+−

=−


expected return defined by the Market Model and (2) the market adjusted return. T-statistics are for the null hypothesis that mean abnormal return is equal to zero. Pjt is calculated using the closing price at day t. The Pjt-1 is calculated using the closing price on the day t-1. Event AR(Market Model) T-statistics AR(Market Adjusted Return) T-statistics

-5 0.2458 0.6709 0.3567 0.9154 -4 0.8876 0.2943 0.9310 0.2772 -3 0.2756 0.7683 0.3952 0.8315 -2 0.2155 1.2451 -0.0696 -0.1928 -1 0.0202 0.1087 0.0542 0.2392 0 -0.9432 -1.4502 -0.7776 -1.1845 1 -0.8499 -1.6158 -0.2105 -0.3920 2 -0.4746 -1.1826 -0.5840 -1.3880 3 -0.3810 -1.1323 -0.4165 -1.1953 4 -0.7067 -0.5126 -0.6455 -0.4623 5 0.3728 1.3931 0.3471 1.1180

141

The results show that investors who hold these companies stocks earned only

normal returns over the five days surrounding the cash dividend announcement dates.

The mean abnormal returns seem to drift randomly over the event period with no

significant changes on day 0. The mean daily abnormal returns are not significantly

different from zero. However, the negative signs on the dividend announcement dates

are in contrast with those reported in the U.S. For example, the mean abnormal returns

to announcements of no change in dividends in the U.S. were insignificantly positive in

Eades et al. (1985) and significantly positive in Bajaj and Vijh (1990).

In sum, the results show that stock price reaction to cash dividend

announcements are in accord with signaling. They are strongly supporting the

information content of dividend hypothesis, which postulates that changes in cash

dividend announcements do convey information about changes in management’s

assessment of future firm prospects. Announcements of dividend increases are

perceived by the market as positive information and result in immediate positive

valuation effects. Announcements of dividend decreases convey negative information to

the market which results in a decline in stock price. Announcements of no change in

dividends result in no significant change in stock price.

In brief, our results reveal that cash dividend announcements do carry new

information to the market. The market reacts favorably to “good news” announcements

(dividend increases) and adversely to “bad news” announcements (dividend decreases)

which support the view that dividend changes have information content. These results

are in sharp contrast with the tax-based signaling models which argue that higher taxes

142

on dividends relative to capital gains are a necessary condition for dividends to have

information and be informative.

4.5.4. Cumulative Abnormal Returns

We also calculate cumulative average abnormal return for different intervals.

The null hypothesis to be tested is that the cumulative average abnormal returns are

equal to zero. The test statistic is the ratio of the cumulative average abnormal return to

its estimated standard error.50 The results are presented in Table 4.7.

The two day window (-1, 0) shows a significant positive wealth effect

surrounding the cash dividend increase. When the event window is widened to include

additional trading days (-2, +2) before and after the announcement, the cumulative

abnormal returns are also positive and statistically significant. For the (-4, +4) and (-5,

+5) windows, the cumulative abnormal returns are positive but insignificant. The

CAR’s for the pre-announcement window (-5, -1) are positive but insignificant. For the

post-announcement window (+1, +5), the cumulative abnormal returns are negative and

insignificant. The results are very similar whether we use market model or market

adjusted return.

For dividend decrease, the (-1, 0) window reveals a significant negative reaction

to the bad news announcements. The CAR’s are insignificant in the other event

windows. The conclusions using the CAR’s from the market adjusted return model are

consistent with those from the market model.

50 There are many studies that use this test including Foster and Vickery (1978), Asquith and Mullins (1983), Jordan (1999), Park, Yang, Nam, and Ha (2002), Brooke and Oliver (2005), Gustafsoon (2005), among others.

143

Table 4.7. Cumulative Abnormal Returns for Dividend Increase, Dividend Decrease, and No Change in Dividends. The table presents the Cumulative Abnormal Returns (CAR) for dividend increase, dividend decrease, and no change using the market model and the market adjusted return. T-statistics are for the null hypothesis that the cumulative average abnormal returns are equal to zero. T-statistics are reported in parentheses.

Dividend Increase Dividend Decrease No Change

Market Model

Market Adjusted Return

Market Model


Market Model


(+5,-5) 0.0823 0.0811 -0.0035 -0.0014 -0.0134 -0.0061 (0.9450) (0.8292) (-0.0326) (-0.0128) (-0.1747) (-0.0722) (-4,+4) 0.0797 0.0792 -0.0095 -0.0050 -0.0196 -0.0131 (1.1931) (1.0787) (-0.1092) (-0.0539) (-0.2785) (-0.1694) (-3,+3) 0.0813 0.0810 -0.0131 -0.0087 -0.0214 -0.0160 (2.1973) (2.1120) (-0.2002) (-0.1238) (-0.8123) (-0.5328) (-2,+2) 0.0790 0.0806 -0.0271 -0.0190 -0.0203 -0.0158 (2.4121) (2.3709) (-0.5936) (-0.4134) (-1.0495) (-0.7244) (-1,+1) 0.0746 0.0769 -0.0388 -0.0380 -0.0177 -0.0092 (4.6385) (4.7073) (-1.4629) (-1.4336) (-1.3019) (-0.6620) (-1,0) 0.0709 0.0726 -0.0351 -0.0322 -0.0092 -0.0072 (5.5059) (5.5438) (-2.2475) (-2.0619) (-1.1043) (-0.8192) (-5,-1) 0.0274 0.0271 0.0064 0.0149 0.0164 0.0167 (0.4648) (0.3921) (0.1298) (0.3008) (0.4012) (0.3466) (+1,+5) -0.0029 -0.0048 0.0150 0.0078 -0.0204 -0.0150 (-0.1574) (-0.2535) (0.2877) (0.1372) (-0.7009) (-0.5018)

When there is no change in dividends, the results reveal that the cumulative

abnormal returns are insignificant in all event windows examined, both under the market

model and market adjusted returns. This suggests that the announcements of no change

in dividends result in no significant change in stock price.

4.5.5. Regression Results on Changes in Dividends and Earnings

To examine whether dividends contain information beyond that contained in

earnings, we follow Amihud and Murgia (1997) approach. Specifically, we estimate a

model where the announcement abnormal returns are a function of both dividend

144

changes and earning changes relative to stock price. The results are presented in Table

4.8.

The results show that both the ∆DIV/P and ∆EPS/P are statistically significant

which suggest that both dividends and earnings news have information content. This

suggests that the dividends and earnings are strongly associated with abnormal returns.

The adjusted R2 of the model is 10.78% and the F-statistic is significant at the one

percent level. There are no important differences between the response coefficients of

dividend increases and decreases. As in Amihud and Murgia (1997), changes in

dividends results in a significant positive stock price reaction which is beyond the

information conveyed by changes in earnings. It should also be noted that the dependent

variable in this regression is the abnormal returns on the dividend announcement date.

We do not measure the earnings announcement return.

Table 4.8. Regression Results of Abnormal Returns on Dividend Changes and Earnings Changes Relative to Stock Price. The table reports the results of estimating the announcement abnormal returns (based on the market model) on both the changes in dividends and changes in earnings relative to the stock price 10 days before the announcement day. The table shows the variable, their coefficients, and their t-statistics. T-statistics are heteroscedastic consistent (White (1980)). Variable Coefficient T-statistic Constant 0.1685*** 3.9278 ∆DIV/P 4.2789*** 5.0909 ∆EPS/P 0.5793*** 3.1918 Adjusted R2 0.1078 F-value 26.2028 Observations 418

*, **, and *** represents significance at the 10, 5, 1 percent levels, respectively

145

We also estimate the stock price reaction on changes in dividends and changes in

earnings (Table 4.9). We find similar results to those reported above. This suggests that

dividends may contain information beyond that contained in earnings.

Table 4.9. Regression Results of Abnormal Returns on Dividend Changes and Earnings Changes. The table reports the results of estimating the announcement abnormal returns (based on the market model) on both the changes in dividends and earnings. The table shows the variable, their coefficients, and their t-statistics. T-statistics are heteroscedastic consistent (White (1980)). Variable Coefficient T-statistic Constant 0.1640*** 3.7421 ∆DIV 2.4916*** 5.4156 ∆EPS 0.1846** 2.5484 Adjusted R2 0.0940 F-value 22.6311 Observations 418

*, **, and *** represents significance at the 10, 5, 1 percent levels, respectively

4.5.6. Market Efficiency

The faster the market reacts to public announcements, the more efficient the

market is considered to be. If dividends do convey information and if the market

incorporates this information into stock prices, the stock prices should reflect the new

information on the day the cash dividend is announced.

Table results reported in Table 4.4 show that there is a positive and significant

abnormal return one day prior to the announcement of an increase in cash dividends.

The fact that some of the effect of the announcement seems to have been impounded

into the stock price prior to the announcement day may be the result of actions by those

with information about the impeding dividend change. If this apparent anticipation

146

effect is the result of the actions of insiders, then the stock market can not be considered

perfectly efficient.

4.6. Bid-Ask Bounce

In this section, we examine whether the results are influenced by bid-ask bounce.

The importance of bid-ask bounce on stock returns is well documented in many studies;

see for example, Keim (1989), Lakonishok and Smidt (1984), Lease, Masulis, and Page

(1991), Porter (1992), and Bajaj and Vijh (1995). Bid-ask bounce may bias returns if

the closing price before the announcement is more likely to be at the bid price and/or the

closing price after the announcement is more likely to occur at the ask price, and vice

versa. For instance, Lease et al. (1991) document that biases resulting from the bid-ask

spread explain a significant part of the abnormal negative returns on seasoned equity

offering announcements. We examine trade and quotes data obtained from RASP to

investigate whether the bid-ask bounce influence our results.

In order to see if our previous results hold when using the RASP data, we first

use the RASP closing transaction prices and recompute the mean abnormal returns for

cash dividend increasing announcements, decreasing announcements, and no change

announcements. Our results reported in Table 4.10 show that there is almost no

difference with the MSM analysis reported in Table 4.4, 4.5, and 4.6.

Next we measure Pit and Pit-1 at the close of the trading day using the midpoint of

the bid and ask quotes. The results are presented in Table 4.10. The results are very

similar to those reported in Table 4.4, 4.5, and 4.6. Hence, it does not appear that bid-

ask bounce can explain the observed abnormal returns. This finding is consistent with

147

those reported by Bajaj and Vijh (1995) using U.S. data where they document that bid-

ask bounce does not drive their abnormal returns around dividend announcement dates.

Table 4.10. Mean Abnormal Return (AR) Using RASP Quote Midpoints The sample includes 194 dividend increasing announcements, 124 dividend decreasing announcements and 42 no change announcements for firms listed on the MSM during the period from January 1997 to June 2003 that have information available in both the MSM data and RASP database. The Abnormal Return is defined

as )(1

1jt

jt

jtjtjtjt RE

PDPP

AR −+−

=−

− , where E(Rjt) is the expected return defined by the

Market Model. T-statistics are for the null hypothesis that mean abnormal return is equal to zero. The prices used to calculate AR is (1) using RASP closing transaction prices, (2) using the midpoint quotes where Pjt is calculated using the midpoint of the bid-ask spread of the closing quote on day t and the Pjt-1 is calculated using the midpoint of bid-ask spread of the closing quote on the day t-1. T-statistics are in parentheses.

Event/ t-statistic

Increase Decrease No Change

AR Midpoint AR Midpoint AR Midpoint -5 0.5409 0.4841 0.1564 0.1398 0.3342 0.3024 (0.2918) (0.2158) (0.1606) (0.1422) (0.9121) (0.7762)

-4 0.4374 0.4024 0.5115 0.4610 0.8603 0.7984 (0.2050) (0.1514) (0.5135) (0.4606) (0.2852) (0.2377)

-3 0.0849 0.0782 0.5805 0.5236 0.4031 0.3715 (0.4573) (0.4013) (0.5706) (0.5104) (1.1236) (0.7817)

-2 0.2349 0.2114 1.0591 0.9555 -0.0650 -0.0588 (0.1689) (0.1428) (1.0816) (0.9712) (-0.3759) (-0.1629)

-1 1.2644 1.1355 -0.7386 -0.6122 0.0564 0.0509 (3.8493) (3.2863) (-0.7731) (-0.6371) (0.3040) (0.2246) 0 6.1160 5.2781 -2.3677 -2.0436 -0.7499 -0.6472 (6.3818) (5.4768) (-3.9016) (-3.4024) (-1.1531) (-0.9858) 1 0.3995 0.3623 -0.5392 -0.4449 -0.1864 -0.1682 (1.2452) (1.1165) (-0.4954) (-0.4078) (-0.3543) (-0.3272) 2 0.1074 0.0988 0.8525 0.7067 -0.6073 -0.5483 (0.3916) (0.3478) (0.9048) (0.7446) (-1.5131) (-1.3033) 3 -0.0372 -0.0349 0.4177 0.3781 -0.3869 -0.3595 (-0.1548) (-0.1434) (0.4465) (0.2703) (-1.1498) (-1.0316) 4 -0.5700 -0.4771 -0.1234 -0.1116 -0.6519 -0.6063 (-0.6703) (-0.5623) (-0.1013) (-0.0908) (-0.4729) (-0.4342) 5 -0.3742 -0.3244 0.1887 0.1704 0.3552 0.3332 (-1.1731) (-1.1641) (0.1831) (0.1653) (1.3276) (1.0732)

148

4.7. Conclusion

While there are many studies conducted to examine dividend signaling in the

U.S., this chapter is one of the few investigations of this topic in emerging markets and it

is the first of its kind using Omani data. In addition, the data set employed in this

chapter is unique in that (1) there are no taxes on dividends and capital gains, which

allow us to test a tax-based signaling model argument that higher taxes on dividends

relative to capital gains are a necessary condition for dividends to be informative, (2)

there is high concentration of share ownership which should reduce the information

asymmetry between managers and investors which in turn suggest a diminished role for

dividends, (3) there is low corporate transparency which imply a positive effect of

dividends, and (4) most companies change their dividends almost every year.

The major objective of this chapter is to identify whether cash dividend

announcements convey information to the market and whether investors consider

announcement of cash dividends as a signal of a firm’s future prospect. Cash dividend

announcements over the period January 1997 to August 2005 are considered for this

study. We employ a conventional event study methodology to examine the stock price

reaction to dividend announcements.

Our results indicate that cash dividend announcements do convey information to

the market. That is, firm’s announcing an increase in their dividends experience a

significant positive price reaction and firms announcing dividend decrease experience a

significant decline in stock prices. Firms that have no change in their dividends report

insignificantly negative average abnormal returns.

149

Our findings support the notion that dividend increases (decreases) convey

positive (negative) information which results in a positive (negative) price reaction.

This study confirms results from earlier studies that there is a significant abnormal return

during the announcement period. The analysis is consistent with the theories that the

announcement effect is due to a signaling of valuable information. These results are in

contrast with the tax-based signaling models which propose that the higher taxes on

dividends relative to capital gains are a necessary condition for them to have information

and be informative.

We also employ trade and quote data to examine whether the bid-ask bounce

drive our results. Our results reveal that the bid-ask bounce does not appear to affect our

results.

150

Chapter 5: Dividend Policy in the Absence of Taxes

5.1. Introduction

“Although a number of theories have been put forward in the literature to explain their

pervasive presence, dividends remain one of the thorniest puzzles in corporate finance”

(Allen, Bernardo, and Welch (2000, p. 2499))

The question of “Why do corporations pay dividends?” has puzzled researchers

for many years. Despite the extensive research devoted to solve the dividend puzzle, a

complete understanding of the factors that influence dividend policy and the manner in

which these factors interact is yet to be established. The fact that a major textbook such

as Brealey and Myers (2003) lists dividends as one of the “Ten unresolved problems in

finance” reinforces Black’s (1976, p. 5) statement “The harder we look at the dividend

picture, the more it looks like a puzzle, with pieces that just don’t fit together”.

Several rationales for corporate dividend policy are proposed in the literature, but

there is little consensus among researchers on the factors that affect dividend policy.

There is no single economic rational for the payment of dividends or the adoption of a

particular dividend policy. In other words, dividend policy remains a puzzle. A major

part of the puzzle stems from the fact that firms continue to pay dividends despite the tax

disadvantage they impose on shareholders. While this is true in the U.S. and other

western countries, Oman poses a unique case. In Oman, there are neither taxes on

dividends nor on capital gains. Hence, what is puzzling researchers in the US may not

be the case in Oman.

151

There are four main objectives of this chapter which are, first, to identify the

factors that determine the amount of dividends, second, to examine the decision to pay

dividends, third, to apply the Lintner model to test the stability of dividend policy, and

fourth, to outline the potential differences in dividend policy between financial and non-

financial firms. For these purposes, we will shed light on the dividend theories and

identify the determinants of the amount of dividends and the decision to pay dividends.

Firstly, we review the theoretical studies. Secondly, we examine the trends of the

dividend payment pattern. Thirdly, we develop hypothesis and test these. Fourthly, we

examine the determinants of the amount of dividends and the decision to pay dividends.

Fifthly, we use the Lintner model to examine the stability of dividend policy. Finally,

we examine whether dividend policy differs between financial and non-financial firms.51

There are many important motives for this study. First and foremost, Omani

firms distribute almost 100% of their profits in dividends which led the CMA to issue a

circular (number 12/2003) arguing that firms should retain some of their earnings for

“rainy days”. This circular also requires firms to have a clear policy for dividends and to

disclose this in their financial reports. This allows us understand the characteristics of

firms that pay dividends. Second, the study will be conducted in a unique environment

where there are no taxes on dividends and capital gains. Tax differentials are a major

part of the dividend puzzle. Third, one explanation for paying dividends is to minimize

agency problems. However, Omani firms are highly levered through bank loans, which

51 Sawicki (2002) documents that there are significant differences in dividend payout of different industries using a sample of firms from East Asia.

152

reduce the role of dividends in alleviating agency problem.52 Fourth, we use the Lintner

model to investigate the stability of dividend policy, this being important given that we

document in Chapter 4 that Omani firms do change their dividends frequently. Fifth, the

determinants of dividend policy are controversial and there is no unanimity among

researchers on the factors that affect dividend policy. This controversy motivates the

conduct of this research in an attempt to provide some new evidence on the factors that

affect dividend policy. Sixth, most previous research excludes non-dividend paying

firms which may create a selection bias (Kim and Maddala (1992), Deshmukh (2003),

among others). We take account of the selection problem by including non-dividend

paying firms. Finally, there are some studies that report differences between dividend

policy of financial and non-financial firms (Naceur, Goaied, and Belanes (2005)). We

examine this issue for Oman. Moreover, Glen, Karmokolias, Miller, and Shah (1995)

document that dividend policies differ between developed and developing countries.

Likewise, Sawicki (2002) finds that there are differences in the general dividend payout

policies adopted by firms in different countries. This lends further support for this study

since the factors that affect dividend payout in Oman may differ from those in other

countries.

In addition, there are relatively few studies that examine the determinants of

dividend policies in emerging markets, and these produce conflicting results. Further,

firms in emerging markets differ from their developed-country counterparts. In

particular, firms in emerging markets face more financial constraints compared to firms

52 See Aivazian et al. (2003a) for a discussion on the role of bank debt in reducing the agency cost. Fleming, Heaney, and McCosker (2005) also provide a discussion of the benefits of debt financing in alleviating the agency problem.

153

in developed countries, and this may affect dividend policy (Aivazian et al. (2003a)).

The differences between emerging markets and developed markets raise the question

about the extent to which dividend policy theories can apply to Oman. Moreover, the

results of this study should help management in setting their dividend policies. Finally,

there is no study that examines dividend policy in Oman and given its unique

characteristics, such a study is warranted.

Our research provides a number of interesting results on dividend policy. First,

we show that there are common factors that affect the dividend policy of both financial

and non-financial firms, and there are others that affect only non-financial firms. For

example, there are six determinants of dividend policy for non-financial firms, while

there are only three factors that affect the dividend policy of financial firms. The

common factors are profitability, size, and business risk. Government ownership,

leverage, and age have a strong influence on the dividend policy of non-financial firms

but no effect on financial firms. On the other hand, agency costs, tangibility, and growth

factors do not appear to have any impact on the dividend policy of both financial and

non-financial firms. The fact that we find agency costs is not an important driver of

dividend policy is not surprising given that Omani firms have high bank debt.

Second, we find that the determinants of the decision to pay dividends are

consistent with those reported for the determinants of dividend policy. In particular, we

find that the factors that influence the probability of paying dividends are the same as

those that determine the amount of dividends paid.

Third, the empirical results in this chapter show that the speed of adjustment

differs substantially between financial and non-financial firms. While we find that non-

154

financial firms adopt a policy of smoothing dividends, this is not the case for financial

firms. In fact, we find that financial firms do not have stable dividend policies.

The remainder of the chapter proceeds as follows. Section 5.2 describes

dividend policy theories and reviews the main empirical studies on corporate dividend

policy. Section 5.3 briefly discusses the potential determinants of dividend policy and

develops testable hypothesis. Section 5.4 describes the data, develops the regression

specifications, presents summary statistics for the payment of dividends, and reports

some descriptive statistics for the sample. Section 5.5 presents the results for the

determinants of dividend policy. In section 5.6 we provide the results for the

determinants of the likelihood to pay dividends. In section 5.7 we examine the stability

of dividends using the Lintner model. Section 5.8 concludes the chapter.

5.2. Theoretical and Empirical Studies53

In attempting to explain the dividend puzzle, financial economists have

developed three main theories of dividend policy. One theory postulates that dividend

payment is irrelevant and has no affect on firm’s stock price (dividend irrelevance

hypothesis). Another set claims that paying dividends has a positive affect on firm’s

stock price (bird-in-the-hand hypothesis). The third theory asserts that paying dividends

has a negative impact on firm’s stock price (tax effect hypothesis). There are other

theories of dividend policy including the signaling hypothesis, the clientele hypothesis

53 See Ang (1987), Allen and Michaely (1995), and Lease et al. (2000) for comprehensive reviews of the dividend policy literature.

155

and the agency cost and free cash flow hypothesis. We next examine each one of these

in more detail.54

5.2.1. Dividend Irrelevance Hypothesis

Dividend policy theory began in 1961 with the publication of the pioneering

study of Miller and Modigliani where they provide a compelling and widely accepted

argument for dividend irrelevance in a perfect market.55 They propose that in a world

without any market imperfections like taxes, transaction costs or asymmetric

information, a company’s dividend policy is irrelevant. Their premise is that valuation

depends only upon the productivity of the firm’s assets and not the form of payout.

They show that the only important determinant of a company’s market value is its

investment policy and as long as this policy doesn’t change, altering the mix of retained

earnings and payout will not influence a firm’s stock price. The irrelevance argument

implies that no matter how much care managers take in selecting their firm’s dividend

policy, the selected policy has no beneficial impact on stockholders wealth. In short,

dividends are irrelevant.56


There are some studies that support the dividend irrelevance hypothesis. In this

vein, Black and Sholes (1974) perform one of the earliest tests by constructing 25

54 See Chapter 3 for an extensive review of the clientele hypothesis and Chapter 4 for a detailed review of the signaling hypothesis literature. 55 See Grundy (2001) for a discussion of the dividend irrelevance proposition. 56 Recently, DeAngelo and DeAngelo (2006, p. 312) show that “Contrary to Miller and Modigliani (1961), payout policy is not irrelevant.”

156

portfolios to examine the association between dividend yield and stock returns. They

find that the expected return on high and low yield stocks are the same. Stated

differently, firms with high-yield and low-yield dividend payout policy do not seem to

affect total returns. Other studies that find evidence consistent with the dividend

irrelevance hypothesis include Miller and Scholes (1978, 1982), Miller (1986)57,

Bernstein (1996), and Ben Naceur and Goaied (2002). These studies maintain that

dividend policy makes no difference because it has no effect on either stock prices or the

cost of equity. Recently, Conroy et al. (2000) examine the pricing effects of dividend

and earnings announcement in Japan where managers simultaneously announce

dividends and earnings. Consistent with dividend irrelevance hypothesis, they find that

current dividend surprises have no material effect on stock prices.

On the other hand, there are some studies that report evidence inconsistent with

the dividend irrelevance hypothesis. For example, Ball et al. (1979) use Australian data

to examine the effect of dividends on firm value. They fail to find any conclusive

evidence to support the dividend irrelevance hypothesis. Baker, Farrelly, and Edelman

(1985) and Farrelly et al. (1986) conduct a survey on 562 firms listed on the New York

Stock Exchange (NYSE) and find that most of the respondents believe that dividend

policy affects stock prices. Partington (1985) conducts a similar survey in Australia and

reports similar results. In another survey, Partington (1989) also finds that Australian

firms have a desire for dividend stability and the usual dividend policy is to maintain

dividend stability, only gradually increasing dividends as profits increase, and dividend

cuts are only made in exceptional circumstances. Likewise, Baker and Powell (1999)

57 See Grundy (2001) for a review of Merton Miller papers.

157

survey 603 CFOs of NYSE–listed firms and find that 90% of the respondents agree that

dividend policy affects stock prices, which supports Baker et al. (1985). In a similar

vein, Baker and Farrelly (1988), Siddiqi (1995), Casey and Dickens (2000), and Baker et

al. (2002) report results that are inconsistent with the dividend irrelevance hypothesis.

Baker, Mukherjee, and Paskelian (2005) survey managers of dividend-paying

Norwegian firms listed on the Oslo Stock Exchange about their views in dividend

policy. They report mixed evidence about whether a firm’s dividend policy influences

firm value.

5.2.2. Bird-In-The-Hand Hypothesis

An alternative but dated view about dividend policy is that the payment of

dividends increase stock price. This is because paying dividends is a “sure thing” while

there is uncertainty about future stock price appreciation. In other words, because stock

prices are highly variable, dividends represent a more reliable form of return than capital

gains. According to the bird-in-the-hand hypothesis, there is a positive association

between dividend payment and stock price. This is because higher dividend payout ratio

will reduce the required rate of return (cost of capital), and thus increase firm value. In

this vein, Graham and Dodd (1951) claim that a dollar of dividends has, on average, four

times the effect on stock price as a dollar of retained earnings.

However, Miller and Modigliani have criticized the bird-in-the-hand hypothesis

and claim that the firm’s required rate of return is independent of its dividend policy

because investors are indifferent between dividends and capital gains. In addition, they

claim that a firm’s risk is influenced by the riskiness of its operating cash flow, not by

158

the way it distributes its income. As a result, Miller and Modigliani called the theory

that a high dividend payout ratio will maximize a firm’s market value the “bird-in-the-

hand fallacy”. Likewise, Bhattacharya (1979) argues that the reasoning behind the bird-

in-the-hand hypothesis is fallacious. He claims that the riskiness of a firm’s cash flow

determines a firm’s risk. Consequently, the increase in dividends will not enhance a

firm’s value by reducing the riskiness of future cash flows.


While empirical support for the bird-in-the-hand hypothesis is very limited, there

are some studies that find evidence consistent with it. Among the first authors in favour

of the “bird in the hand” hypothesis are Graham and Dodd (1951). They argue that an

increase in dividends increases stock price and lowers the cost of equity.58 In fact,

Graham and Dodd state, “The considered and continuous verdict of the stock market is

overwhelmingly in favour of liberal dividends as opposed to niggardly ones”.

Elaborating on his “bird in the hand” argument, Gordon (1959) argues that a primary

reason for an investor to purchase a stock is to receive dividends. He examines this

hypothesis and finds that dividends have greater affect on firm’s stock price than

retained earnings. Fisher (1961) reports similar results using data from the UK during

the period between 1949 and 1957. Long (1978) provides empirical evidence that

investors may indeed prefer cash dividends. Likewise, Gordon and Shapiro (1956),

58 Litzenberger and Ramaswamy (1979, 1982), Blume (1980), and Ang and Peterson (1985) take the opposite direction and document that stocks which pay more dividends have higher required rates of returns and hence lower stock price.

159

Gordon (1963), Lintner (1962), and Walter (1963) report evidence consistent with the

bird-in-the-hand hypothesis.

Alternatively, Diamond (1967) examines the effect of dividends and retained

earnings for a sample of 255 US firms during the period 1961 and 1962. The results

obtained provide only weak evidence for the argument that investors prefer dividends

over retained earnings. These results are similar to those reported by Friend and Puckett

(1964). Baker et al. (2002) conduct a survey on managers of NASDAQ firms that

consistently pay dividends to determine their views about dividend policy. In this

survey, they ask managers whether firms prefer dividends over capital gains. They find

no support for the bird-in-the-hand hypothesis. In fact, Baker et al. (2002, p. 278) state

“…this finding does not provide support for the bird-in-the-hand explanation for why

companies pay dividends”.

5.2.3. Tax Effect Hypothesis59

The school of thought which favours lower dividends, Brennan (1970) and

Litzenberger and Ramaswamy (1980), base its case on the view that dividends are less

desirable than capital gains because dividends are taxed more heavily than capital gains.

This view is strengthened by the fact that in most countries dividends are taxed

immediately while taxes on capital gains are deferred until the gains are actually

realized. This is a departure from the MM hypothesis where they assume that there are

no taxes. The tax-effect hypothesis argues that there is a negative association between

dividends and stock price. This is because a high dividend payout increases the cost of

59 See Graham (2003) for a survey on the impact of taxes on corporate finance.

160

capital which results in a decrease in stock price. The tax disadvantage of dividends

tends to make investors prefer companies that retain most of their earnings and, as a

result, these investors are willing to pay a premium for companies with low dividend

payment (Brennan (1970)). Consequently, firms should keep their dividend payments

low if they want to maximize stock prices.

5.2.3.1. Empirical Evidence60

Although there are many studies that examine the tax-effect hypothesis, the

evidence reported in most cases is not supportive. For instance, Black and Sholes

(1974) find that low and high dividend yield stocks do not have significantly different

stock returns either before or after taxes. That is, they find no evidence of a tax effect.

In contrast, Litzenberger and Ramaswamy (1979) use monthly data from the US from

1931 to 1977 and classify stocks into yield classes, a positive dividend-yield class and

zero dividend-yield class. They find evidence in support of the theory that there is a

differential tax impact on dividends over capital gains. Specifically, Litzenberger and

Ramaswamy (1979) document that pretax returns are associated with dividend yield.

They conclude that “for every dollar increase in return in the form of dividends,

investors require an additional 23 cents in before tax returns” (p. 190). Litzenberger and

Ramaswamy (1979) results imply that firms could increase their stock price by paying

fewer dividends. Blume et al. (1974) find that taxes affect the portfolio mix of investors.

60 There are many studies that examine the impact of taxes on dividends by examining the behaviour of stock prices around the ex-dividend day. For an extensive review of the literature on this part, see Chapter 3.

161

Poterba and Summers (1984) also report evidence consistent with the tax-effect

hypothesis.

On the other hand, Miller and Sholes (1982) re-examine Litzenbereger and

Ramaswamy (1979) findings and provide evidence inconsistent with the tax-effect

hypothesis. In particular, they fail to find any evidence of a tax effect. Keim (1985)

uses a sample of 429 firms and estimates the relationship between long-run dividend

yields and stock returns. He finds that the relationship between the long-run dividend

yield and stock returns is not solely driven by the difference in tax treatment between

dividends and capital gains. Chen, Grundy, and Stambaugh (1990) document that the

positive relationship between dividend yield and equity returns can be explained by a

time-varying risk premium that is correlated with the dividend yield. They show that

there is no significant association between cross-sectional variations in returns and

dividend yield that is a consequence of a tax penalty. In a more recent study, Morgan

and Thomas (1998) use data from the UK over the period 1975 to 1993 to examine the

tax-effect hypothesis. Their results are inconsistent with the tax-effect hypothesis.

Kalay and Michaely (2000) re-examine the influence of the differential taxation of

dividends and capital gains and find no empirical evidence for the tax effect.

5.2.4. Agency Costs and Free Cash Flow Hypothesis

A major strand of the literature focuses on agency problem between managers

and shareholders. Due to the separation between ownership and control, managers

(agents) may not always act in the best interest of the firm owners. This induces

shareholders to incur agency costs to monitor managers’ behaviour. Dividend payments

162

may help in aligning the interests of managers and shareholders by cutting down the

cash available for use at the discretion of management, and hence providing protection

against self-interest of management (Jensen and Meckling (1976), Rozeff (1982),

Easterbrook (1984), Jensen (1986), Crutchley and Hansen (1989), Jensen et al. (1992),

Alli et al. (1993), Saxena (1999), and Mollah, Keasey, and Short (2000)). Moreover,

paying larger dividends reduces the discretionary internal cash flow and forces the firm

to seek external financing from capital markets and the scrutiny and disciplining effects

of investment professionals (Easterbrook (1984)). In other words, the capital markets

provide an efficient monitoring mechanism for firms to reduce excess perquisite

consumption and hence reduce the agency problem. Moreover, Jensen’s (1986) free

cash flow hypothesis suggests that excess free cash flow motivates managers to invest in

projects with negative net present value. Under this hypothesis, managers have an

incentive to engage in activities to increase the size of the firm beyond the optimal level.

Dividend payments may help reduce the overinvestment problem by reducing the free

cash flow under management discretion. Consequently, dividend payments may help in

reducing agency costs between managers and shareholders.

Another source of agency costs is the potential conflict between shareholders and

bondholders. This conflict arises because shareholders can expropriate wealth from

bondholders by paying themselves dividends. Stated differently, dividend payments to

shareholders may result in a reduction of the funds available to be distributed to

bondholders (Jensen and Meckling (1976)). Therefore, bondholders may prefer to place

some restrictions on dividend payments to make sure that the firm has enough money to

163

pay them (Smith and Warner (1979) and Kalay (1982b)). In contrast, shareholders may

prefer to have large dividend payments (Ang (1987)).


There are many studies that address agency costs as an explanation for paying

dividends, however these produce mixed results. Perhaps the best-known attempt to

find an empirical relationship between agency costs and dividend policy is Rozeff

(1982). He uses a sample of 1,000 non-regulated firms in 64 different industries from

1974 to 1980. Rozeff employs two variables as proxies for agency costs and finds that

these variables are important determinants of dividend policy. In particular, Rozeff

documents that firm’s establish higher dividend payouts when insiders hold a lower

fraction of the equity and/or greater number of stockholders owns the outside equity.

Dempsey and Laber (1992) update the work of Rozeff’s by using an extended period

between 1981-1987. Their findings are in line with Rozeff’s results. In contrast, Alli et

al. (1993) use a factorial model and find results that are inconsistent with Rozeff (1982).

In their study, as the number of stockholders increases, the agency problem becomes

more severe and hence the need for monitoring managerial actions increases. Managers

need to pay higher dividends to reduce the agency problem. Alli et al. also find that

shareholders and bondholders conflicts affect the dividend policy of the firm. Crutchley

and Hansen (1989) investigate the relationship between ownership, dividend policy and

leverage and document that managers make financial decisions to efficiently control

agency costs. In a similar vein, Jensen et al. (1992) examine the determinants of cross-

sectional differences in insider ownership, debt and dividend policy. They use three-

164

stage least squares for a sample of 565 firms for the year 1982 and 632 firms for the year

1987. They report evidence that supports Rozeff (1982) and the agency cost hypothesis.

In particular, they find that inside ownership is one of the most influential determinants

of dividend policy.

More support and further contribution to the agency theory debate is provided by

Holder, Langrehr, and Hexter (1998) in their examination of 477 US firms over the

period 1980 to 1990. In particular, they report a significant negative association

between insider ownership and dividend payouts and a significant positive association

between dividend payouts and the number of shareholders. Saxena (1999) investigates

the determinants of dividend policy of 235 unregulated and 98 regulated NYSE listed

firms over the period 1981 to 1990. He documents that agency costs have a primary

affect on dividend policy which is similar to the results reported by Holder et al. (1998).

Lang and Litzenberger (1989) examine the free cash flow hypothesis using a

sample of 429 US dividend-change announcements for the period 1979 to 1984. They

use the framework of the principal-agent conflict model developed by Berle and Means

(1932) and extended by Jensen (1986). They find that free cash flow has strong

explanatory power, consistent with the free cash flow hypothesis. In contrast, Howe,

He, and Kao (1992) use a sample of 55 self-lenders and 60 special dividend

announcements between 1979 and 1989 and provide evidence inconsistent with Lang

and Litzenberger (1989). In a similar vein, Denis, Denis, and Sarin (1994) examine the

relationship between dividend yield and Tobin’s Q on a sample of 5,992 dividend

increases and 785 dividend decreases over the period 1962 to 1988. They report

evidence inconsistent with the free cash flow hypothesis. Yoon and Starks (1995) repeat

165

the Lang and Litzenberger experiment over a larger time period. They use a sample of

4,179 dividend change announcements of firms listed on the NYSE over the period 1969

to 1988 and report similar results to those of Denis et al. (1994). Similarly, Lie (2000)

uses a large sample of special dividends, regular dividend, and self-tender offers to

examine the free cash flow hypothesis. He reports evidence inconsistent with the free

cash flow hypothesis. On the other hand, the Grullon, Michaely, and Swaminathan

(2002) findings of a declining return on assets, cash levels, and capital expenditure in the

years after dividend increases implies that firms that expect a reduction in their

investment opportunity set are the ones that are more likely to increase dividends. This

evidence is in line with the free cash flow hypothesis.

Recently, DeAngelo, DeAngelo, and Stulz (2004) examine the probability that a

firm increases dividends with higher levels of equity returns. They provide evidence

that is strongly in line with their prediction. Specifically, for publicly traded industrial

firms over 1973-2002, the proportion of firms that pay dividends is high when the ratio

of return on total common equity (or total assets) is high, and falls with declines in either

ratio, becoming near zero when a firm has a low return on equity. They interpret this

result as evidence that firms pay dividends to mitigate agency problems. On the other

hand, Grinstein and Michaely (2005) find no evidence that either the portion of shares

held by institutions or the concentrations of their holdings is related to dividend payout,

inconsistent with agency cost theory. Furthermore, they find that institutional investors

do not monitor and control management actions through dividend policy. Similarly,

Brav et al. (2005) in their interviews of financial executives in the US find that most

financial executives do not think that dividend policy is a means of imposing self-

166

discipline. Specifically, almost 87% of executives think that the discipline imposed by

dividends is not an important factor influencing dividend policy.

Further support for the agency cost hypothesis is reported using data from

outside the US. For example, Mollah et al. (2000) examine 153 non-financial

companies listed on the Dhaka Stock Exchange for the period 1988 to 1997. They find

that all the proxies used for agency costs are significant and agency costs are an

important determinant of dividend policy. Similarly, La Porta, Lopez-De-Silanes,

Shleifer, and Vishny (2000) use a sample of 4,000 firms from 33 countries around the

world. They find that dividend policies vary across legal regimes in ways consistent

with the agency theory of dividends. In particular, they report that firms pay more

dividends in countries with better shareholder protection. They conclude that “our data

suggest that the agency approach is highly relevant to an understanding of corporate

dividend policies around the world”. Likewise, Manos (2002) uses a sample of 661 non-

financial firms listed on the Bombay Stock Exchange and finds evidence consistent with

the agency cost hypothesis. Also, Zeng (2003) investigates the determinants of dividend

policy for Canadian firms and reports evidence consistent with the agency cost model.

More recently, Borokhovich, Brunarski, Harman, and Kehr (2005) find that on average,

firms with a majority of outside directors on their boards experience significantly lower

mean abnormal returns around the announcements of sizable dividend increases. They

interpret this as evidence that dividends reduce agency costs. Similarly, Chen and

Dhiensiri (2005) analyze the determinants of dividend policy using a sample of firms

listed on New Zealand Stock Exchange (NZSE) and report evidence consistent with the

agency cost theory. In particular, they find that NZSE firms tend to have a high

167

dividend payout ratio when they have high ownership dispersion. They also find that

these firms tend to have a lower dividend payout ratio when they have a higher degree of

insider ownership. On the other hand, Chay and Suh (2005) investigate the determinants

of dividend policy in 24 countries around the world and find weak support for the

hypothesis that agency costs are related to dividend payouts.

5.3. Factors that Influence Dividend Policy

Based upon the determinants of corporate dividend policy identified by the

previous theoretical and empirical studies and the availability of data in the “Share-

Holding Guide of MSM Listed Companies”, this section describes the factors that we

use to determine dividend policy.

5.3.1. Profitability

Profits have long been regarded as the primary indicator of a firm capacity to pay

dividends. In fact, several studies find the profitability of the firm is a significant factor

that influences a firm’s dividend policy (Lintner (1956), Adaoglu (2000), Pandey

(2003), Aivazian et al. (2003b, 2006), among others). Since dividends are usually paid

from the annual profits, it is logical that profitable firms are able to pay more dividends.

According to pecking order theory, highly profitable firms are in a position to distribute

dividends. Fama and French (2001) report a positive association between dividends and

profitability which they interpret as evidence in support of the pecking order theory. To

examine whether the profitability of the firm influences its dividend policy, we use the

ratio of earnings before interest and taxes to total assets as our surrogate for profitability

168

(Tong and Green (2005), Farhat et al. (2006), Chang et al. (2006), among others). We

expect to find a positive relationship between dividends and profitability.

5.3.2. Firm Size

Variables such as size have the potential to influence a firm’s dividend policy. In

fact, there are many studies that document firm size as an important determinant of

dividend policy. In general, these studies report a positive relationship between firm

size and dividends (Lloyd, Jahera, and Page (1985), Chang and Rhee (1990), Smith and

Watts (1992), Gaver and Gaver (1993), Vogt (1994), Barclay, Smith, and Watts (1995),

Redding (1997), Adedeji (1998), Bradley, Capozza, and Seguin (1998), Holder et al.

(1998), Fama and French (2001), Aivazian et al. (2006), among others). The

explanation for the positive relationship is that larger firms have an advantageous

position in the capital markets to raise external funds and are therefore less dependent on

internal funds. Furthermore, larger firms have lower bankruptcy probabilities and

therefore should be more likely to pay dividends. This implies an inverse relationship

between the size of the firm and its dependence on internal financing. Hence, larger

firms are expected to pay more dividends.

As a surrogate for firm size, we use the natural logarithm of sales. This measure

is used by many prior studies including Booth et al. (2001), Dickens, Casey, and

Newman (2002), Aivazian et al. (2003b), Bebczuk (2004), Fleming, Heaney, and

McCosker (2005), and Grinstein and Michaely (2005).

169

5.3.3. Leverage

Leverage may affect a firm’s capacity to pay dividends. This is because firms

that finance their business activities through borrowing commit themselves to fixed

financial charges that include interest payments and the principal amount. Failure to

make these payments by the due time subjects the firm to risk of liquidation and

bankruptcy. This suggests that firms with a high level of leverage have higher levels of

risk. Higher leverage may result in a low dividend payment. Furthermore, some debt

covenants have restrictions on dividend distributions because the lenders want to secure

their debt. In addition, debt can serve as a substitute for dividends in reducing the

agency problem (Jensen (1986)). This is because firms that borrow are required to make

contractual payments to lenders which reduce the free cash flow available to managers

and subject them to monitoring from capital markets. This analysis suggests a negative

relationship between dividends and leverage.

Several studies report results that are consistent with a negative relationship

including Nakamura (1989), DeAngelo and DeAngelo (1990), Jensen et al. (1992),

Agrawal and Jayaraman (1994), Bradley et al. (1998), Crutchley, Jensen, Jahera, and

Raymond (1999), Faccio, Lang, and Young (2001), Gugler and Yurtoglu (2003),

Aivazian et al. (2006), among others.

We test whether leverage is an important determinant of dividend policy by

using the debt ratio as our proxy for leverage. The debt ratio has been used by many

studies including Sawicki (2002), Aivazian et al. (2003a,b), Zeng (2003), Bebczuk

(2004), Trojanowski (2004), Bancel, Bhattacharyya, and Mittoo (2005), Kania and

170

Bacon (2005), Wei and Xiao (2005), Trojanowski and Renneboog (2005), and Zhang

(2005).

5.3.4. Agency Costs

The separation of ownership and control results in the agency problem. This

problem can be reduced by distributing dividends (Rozeff (1982), Easterbrook (1984),

Jensen et al. (1992), among others). In this vein, dividends are paid out to stockholders

in order to prevent managers from building unnecessary empires to be used in their own

interest. In addition, dividends reduce the size of internally generated funds available to

managers, forcing them to go to the capital market to obtain external funds (Easterbrook

(1984)). Furthermore, dividend payments are used to reduce the free cash flow problem

(Jensen (1986)). Dividend payments reduce discretionary funds available to managers

and this reduces the overinvestment problem.

As explained in Rozeff (1982), firms with a larger percentage of outside holdings

are subject to higher agency costs. The more dispersed is the ownership structure, the

more acute the free rider problem and the greater the need for outside monitoring

(Manos (2002)). Stated differently, as the number of stockholders increase, agency

problems become more severe and thus the need for monitoring managers also increases.

Hence, these firms should pay more dividends to control the impact of widespread

ownership. Consequently, it is expected to find a positive association between the

number of shareholders and the agency problem.

For the case of Oman, which as we previously reported is highly levered where

banks play a pivotal role in financing Omani firms, agency problems should be less

171

severe. Jensen (1986) argues that debt could serve as a substitute for dividends in

reducing the agency problem. This fact should reduce the importance of dividends in

alleviating the agency problem in Oman.

While there is a wide agreement that agency costs are an important determinant

of dividend policy, a critical issue is to find an appropriate proxy for agency costs. In

this vein and as explained before, Rozeff (1982) argues that firms with greater number

of shareholders (wider dispersion of ownership) are subject to higher monitoring costs.

Previous research used the number of shareholders as a proxy for dispersion of

ownership (Rozeff (1982), Lloyd et al. (1985), Jensen et al. (1992), Alli et al. (1993),

Schooley and Barney (1994), Holder et al. (1998), Saxena (1999), Mollah et al. (2000)),

and Deshmukh (2003)). We follow these studies by using the logarithm of the number

of shareholders to account for the dispersion of ownership which is used as a proxy for

agency costs.61 If dividends are important in alleviating agency problems, we should

observe a positive association between dividends and the number of shareholders.

5.3.5. Business Risk

Business risk is a potential factor that may affect dividend policy. High levels of

business risk make the relationship between current and expected future profitability less

certain. Consequently, it is expected that firms with higher levels of business risk will

have lower dividend payments. Furthermore, Beaver, Kettler, and Scholes (1970),

Michel and Shaked (1986), Bar-Yosef and Huffman (1986), Glen et al. (1995), and

61 Some studies use the percentage of a firm’s common stock held by insiders as a proxy for agency costs (Rozeff (1982), Lloyd et al. (1985), Dempsey and Laber (1992), Jensen et al. (1992), Collins, Saxena, and Weaver (1996), and Mollah et al. (2000)). Since we do not have these data, we are not able to use it in this study.

172

others argue that the uncertainty of a firm’s earnings may lead it to pay lower dividends

because volatile earnings materially increase the risk of default. In addition, field

studies using survey data (e.g., Lintner (1956), Brav et al. (2005)) report compelling

evidence that risk can affect dividend policy. In these surveys, managers explicitly cite

risk as a factor that influences their dividend choice. In a recent study, Hoberg and

Prabhala (2006) document that risk is an economically and statistically significant

determinant of dividends.

As a surrogate for business risk, we follow Aivazian et al. (2003b) and use the

standard deviation of return on investment. We expect to find a negative relationship

between dividends and business risk.

5.3.6. Ownership Structure

The type of ownership is an important factor that may influence a firm’s

dividend policy (Maury and Pajuste (2002)).62 Different types of owners have different

preferences for dividends. For example, in family-controlled firms where managers are

the owners there is less need for dividends to reduce the agency problem. In contrast,

firms with large government ownership may suffer more from agency problems,

because, in firms where there is large government ownership, there is “a double

principal-agent problem” (Gugler (2003, p. 1301)). Dividend payments may alleviate

the agency problem in these firms. The above analysis implies a positive association

between dividends and government ownership. To control for government ownership,

62 See Short (1994) for a survey on the relationship between ownership structure and dividend policy.

173

we use a dummy variable which is equal to one for firms where the government is the

controlling shareholder, and zero otherwise.63

Furthermore, firms with a high percentage of institutional ownership are

expected to suffer less from agency problems. This is because institutional investors can

play a significant role in monitoring these firms to alleviate agency problems. In this

vein, Zeckhauser and Pound (1990) demonstrate that institutional shareholders may act

as a substitute monitoring device, thereby reducing the need for external monitoring by

capital markets. On the other hand, Short, Zhang, and Keasey (2002, p. 108), state that

“the arm’s length view of investment held by many institutional investors, coupled with

the incentives to free ride with respect to monitoring activities, suggests that institutional

shareholders are unlikely to provide direct monitoring themselves”. In the US,

institutional investors are expected to invest more in dividend-paying stocks to get

advantage of the tax treatment that favour institutional investors (Redding (1997)).64

However, Grinstein and Michaely (2005) fail to find any evidence that institutional

ownership is related to the dividend payout ratio.

5.3.7. Maturity Hypothesis

Grullon et al. (2002) suggest that as firms mature they experience a contraction

in their growth which results in a decline in their capital expenditures. Consequently,

63 We use a 10% threshold level of ownership to identify the ultimate owner of the firm. For instance, if the government owns 10% or more of a firm’s shares, that firm is considered government owned. This is the criteria used by the MSM. This approach is also used by La Porta et al. (1999), Faccio et al. (2001), Maury and Pajuste (2002), among others. 64 While we have aggregate data that are published in the MSM annual reports (see Appendix A), we do not have data at the firm level on the type of ownership structure such as insider ownership and institutional ownership. It is worth noting that the MSM has started recently to publish the names of individuals and institutions with 10% or more shareholding.

174

these firms have more free cash flow to pay as dividends. In contrast, younger firms

need to build up reserves to finance their growth opportunities requiring them to retain

earnings. Consequently, these firms do not pay as much in dividends. Similarly, Brav et

al. (2005) suggest that more mature firms are more likely to pay dividends. Indeed,

Salas and Chahyadi (2005) find that maturity is a significant determinant of dividend

policy. We test the maturity hypothesis by using the firms’ age as a proxy for a firm’s

maturity. Following Salas and Chahyadi (2005) and Barclay, Holderness, and Sheehan

(2006), we define age as the difference between the calendar year of the observation and

the firm’s incorporation date reported in the “Share-Holding Guide of MSM Listed

Companies”. We expect a positive association between dividends and the age of the

firm.

5.3.8. Tangibility

Asset tangibility may have an effect on dividend policy. This is because firms

with high level of tangible assets can use these as collateral for debt (Booth et al. (2001)

and Bevan and Danbolt (2004)). Consequently, such firms tend to rely less on retained

earnings implying that these firms will have more cash that can be distributed in

dividends. This suggests a positive association between asset tangibility and dividends.

Furthermore, high levels of tangible assets are an indication of higher level of protection

for bondholders. In other words, firms with high levels of tangible assets should be

subject to less agency problem between shareholders and bondholders (Titman and

Wessels (1988)). The higher the tangible assets the less likely bondholders will impose

175

severe restrictions on the firm’s dividend policy, and consequently, this will lead to a

higher level of dividend payment.

Aivazian et al. (2003b) find that firms operating in emerging markets with high

levels of tangible assets tend to have lower dividends. They explain this result by saying

that firms in emerging markets face more financial constraints when short-term bank

financing is a major source of debt. Hence, firms with high levels of tangible assets will

have fewer short term assets that can be used as collateral to obtain the necessary

financing. We show in Chapter 2 that Omani firms are highly levered with short-term

bank debt playing a pivotal role in financing. In this case, Aivazian et al. (2003b)

analysis implies that we should observe a negative association between dividends and

tangibility. To test for the above hypothesis, we follow Booth et al. (2001) and Aivazian

et al. (2003b) and use the ratio of total assets minus current assets divided by total assets

as a surrogate for tangibility. We predict a negative association between dividends and

asset tangibility.

5.3.9. Growth Opportunities

Firms experiencing substantial success and rapid growth require large additions

of capital. Consequently, growth firms are expected to pursue a low dividend payout

policy. On the other hand, firms with low growth opportunities are more likely to pay

dividends. Similarly, the pecking order theory predicts that firms with a high proportion

of their market value accounted by growth opportunities should retain more earnings so

that they can minimize the need to raise new equity capital. It is also consistent with the

free cash flow theory where firms with high growth opportunities will have lower free

176

cash flow and will pay lower dividends (Jensen (1986), Lang and Litzenberger (1989),

Howe et al. (1992), and Denis et al. (1994)).

Previous research by Rozeff (1982), Smith and Watts (1992), Jensen et al.

(1992), Alli et al. (1993), Gaver and Gaver (1993), Schooley and Barney (1994), Fama

and French (2001), Ho, Lam, and Sami (2004), and Aivazian et al. (2006) report results

that support the negative relationship between dividends and growth opportunities.

Likewise, Barclay et al. (1995) find investment opportunities are an important

determinant of dividend policy.

Table 5.1. Summary of Testable Hypothesis and Proxy Variables The table presents summary of the testable hypothesis based on the review of the theoretical and empirical studies. Factor Variable

Name Definitions Hypothesized

Sign Profitability PROFIT Ratio of earnings before interest and

taxes to total assets Positive

Size LOGS Log of sales. Positive Leverage DR Ratio of total debt to total assets. Negative Agency Costs STOCK Natural Log of the number of

stockholders. Positive

Business Risk DROI Standard deviation of return on investment.

Negative

Government Ownership

GOVOWN Dummy equal one if firm owned by government or its agencies and zero otherwise.

Positive

Maturity AGE The difference between the current year of the observation and the year of incorporation.

Positive

Tangibility65 TANG Total assets minus current assets divided by total assets.

Negative

Growth Opportunities

MB Ratio of a firm’s market value of equity dividend by the book value of its assets.

Negative

65 We subtracted intangible assets from long-term assets in the numerator.

177

To account for growth opportunities, we follow previous research and use the

market-to-book ratio as a surrogate for growth opportunities (Barclay et al. (1995),

Cleary (1999), Travlos et al. (2001), Deshmukh (2003), Aivazian et al. (2003b, 2006),

Stacescu (2004), Naceur et al. (2005), Grinstein and Michaely (2005), and Barclay et al.

(2006)). We expect a negative relationship between dividends and growth opportunities.

In sum, we have described nine hypotheses that are related to factors that may

affect dividend policy. To recapitulate, Table 5.1 reports a summary of the hypothesis

described above. The table also provides the proxies used for the variables along with

the expected sign for each factor.

5.4. Data

The data for this study are obtained from “Share-Holding Guide of MSM Listed

Companies” published by the MSM. As the data were available in hard copy only, the

first task was to input the data into a computer database. The data set comprise all

publicly traded firms listed at the MSM. In the sample, firms come from all four sectors

that comprise the MSM namely, financial and banking sector, service sector, industry

sector, and insurance sector. We split this sample into financial and non-financial firms.

Financial firms include banks, insurance, leasing, and investment holdings while non-

financial firms include industrial and service firms such as poultry, fisheries, agriculture,

oil, and manufacturing firms.

The number of firms included in the study changes from one year to another,

with a range from 14 to 37 for financial firms and a range from 32 to 107 for non-

178

financial firms. This results in a data set of an unbalanced panel containing 413 firm-

year observations for financial firms and 1,057 firm-year observations for non-financial

firms. The fact that we are using panel data gives “more informative data, more

variability, less collinearity among the variables, more degrees of freedom and more

efficiency” (Baltagi (2001, p.6)).66

These data are time series cross-sectional variables which are collected over the

entire life of the MSM from 1989 to 2004. We check the accuracy of the data by

comparing the figures from the MSM Guide with the data from the firm’s financial

statements available on the internet, where possible.

The empirical literature on dividend policy has largely ignored firms that do not

pay dividends. If value-maximizing firms choose not to pay dividends, a sample that

contains only dividend paying firms will be subject to a selection bias. An econometric

analysis of such a sample will yield biased and inconsistent estimates. To address this

selection bias, we use both dividend-paying and non-dividend paying firms. In this vein,

Kim and Maddala (1992) demonstrate that it is important to allow for zero observations

on dividends in the estimation of models of dividend behaviour. Likewise, Deshmukh

(2003, p. 353) states “If firms find it optimal to not pay dividends, then their exclusion

from any empirical analysis may create a selection bias in the sample, resulting in biased

and inconsistent estimates of the underlying parameters”.67

66 There are many studies that use panel data to investigate dividend policy such as Anderson (1986), Chowdhury and Miles (1989), Kim and Maddala (1992), Adaoglu (2000), Benito and Young (2003), Gugler and Yurtoglu (2003), Ho (2003), Omet (2004), Trojanowski (2004), among others. 67 For further information on this issue, see Anderson (1986) and Kim and Maddala (1992).

179

5.4.1. Estimation Model

Based on the previous description of our proxies for the potential factors that

may affect dividend policy, we estimate the following model:

GOVOWNDROISTOCKDRLOGSPROFITBDIVYLD 6543210 ββββββ ++++++=

εβββ ++++ MBTANGAGE 987 (5.1)

where the variables are as defined in Table 5.1. The expected signs for the explanatory

variables in the empirical model are positive for profitability, size, agency costs,

government ownership, and maturity; and negative for leverage, business risk,

tangibility and growth.

We use dividend yield as the dependent variable. This is in line with previous

research by Chang and Rhee (1990), Gaver and Gaver (1992), Smith and Watts (1992),

Schooley and Barney (1994), Barclay et al. (1995), Redding (1997), Gul (1999), Han,

Lee, and Suk (1999), Dickens et al. (2002), Aivazian at el. (2003a), Ho et al. (2004),

Stacescu (2004), Naceur et al. (2005), among others. As a robustness check, we also

employ the same measure of dividend policy used by Fama and French (2002), Aivazian

et al. (2003b), and Barclay et al. (2006), which is dividend-to-asset ratio.68

The distribution of dividends is truncated with a zero dividend as its lower

bound. This necessitates the use of Tobit analysis which is a robust method for dealing

with a truncated distribution.69 Furthermore, in Oman as well as in other countries, there

68 We did not use the payout ratio to avoid the problems of negative payout ratios that results from negative earnings or excessively high payout ratios when income is close to zero (Schooley and Barney (1994)). In Fact, Aivazian et al. (2003b, p. 378) state that “the dividend payout ratio is highly unstable and nonnormal as earnings get close to zero; consequently, it is not useful as a dependent variable in cross-sectional regressions.” 69 See Olsen (1987) for a more detailed discussion of the Tobit model.

180

are some firms that pay dividends and others that do not. Even those that pay dividends

do not pay them continuously. This creates a censoring problem (Kim and Maddala

(1992)). This requires the use of Tobit Model (Anderson (1986), Kim and Maddala

(1992), and Huang (2001a, 2001b)). Moreover, our use of Tobit regression to examine

dividend policy is consistent with previous research by Kim and Maddala (1992),

Barclay et al. (1995), Dickens et al. (2002), Manos (2002), Bebczuk (2004), Al-Malkawi

(2005), Trojanowski and Renneboog (2005), among others.

5.4.2. Payment of Dividends

Omani firms tend to attract investors by distributing large dividends. Most of the

profitable Omani firms distribute dividends as a means of rewarding investors for

holding their securities. Stock repurchase is a rare phenomena in Oman, however some

firms supplement their cash dividends distributions with stock dividends.70

In Oman, most profitable companies distribute 100% of their profits as cash

dividends. This led the CMA to issue a circular (number 12/2003) arguing that firms

should retain some of their earnings for “rainy days”. This circular also requires firms to

have a clear policy of dividends and to disclose it in their financial reports. With this

regard, the circular states that

“…studies have shown that the majority of Omani public joint stock companies

currently operate with a dividend cover of 100% of its available profits assigned to

dividends…We are all required to set out a clear cut dividend policy with a view to the

70 It is possible for Omani companies to buy back their shares provided that they submit an application to the CMA where they have to list the reasons for buying back their shares.

181

long term expansion of the company by striking the right mix to meet both good

housekeeping practice (retention of some earnings appropriate to the economic

conditions) and the understandable desire of shareholders for immediate returns. CMA

calls upon public joint stock companies to adopt prudent policies in cash dividends and

to disclose the same in the annual report of the board of directors attached to the

financial statements.”

Table 5.2. Dividend Payout Ratio for All, Financial, and Non-Financial Firms over the Period 1989-2004. The table presents the mean and the standard deviation for firms listed at the MSM for each year from 1989-2004. Furthermore, the table also shows the mean and standard deviation for financial and non-financial firms during the same period. In panel A, we present the results for all firms including both dividend paying and non-paying firms. In panel B, we report the results for dividend paying firms. Panel A: All Firms

All

Financials

Non-Financials

Year Mean StDev Mean StDev Mean StDev 1989 42% 44% 47% 30% 40% 48% 1990 66% 205% 94% 279% 36% 42% 1991 43% 43% 49% 47% 39% 41% 1992 47% 82% 32% 39% 55% 96% 1993 134% 701% 46% 35% 171% 837% 1994 52% 85% 45% 34% 56% 98% 1995 41% 55% 49% 49% 39% 58% 1996 39% 75% 37% 35% 40% 87% 1997 32% 46% 19% 30% 37% 51% 1998 29% 177% 20% 31% 32% 206% 1999 29% 162% 25% 59% 30% 186% 2000 63% 400% 24% 49% 76% 466% 2001 35% 181% 15% 30% 42% 209% 2002 49% 249% 33% 52% 54% 289% 2003 34% 142% 60% 142% 25% 141% 2004 57% 262% 58% 139% 56% 295%

Overall period 46% 182% 41% 67% 48% 197% Observations 1514 437 1077

182

Panel B: Dividend Paying Firms All Financials Non-Financials

Year Mean StDev Mean StDev Mean StDev 1989 70% 35% 60% 19% 76% 41% 1990 117% 263% 149% 343% 72% 30% 1991 71% 33% 80% 32% 66% 33% 1992 86% 94% 72% 18% 91% 111% 1993 225% 902% 65% 20% 312% 1121% 1994 90% 95% 62% 22% 106% 115% 1995 76% 54% 70% 44% 80% 60% 1996 73% 90% 58% 26% 81% 110% 1997 63% 48% 43% 32% 70% 51% 1998 159% 394% 55% 25% 281% 571% 1999 185% 378% 96% 81% 258% 504% 2000 256% 787% 70% 62% 371% 991% 2001 130% 333% 49% 37% 166% 396% 2002 122% 385% 55% 58% 166% 492% 2003 86% 218% 123% 187% 69% 232% 2004 151% 412% 138% 189% 157% 481%

Overall period 122% 283% 78% 75% 151% 334% Observations 806 261 545

As with other Arab countries, Omani investors seem to prefer to receive periodic

income in the form of dividends (Bolbol and Omran (2004)). For the entire sample,

Panel A of Table 5.2 shows that the average payout ratio is around 46%. When the zero

dividend observations are removed, the average payout ratio increases considerably to

122% (Panel B). This is much higher than the payout ratio reported by Fazzari,

Hubbard, and Petersen (1988), Kaplan and Zingales (1997), and Aivazian et al. (2006)

samples of US firms. It is also higher than 23.3% reported by Chen and Dhiensiri

(2005) for New Zealand. Note that the payout ratio for non-financial firms is higher

than that for financial firms. The standard deviation of the payout ratio exhibits a

similar pattern.

183

5.4.3. Descriptive Statistics71

Table 5.3 provides summary statistics for two measures of dividend policy for

non-financial firms. As in Aivazian et al. (2003b), we report the ratio of aggregate

dividend to total assets to avoid the problems that may exist with the divided yield.

Table 5.3. Descriptive Statistics for Non-Financial Firms The table presents descriptive statistics for all non-financial firms listed at the MSM for the years 1989-2004. The observations are 1057. The variables are dividend yield (DIVYLD), dividend-to-asset ratio (DIV/TA), profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB).

Variable Mean Median Standard Deviation Minimum Maximum DIVYLD 0.0318 0.0000 0.0779 0.0000 0.7565 DIV/TA 0.0226 0.0000 0.0423 0.0000 0.2903 PROFIT 0.1137 0.0647 0.2623 -1.2994 3.4059 LOGS 6.3180 6.3845 0.7677 2.6532 8.5063

DR 0.6380 0.5641 0.5975 0.0003 8.1240 STOCKS 2.5045 2.4829 0.5877 0.6990 4.4273

DROI 0.0599 0.0208 0.1315 0.0000 1.5080 GOVOWN 0.1608 0.0000 0.3676 0.0000 1.0000

AGE 9.7133 8.0000 7.1324 0.0000 30.0000 TANG 0.3591 0.2816 0.4415 0.0000 0.9521

MB 1.5475 1.2844 4.2188 -33.2831 49.2872

As can be seen in Table 5.3, Omani firms have an average dividend yield of

3.18%72 and a market-to-book ratio of 155%. The profitability of non-financial Omani

firms as reflected in the ratio of earnings before interest and taxes to total assets is

around 11.37%. Consistent with our analysis in Chapter 2, the figures reported show

that non-financial Omani firms are highly levered with a debt ratio of around 63.80%.

71 We present the correlation matrix and the VIF for both financial and non-financial firms in Table E1 in Appendix E. All the VIFs are less than the standard cutoff value of ten, indicating that multicollinearity does not appear to be a significant factor. 72 The dividend yield is calculated from a sample that contains both dividend paying and non-dividend paying firms which may underestimate it.

184

This is much higher than the debt ratio for most of the countries reported in Aivazian et

al. (2003b) including the US. However, business risk (standard deviation for return on

investment) in Oman is similar to the emerging countries reported in Aivazian et al.

(2003b).

Table 5.4 describes the sample for financial firms. The figures reported show

that the dividend yield is slightly higher for financial firms with a value of 3.39%.

Similarly, the standard deviation of return on investment is larger for financial firms.

However, government ownership in financial firms is smaller than that for non-financial

firms. Likewise, the profitability and growth of financial firms is less than that for non-

financial firms. The results also show that financial firms are highly levered with a debt

ratio of 62.66% which is similar to that reported for non-financial firms.

Table 5.4. Descriptive Statistics for Financial Firms The table presents descriptive statistics for all financial firms listed at the MSM for the years 1989-2004. The observations are 413. The variables are dividend yield (DIVYLD), dividend-to-asset ratio (DIV/TA), profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB).

Variable Mean Median Standard Deviation Minimum Maximum DIVYLD 0.0339 0.0000 0.0582 0.0000 0.6940 DIV/TA 0.0178 0.0000 0.0296 0.0000 0.1694 PROFIT 0.0519 0.0450 0.2299 -1.1177 3.1833 LOGS 6.3609 6.4294 0.8510 2.5855 8.0593

DR 0.6266 0.5982 0.8276 0.0010 9.1872 STOCKS 2.7932 2.8633 0.5521 1.1139 4.4760

DROI 0.0769 0.0134 0.2837 0.0000 5.0525 GOVOWN 0.1501 0.0000 0.3576 0.0000 1.0000

AGE 9.4165 7.0000 7.1388 0.0000 31.0000 TANG 0.0365 0.0033 0.1316 0.0000 0.9273

MB 1.4082 1.0848 2.3499 -14.7437 31.3345

185

Table 5.5 reports summary statistics on cash dividends for non-financial firms

for each year from 1989-2004. In most cases, the number of non-financial firms that pay

cash dividends changes from one year to the next with the highest number of firms

paying cash dividends in 2004 and the lowest in 1990. Overall, around 50% of the firm-

year observations have zero dividends.

Table 5.5. Number and Fraction of Non-Financial Firms Paying Dividends The table presents the number of firms that pay dividends (and the percentage of firms that pay dividends) as well as the number of firms that do not pay dividends (and the percentage of firms that do not pay dividends) for all non-financial firms listed at the MSM for each year from 1989-2004.

Year No Dividend Percentage Dividend Percentage Total 1989 16 0.4848 17 0.5152 33 1990 16 0.5000 16 0.5000 32 1991 14 0.4118 20 0.5882 34 1992 14 0.4000 21 0.6000 35 1993 18 0.4500 22 0.5500 40 1994 21 0.4773 23 0.5227 44 1995 29 0.5179 27 0.4821 56 1996 30 0.5085 29 0.4915 59 1997 23 0.3651 40 0.6349 63 1998 60 0.6522 32 0.3478 92 1999 60 0.6000 40 0.4000 100 2000 59 0.5900 41 0.4100 100 2001 51 0.5313 45 0.4688 96 2002 50 0.5319 44 0.4681 94 2003 35 0.3846 56 0.6154 91 2004 30 0.3409 58 0.6591 88

Observations 526 531 1057

Table 5.6 presents summary statistics on cash dividends for financial firms.

There are some notable differences to those reported for non-financial firms. For

instance, most financial firms distribute dividends. The percentage of financial firms

that pay dividends (62%) is higher than that for non-financial firms (50%). While the

186

lowest percentage of firms-year observations that pay dividends for non-financial firms

occurs in 1998, the lowest for financial firms is in 1992. The highest percentage occurs

in 2003.

Table 5.6. Number and Fraction of Financial Firms Paying Dividends The table presents the number of firms that pay dividends (and the percentage of firms that pay dividends) as well as the number of firms that do not pay dividends (and the percentage of firms that do not pay dividends) for all financial firms listed at the MSM for each year from1989-2004.

Year No Dividend Percentage Dividend Percentage Total 1989 3 0.2143 11 0.7857 14 1990 5 0.2941 12 0.7059 17 1991 7 0.3889 11 0.6111 18 1992 10 0.5556 8 0.4444 18 1993 5 0.2941 12 0.7059 17 1994 5 0.2778 13 0.7222 18 1995 6 0.2727 16 0.7273 22 1996 10 0.3846 16 0.6154 26 1997 13 0.4643 15 0.5357 28 1998 12 0.3529 22 0.6471 34 1999 15 0.4054 22 0.5946 37 2000 17 0.4857 18 0.5143 35 2001 18 0.5294 16 0.4706 34 2002 8 0.2424 25 0.7576 33 2003 6 0.2000 24 0.8000 30 2004 16 0.5000 16 0.5000 32

Observations 156 257 413

5.5. Determinants of Dividend Policy

We employ a Tobit regression to examine the determinants of dividends policy

for financial and non-financial firms using dividend yield as the dependent variable.73

As a robustness check, we re-estimate our Tobit model using the ratio of the aggregate

73 It is not possible to estimate conditional fixed effects for tobit models because a sufficient statistic allowing the fixed effects to be conditioned out of the likelihood does not exist (Becher, Campbell, and Frye (2005)).

187

dividend to total assets instead of the dividend yield. The results are insensitive to this

measure of dividend policy.74

While there are some common factors (see Table 5.7) that affect the dividend

policy of both financial and non-financial firms, there are also factors that affect only

non-financial firms (see Table 5.8). For example, there are six determinants of dividend

policy for non-financial firms, while there are only three factors that affect the dividend

policy of financial firms. The common factors that affect the dividend policy of both

financial and non-financial firms are profitability, size, and business risk. Leverage,

government ownership, and age affect dividend policy of non-financial firms only. On

the other hand, agency costs, tangibility, and growth are insignificant for both financial

and non-financial firms indicating that these factors are not important determinants of

dividend policy in Oman. The fact that agency costs do not appear to have an effect on

dividend policy of both financial and non-financial firms is not surprising since we

argued earlier that Omani firms are highly levered through bank loans and this renders

the role of dividends in reducing the agency costs less important. We next describe the

results for non-financial and financial firms in greater detail.

5.5.1. Non-Financial Firms

Table 5.7 reports the results for the factors that explain dividend policy for the

non-financial firms. We find that all of the variables are statistically significant except

for agency costs, tangibility, and growth factors.

74 As a robustness check, we estimate a random effects tobit regression. The results are qualitatively similar to those obtained using tobit regression. See Table E2 in Appendix E for the results of non-financial firms and Table E3 for financial firms.

188

We test the overall significance of the model using the Wald test, which has a

chi-square (χ2) distribution under the null hypothesis that all the exogenous variables are

equal to zero. The χ2 statistic of the Wald test for dividend yield is 214.31 (p-value =

0.0000) and 291.79 (p-value = 0.0000) for the dividend-to-asset ratio. This indicates

that the explanatory power of both models is significant at the one percent level. We

next describe the statistically significant factors in more detail.

Table 5.7. Tobit Regression for the Determinants of Dividend Policy of Non-Financial Firms. We estimate tobit regressions for all non-financial firms listed at the MSM during 1989-2004. The dependent variables are the dividend yield and the dividend-to-asset ratio. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics.

Dividend Yield

Dividend-to-Asset Ratio Variable

Coefficient T-Statistic Coefficient T-Statistic C -0.5147*** -7.8937 -0.2648*** -7.8420 PROFIT 0.1128*** 2.7588 0.0947*** 4.5006 LOGS 0.0898*** 7.8297 0.0434*** 7.3029 DR -0.0823*** -3.9707 -0.0677*** -5.9694 STOCKS -0.0338 -1.4866 -0.0052 -0.8543 DROI -0.4370*** -4.6890 -0.2529*** -5.2399 GOVOWN 0.0008** 2.0981 0.0003* 1.6406 AGE 0.0016* 1.7280 0.0015*** 3.1758 TANG -0.0199 -1.2222 -0.0116 -1.3573 MB -0.0008 -0.4706 0.0010 1.2529 No of Observations 1,057 1,057 Log Likelihood -102.8745 123.5742 Wald Test [χ2 (9)]a 214.3100 291.7900 P-value 0.0000 0.0000 *, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom.

189

Profitability

Profitable firms are hypothesized to be more able to pay dividends. Our results

are in line with our hypothesis. In particular, the coefficients on profitability (PROFIT)

are positive and statistically significant at the one percent level whether we use dividend

yield or dividend-to-asset ratio. This result is similar to Lintner (1956, p. 107) where he

stated that “…net earnings were the dominant element which determined current

changes in dividends”. It is also consistent with the results documented by Jensen et al.

(1992), Han et al. (1999), Fama and French (2001, 2002), and Aivazian et al. (2003a,

2006).

Size

Larger firms have easier access to capital markets and face lower transaction

costs compared to smaller firms (LIoyd et al. (1985), Holder et al. (1998), Fama and

French (2002), Aivazian et al. (2006), among others). Accordingly, we hypothesized a

positive relationship between dividends and size. Our results are consistent with this

prediction. This result is consistent with those reported by Redding (1997), Fama and

French (2001), and Aivazian et al. (2006).

Leverage

Highly levered firms depend on external financing to a greater extent than the

one with lower leverage ratios, because leverage produces fixed charge requirements.

Consequently, levered firms should pay fewer dividends. We test this hypothesis using

the debt ratio as a surrogate for leverage. As predicted, the coefficients on leverage

190

(DR) are negative and statistically significant at the one percent level. This finding

accords with the results of DeAngelo and DeAngelo (1990), Jensen et al. (1992), and

Aivazian et al. (2003b, 2006).

Business Risk

Risky firms should pay fewer dividends. Hence, we predict a negative

association between dividends and business risk. To test this hypothesis, we utilize the

standard deviation of return on investment as proxy for business risk. Our results are

consistent with this prediction.

Government Ownership

In Oman, there are many firms where the government is a controlling

shareholder. We use a dummy variable which is equal to one in firms where

government has 10% or more of the shares. We predict a positive association between

dividends and government ownership. Our hypothesis is based on the argument that

government-controlled firms are subject to “double agency costs”. As predicted, the

estimates of government ownership (GOVOWN) are positive and significant. Our

findings are consistent with those reported by Gul (1999) who examines dividend policy

in Shanghai Stock Exchange and find that government-controlled firms tend to have

large payout ratios. The results are also in line with those reported by Gugler (2003)

who used data from Austria. His tests show a positive association between dividend

yield and government ownership. They are also consistent with the evidence

191

documented by Wei, Zhang, and Xiao (2003) for China and Carvalhal-da-Silva and Leal

(2004) for Brazil.

Maturity Hypothesis

Mature firms experience a contraction in their growth which may result in a

decline in capital expenditure. As a result, these firms should have more free cash flow

to pay in dividends. Hence, we should observe a positive association between dividends

and maturity. As a surrogate for maturity, we use the firm age defined as the difference

between the current year of the observation and the year of incorporation. Consistent

with our predictions, the coefficients for age are positive and significant. Our results are

consistent with a recent finding by Salas and Chahyadi (2005) who report evidence that

maturity is a significant determinant of dividend policy.

5.5.2. Financial Firms

Table 5.8 presents the results for the factors that influence dividend policy of

financial firms. As mentioned previously, there are three determinants of dividend

policy of financial firms which are profitability, size, and business risk. Other factors

such as leverage, agency costs, government ownership, age, tangibility, and growth

seem to not have any significant impact on dividend policy of financial firms. All the

significant factors have the hypothesized signs. We described the results of all the

significant factors for dividend policy of non-financial firms above. The same analysis

applies for financial firms.

192

Table 5.8. Tobit Regression for the Determinants of Dividend Policy of Financial Firms. We estimate tobit regressions for all financial firms listed at the MSM during 1989-2004. The dependent variables are the dividend yield and the dividend-to-asset ratio. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics.

Dividend Yield

Dividend-to-Asset Ratio Variable

Coefficient T-Statistic Coefficient T-Statistic C -0.2621*** -4.8914 -0.1003*** -3.3994 PROFIT 0.1958*** 3.3637 0.2004*** 5.6068 LOGS 0.0446*** 4.5957 0.0191*** 3.6007 DR -0.0035 -0.5396 0.0002 0.0459 STOCKS -0.0110 -0.9763 -0.0090 -1.4456 DROI -0.2298*** -2.8843 -0.1384*** -3.0355 GOVOWN 0.0001 0.2748 -0.0001 -0.3533 AGE 0.0009 1.0127 -0.0006 -1.2642 TANG -0.0733 -1.3227 -0.0449 -1.4645 MB -0.0009 -0.3848 0.0027 1.2238 No of Observations 413 413 Log Likelihood 75.8372 158.1734 Wald Test [χ2 (9)]a 97.0100 101.2400 P-value 0.0000 0.0000 *, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom.

5.6. Determinants of the Decision to Pay Dividends

In this section, we examine the likelihood that a firm will pay dividends. In

order to do so we estimate probit regressions, where the dependent variable is binary

variable equal to one if the firm pays dividends and zero otherwise.75,76 As regressors,

75 Probit models do not lend themselves to the inclusion of fixed effects. In this vein, Baltagi (1995) notes that “... the probit model does not lend itself to a fixed effects treatment.” Similarly, Maddala (1987, p. 285) states that “the fixed effects probit model is difficult to implement computationally.” 76 We also estimate a random effects probit regression and find similar results to those obtained using probit regression. See Table E4 in Appendix E for the results of non-financial firms and Table E5 for the results of financial firms.

193

we employ the same variables as described in Table 5.1. The objective of the analysis is

to examine whether the factors that determine the amount of dividends paid also have an

impact on the probability that a firm will pay dividends.

Our results for the determinants of the decision to pay dividends are consistent

with those reported for the determinants of dividend policy. In particular, we find that

the factors that influence the probability to pay dividends are the same factors that

determine the amount of dividends paid.

5.6.1. Non-Financial Firms

The results presented in Table 5.9 shows that all the factors considered for

examination are significant except for agency costs, tangibility, and growth. The six

factors that we find previously influencing the amount of dividends paid are the same

factors that affect the likelihood to pay dividends. For example, the coefficient on size is

significant at all reasonable levels with a positive sign indicating that larger firms are

more likely to pay dividends. Likewise, factors including profitability, government

ownership, and age are all significant with a positive sign. On the other hand, risky

firms and firms with high debt ratios are less likely to pay dividends.

Factors including agency costs, tangibility, and growth seem to have no effect on

the decision to pay dividends, consistent with our earlier results from the Tobit model.

The overall explanatory power of the model as evaluated by the Wald test is significant

at the one percent level.

194

Table 5.9. Probit Regressions to Explain Which Non-Financial Firms Pay Dividends We estimate probit regressions for all non-financial firms listed at the MSM during 1989-2004. The dependent variable is a binary variable that equals to one if the firm pays dividends and zero otherwise. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -4.0045*** -8.9004 PROFIT 0.7110** 2.5546 LOGS 0.6858*** 8.5343 DR -0.9218*** -6.0088 STOCKS -0.1319 -1.5297 DVROI -3.6518*** -5.4014 GOVOWN 0.0054* 1.7301 AGE 0.0222*** 3.3317 TANG -0.1523 -1.3056 MB -0.0003 -0.0234 No of Observations 1,057 Log Likelihood -537.3487 Wald Test [χ2 (9)]a 295.3000 P-value 0.0000

*, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom.

5.6.2. Financial Firms

We estimate our Probit model of the likelihood to pay dividends on our sample

of financial firms. The results are presented in Table 5.10 and show that there are three

factors that influence the likelihood to pay dividends which are profitability, size, and

business risk. These factors are the same as the one reported for the determinants of the

amount of dividends. The coefficients on leverage, agency costs, government

ownership, age, tangibility, and growth variables are not statistically different from zero

indicating that these variables do not have a significant impact on the decision to pay

dividends.

195

Table 5.10. Probit Regressions to Explain Which Financial Firms Pay Dividends We estimate probit regressions for all financial firms listed at the MSM during 1989-2004. The dependent variable is a binary variable that equals to one if the firm pays dividends and zero otherwise. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -2.6748*** -4.1903 PROFIT 2.2372*** 3.4718 LOGS 0.5411*** 4.6679 DR 0.0644 0.6742 STOCKS -0.2596 -1.5432 DROI -2.2082*** -2.6152 GOVOWN 0.0087 1.1521 AGE -0.0055 -0.4975 TANG -0.9364 -1.4410 MB 0.0041 0.1552 No of Observations 413 Log Likelihood -238.4264 Wald Test [χ2 (9)]a 95.5700 P-value 0.0000


A comparison between the factors that influence the probability of paying

dividends in the financial and non-financial firms reveal that there are three common

factors. These factors are profitability, size, and business risk. Leverage, government

ownership, and age have a strong impact on the decision to pay dividends for non-

financial firms and no effect on financial firms. On the other hand, agency costs,

tangibility, and growth do not appear to have any impact on both financial and non-

financial firms. As mentioned previously, the fact that we find agency cost is not

important driver of Omani firm's dividend policy is not surprising since Omani firms

196

have high bank loans which reduce the role of dividends in alleviating agency problems.

The chi-square (χ2) statistic is 95.57 with a p-value 0.0000 indicating that we are able to

reject the null hypothesis that the parameters in the regression equation are jointly equal

to zero.

In sum, the factors that influence the amounts of dividends are the same factors

that determine the decision to pay dividends for both financial and non-financial firms.

5.7. The Lintner Model77

In a frequently cited study, Lintner (1956) develops a quantitative model to test

for the stability of dividend policy where he hypothesizes the following relationship

between dividends and earnings:

tt rED =* , (5.2)

where tD* is the target level of dividends for any year t, r is the target payout ratio, and

Et is the firm’s net earnings in year t. In addition, Lintner (1956) also predicts that a

firm will only partially adjust to the target dividend level in any given year, so the

change in dividend payments from year t-1 to year t is given by:

ttttt uDDcDD +−+=− −− )( 1*

1 α (5.3)

77 Linter (1956) studies the dividend patterns of 28 well-known, established companies in the US. He reports evidence that firms maintain target dividend payout ratio and adjust their dividend policy to this target. He also documents that firms pursue a stable dividend policy and gradually increase dividends given the target payout ratio. Recently, Brav et al. (2005) survey 384 financial executives and conduct in-depth interviews with an addition 23 to determine the factors that influence dividend policy and share repurchase decisions. Their results “indicates that maintaining the dividend level is a priority on par with investment decisions…In contrast to Lintner’s era, we find that the target payout ratio is no longer the preeminent variable affecting payout decisions”.

197

where α is the intercept term, c is the speed of adjustment coefficient, u is the error term,

tD* is the target dividend payment in period t, Dt is the actual dividend payment in

period t and Dt-1 is the actual dividend payments in period t-1.

Substituting rEt for the target dividend payment ( tD* ) in equation (5.3), we arrive at the

following model,

ttttt uDEDD +++=− −− 1211 ββα (5.4)

where β1 = cr and β2 = -c.

The constant term (α) is expected to have a positive sign “to reflect the greater

reluctance to reduce than to raise dividends” Lintner (1956, p. 107). The speed of

adjustment coefficient (c) reflects that stability of dividends and measures the speed of

adjustment toward the target payout ratio (r) in response to earnings changes. The value

c reflects the dividend smoothing behaviour of firms to changes in the level of earnings.

A higher value of c indicates less dividend smoothing and vice versa. Thus, a

conservative firm will have a lower adjustment rate, while a less conservative firm will

have a higher adjustment rate.

As shown by Lintner, equation (5.4) can be rewritten as:

tttt uDccrED +−++= − )1()1(α (5.5)

This model implies that firms set their dividends in accordance with current level of

earnings, and that changes in dividends do not correspond exactly with the changes in

earnings.

To test whether dividend policy in Oman is stable, we follow Fama and Babiak

(1968) and use earnings per share (EPS) and dividends per share (DPS) rather than total

earnings as follows:

198

tttt uEPSDPSDPS +++= − 211 ββα (5.6)

where DPSt is the dividend per share for period t, EPSt is the earning per share for period

t, and u is the error term. Fama and Babiak argue that per share data are more

appropriate for this test than the aggregate data used by Lintner. Indeed, almost all

studies conducted since Lintner’s study employ per share data rather than aggregate

data. This model has been used by many scholars to examine the stability of dividends

such as Brittan (1964, 1966), Fama and Babiak (1968), Fama (1974), Dewnter and

Warther (1998), Adaoglu (2000), Aivazian et al. (2003a), Omet (2004), Naceur et al.

(2005), among others.

We document in Chapter 4 that Omani firms frequently change their dividends.

In this section, we examine the stability of dividend behaviour in Oman using the

Lintner model. Since there are some firms in Oman that do not pay dividends, this

creates a censoring problem which needs to be addressed in estimating the Lintner

model. In this case, previous research suggested the use of the Tobit model (Anderson

(1986), Kim and Maddala (1992), and Huang (2001a, 2001b)). We also use a Tobit

model to test the stability of dividends in Oman.78

78 We also use a random effects tobit regression. The tobit and random effects tobit results are very similar for financial firms (see Table E7). For non-financial firms, the random effects tobit regression shows a more rapid speed of adjustment than the tobit (see Table E6). Still, the results indicate that the lagged dividend per share is more important than the current earnings per share in determining the current dividend per share.

199

5.7.1. Empirical Results for the Lintner Model79

We estimate the Lintner model for both financial and non-financial firms.80 For

both, we find the lagged DPS and EPS are statistically significant with a positive sign.

The constant term for both financial and non-financial firms is negative and significant

indicating that Omani firms are not reluctant to cut dividends.81 The major results

obtained from the analysis are that the speed of adjustment differs substantially between

financial and non-financial firms. While we find that non-financial firms adopt a policy

of smoothing dividends, this is not the case for financial firms. In fact, we find that

financial firms do not have a stable dividend policy.82 We evaluate the explanatory

power of the model via the Wald test and we find that for both financial and non-

financial firms the chi-square is significant at the one percent level. We next review the

Lintner model for financial and non-financial firms in more detail.

79 Several studies report evidence that supports Lintner’s (1956) behavioural model such as Fama and Babiak (1968), Baker et al. (1985), Baker and Powell (1999). Benartzi et al. (1997, p. 1032) conclude that “…Lintner’s behavioral model of dividends remains the best description of the dividend setting process available”. 80 Lintner’s model has been used by many studies in different countries including Chateau (1979) in Canada, Shevlin (1982) in Australia, McDonald et al. (1975) in France, Leither and Zimmermann (1993) in West Germany, UK, France, and Switzerland, Ariff and Johnson (1994) in Singapore, Lasfer (1996) in UK, Dewenter and Warther (1998) in Japan and US, Adaoglu (2000) in Turkey, Pandey (2003) in Malaysia, Stacescu (2004) in Switzerland, Naceur et al. (2005) in Tunisia, and Al-Malkawi (2005) for Jordan. 81 The negative constant reported in this chapter is consistent with the results documented by Kim and Maddala (1992), Huang (2001a, 2001b), and Al-Malkawi (2005) who utilize Tobit regression to estimate the Lintner model. 82 Aivazian et al. (2006) show that the type of corporate debt plays an important role in determining the firms’ dividend policy. In particular, they find that firms with access to public debt market are more likely to pay dividends and subsequently to follow a smoothing dividend policy than firms that rely on bank debt.

200

5.7.1.1. Non-Financial Firms

The results presented in Table 5.11 show that both the coefficients on lagged

DPS and EPS are statistically significant with a positive sign. But the generally higher

coefficient and the associated t-statistic of the lagged DPS imply the greater importance

of past dividend in deciding the dividend payment. These results are consistent with

Lintner and suggest that the lagged DPS and EPS are important factors that affect the

decision to pay dividends. The coefficient on the constant is also statistically significant

with a negative sign. This indicates that Omani firms are not reluctant to cut dividends,

inconsistent with Lintner (1956).

The objective of using the Lintner model in this chapter is to examine whether

Omani firms follow stable dividend policies. Consequently, we are interested in the

speed of adjustment. The speed of adjustment reflects how quickly the firms adjust

dividends towards the target ratio; the higher the speed of adjustment, the less the

smoothness, and the less stability in dividends. In our case, the speed of adjustment is

0.2535 which indicates that Omani non-financial firms do smooth their dividends. This

is close to the value of 0.30 obtained by Lintner for the US. Recently, Brav et al. (2005)

find that the mean speed of adjustment for US companies with valid Compustat data is

0.67, 0.4, and 0.33 for the 1950-1964, 1965-1983, and 1984-2002 periods, respectively.

Our estimate is lower than that for the first period and close to those reported for the

other two periods in Brav et al. Likewise, our speed of adjustment is similar to the 0.25

documented by Goergen, Renneboog, and Correia da Silva (2004) for Germany.

However, it is lower than the 0.66 reported by Stacescu (2004) for Switzerland. For

emerging markets, our speed of adjustment is much lower than the 0.71 obtained by

201

Pandey and Bhat (2004) for India. It is also considerably lower than the 0.52

documented by Omet (2004) for Jordan and the 1.00 reported by Adaoglu (2000) for

Turkey.

Table 5.11. Lintner Model Estimates for Non-Financial Firms We estimate Tobit regression for all non-financial firms listed at the MSM over the period 1989-2004. The dependent variable is the dividend per share. The explanatory variables are the lagged DPS and the current EPS. The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.4121*** -13.1435 DPS-1 0.7465*** 14.6388 EPS 0.1767*** 6.4442 No of Observations 969 Log Likelihood -579.9871 Wald Test [χ2 (2)]a 238.0600 P-value 0.0000


Our result of a stable dividend policy is consistent with the results reported in

several studies including Shevlin (1982), Roy and Cheung (1985), Thomson and Watson

(1989), Annuar and Shamsher (1993), Leither and Zimmermann (1993), Ariff and

Johnson (1994), Papaioannou and Savarese (1994), Kato and Lowentein (1995), Kester

and Isa (1996), Lasfer (1996), Chiang, Davidson, and Ckunev (1997), Dewenter and

Warther (1998), Aivazian et al. (2003b), and Bancel et al. (2005).

Another variable of interest is whether Omani non-financial firms have a target

payout ratio or not. Lintner (1956) hypothesizes that firms set a long-term target payout

ratio and move gradually towards the target. We calculate the target payout ratio and

202

find that Omani non-financial firms have a target payout ratio of 0.6970.83 This value is

higher than the 0.50 reported by Lintner for the US. It is also higher than the 0.459

documented by Fama and Babiak (1968).

5.7.1.2. Financial Firms

We re-estimate the Lintner model on our sample of financial firms. The results

are reported in Table 5.12. Similar to the results obtained for non-financial firms, we

find that the coefficient on the lagged DPS and ESP are statistically significant with a

positive sign. The coefficient on the constant is also significant and negative indicating

that financial firms are not reluctant to cut dividends. However, the speed of adjustment

is much higher for financial firms with a value of 0.9412. This indicates that Omani

financial firms do not smooth their dividends. Rather, they change their dividends

frequently. In short, Omani financial firms do not follow a stable dividend policy. With

regard to the target payout ratio, it is around 0.5668. This finding indicates that financial

firms do have a target dividend payout ratio that they move quickly towards.

In sum, there is a major difference concerning the stability of dividends between

financial and non-financial firms. Financial firms do not follow a stable dividend policy

while non-financial firms smooth their dividends. Regarding the reluctance to cut

dividends, both financial and non-financial firms are not reluctant to cut dividends.

83 We calculate the target payout ratio as (the coefficient on EPS divided by the speed of adjustment).

203

Table 5.12. Lintner Model Estimates for Financial Firms We estimate Tobit regression for all financial firms listed at the MSM over the period 1989-2004. The dependent variable is the dividend per share. The explanatory variables are the lagged DPS and the current EPS. The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.1457*** -7.3644 DPS-1 0.0588*** 2.7855 EPS 0.5335*** 46.8658 Observations 377 Log Likelihood -142.8506 Wald Test [χ2 (2)]a 509.3700 P-value 0.0000


5.8. Conclusion

We investigate dividend policy in a unique environment where firms distribute

almost 100% of their profits in dividends and firms are highly levered. We use a panel

data on a sample of Omani firms and take account of the zero observations using Tobit

and Probit models. Our study has four main objectives, namely (1) to identify the

factors that determine the amount of dividends, (2) to examine the likelihood that firm’s

pay dividends, (3) to apply the Lintner model to test the stability of dividend policy, and

(4) to outline the potential differences in dividend policy between financial and non-

financial firms.

Our results show that there are some common factors that determine dividend

policy for both financial and non-financial firms and there are other factors that affect

only non-financial firms. Specifically, there are six determinants of dividend policy for

non-financial firms, while there are only three factors that influence the dividend policy

of financial firms. The common factors are profitability, size, and business risk.

204

Government ownership, leverage, and age have a strong impact on the dividend policy

of non-financial firms but no effect on financial firms. Agency costs, tangibility, and

growth do not appear to have any effect on the dividend policy of either financial or

non-financial firms. The fact that agency costs is not an important determinant of

dividend policy is not surprising given that we document previously that Omani firms

are highly levered via bank debt where the role of dividends in alleviating the agency

problems is less important.

Our findings for the determinants of the decision to pay dividends are consistent

with those reported for the determinants of dividend policy. In particular, we find that

the factors that influence the probability to pay dividends are the same factors that drive

the amount of dividends paid.

With respect to the stability of dividend policy, we find that the speed of

adjustment differs substantially between financial and non-financial firms. While we

find that non-financial firms adopt a policy of smoothing dividends, this is not the case

for financial firms. In fact, financial firms do not have stable dividend policies.

205

Chapter 6: Conclusion

This dissertation examines four specific issues on capital structure and dividend policy.

The first issue examined concerns the determinants of capital structure dynamics. The

results show that Omani firms have high leverage ratios and the main source of debt is

short-term bank financing. The limited bond market leaves room for banks to play an

important role in financing Omani firms. Banks mainly provide short-term loans which

explain the high reliance of Omani firms on this form of financing.

We find robust evidence that stock price changes have a strong and primary

effect on observed market-based debt ratios. Firm’s capital structure seems to move

practically in line with that mechanistically induced by their stock returns. We also find

that firms show some tendency to nudge back to their old debt ratios. However, the

impact of stock returns dominates the effects of readjustment. Adding previously

popular determinates of capital structure has only modest economic impact on capital

structure dynamics. In essence, when we include other commonly used variables into

our model, stock returns subsume other factors. Nevertheless, there are non-stock return

variables that have both statistical and economic significance. For example, taxes show

some incremental explanatory power over five years. However, the impact of tax is far

less than that of stock returns. When used with bank debt, stock returns continue to

subsume other determinants of capital structure. We also find that adjustment costs are

unlikely to be the main reason behind our results. Our results are robust to different

estimation methods.

206

The second issue investigated is ex-dividend behaviour. The results reveal that

stock prices on the ex-dividend days fall by significantly less than the amount of

dividends and ex-day abnormal returns are significantly positive. We investigate

whether transaction costs and risk inhibit arbitrage. Our results show that neither is

significant. We also examine abnormal volume around the ex-days and find a reduction

in volume around the ex-day. These results do not support the short-term trading

hypothesis which predicts a positive abnormal volume around ex-days. We also test

Frank and Jagannathan’s (1998) model which argues that the ex-day premium deviate

from one due to the effects of bid-ask bounce. This is what we find. In particular, we

find that when midpoint prices are used instead of transaction prices, stock prices drop

by the full amount of the dividend on the ex-day. We also find that the ex-day abnormal

return is insignificantly different from zero. In general, our results demonstrate that the

microstructure of the Omani stock markets explain the ex-day pricing anomaly.

The third issue analyzed is the stock price reaction to dividend announcements.

The results show that market reacts strongly to announcements of changes in cash

dividends. Investors do care about the information transmitted by dividend

announcements. Firms that increase (decrease) their dividends have an increase

(decrease) in stock prices. Firms that have no change in their dividends experience

insignificant negative average abnormal returns, consistent with no change in dividends

being, on average, somewhat of a disappointment. These findings support the view that

dividends convey unique and valuable information to investors. These results contradict

the tax-based signaling models which argue that higher taxes on dividends relative to

207

capital gains are a necessary condition for dividends to have information and be

informative.

The final issue studied is the determinants and stability of dividend policy of

financial and non-financial firms. The results demonstrate that there are common

factors that affect the dividend policy of both financial and non-financial firms, and

there are others that affect only non-financial firms. For example, there are six

determinants of dividend policy for non-financial firms, while there are only three

factors that affect the dividend policy of financial firms. The common factors are

profitability, size, and business risk. Government ownership, leverage, and age have a

strong influence on the dividend policy of non-financial firms but no effect on financial

firms. On the other hand, agency costs, tangibility, and growth factors do not appear to

have any significant impact on the dividend policy of both financial and non-financial

firms. The fact that we find agency costs is not an important driver of dividend policy is

not surprising given that Omani firms have high bank debt. We also find that the

determinants of the decision to pay dividends are consistent with those reported for the

determinants of dividend policy. In particular, we find that the factors that influence the

probability of paying dividends are the same as those that determine the amount of

dividends paid. We document that the speed of adjustment differs substantially between

financial and non-financial firms. While we find that non-financial firms adopt a policy

of smoothing dividends, this is not the case for financial firms. In fact, we find that

financial firms do not have stable dividend policies.

208

Appendices

Appendix A

The Oman Economy and Its Financial Sector

A.1. Introduction

No economy can flourish unless an environment conducive to growth is

provided. Historically and empirically, a positive correlation exists between the health

of the overall economy and that of the financial sector, which implies that changes in the

financial sector affect the economy and more obviously changes in the economy affect

the market. In fact many studies document that banks and stock market development

affect economic growth (see Levine and Zervos (1998), Beck and Levine (2004), among

others). In developed economies, stock markets and financial institutions are considered

to be the main driver of economic activity due to the role they play in mobilizing

savings, allocating capital, financing investments, and monitoring firms (Demirguc-Kunt

and Levine (1999)). This may suggests that the activities of banks and the buying and

selling of shares on the market are extremely important for the allocation of capital

within economies. In a country like Oman, which depends on one major source of

income, effective allocation of scarce resources is of a paramount importance.

The major objectives of this appendix are threefold: First, to discuss the

performance and the unique characteristics of Oman, second, to describe the major

features of the Muscat Securities Market and third, to provide a brief description of the

financial sector in Oman. For these purposes, the focus is on the MSM and the debt

209

market, with an emphasis on those aspects of the MSM and debt market that are of

particular interest and relevance to the current study on capital structure and dividend

policy.84 The rest of the chapter is divided into four sections. A general overview of the

economy including exchange rate regime, interest rate structure, and international trade

and monetary policy is incorporated in section A.2. Section A.3 reviews the main

features of the Omani financial sector including the major characteristics of the market

such as the foundation of the market, structuring the capital market, listing and trading,

market capitalization, turnover, ownership structure, and the performance of MSM.

Section A.4 describes the taxation system in Oman. Section A.5 presents the main

features of the debt market in Oman and emphasizes the reasons for the debt market’s

underdevelopment. Finally, the structure of financing, which is divided into internal and

external sources, is presented in section A.6.

A.2. Overview of the Economy:

“The diversification of the economy, the development of the human skills, the effective

exploitation of the available natural resources and the creation of the suitable

conditions to encourage the private sector to perform a greater role in the growth of the

national economy all this will lessen our dependence on oil.”

His Majesty Sultan Qaboos bin Said, November 18, 1999

Oman is a small free market economy with a stable social, political, and

economic system, low taxation rates, steady economic growth, low inflation, a

manageable level of external debt, fairly liberal investment laws, a sustainable level of 84 A description of dividend policy is provided in Chapters 3, 4, and 5.

210

budget deficit, and no controls over capital movements. Like most other countries in the

Gulf region, most of Oman’s income is generated from petroleum extraction activities.

In terms of oil production, Oman is ranked 18th in the world. Oman’s proven oil

reserves are estimated at 5.5 billion barrels. Oil production declined from 299 million

barrels in 2003 to 285.4 million barrels in 2004. Average production per day thus

decreased from around 820,000 barrels per day in 2003 to 779,700 barrels per day in

2004. However, the dampening effects of oil production on the economy have been

more than offset by the high oil prices. The average oil price for Omani crude went up

from US $27.84 per barrel in 2003 to US $34.42 per barrel in 2004. Crude oil supplies

are expected to last at least 20 years, while ever increasing natural gas reserves will last

considerably longer.85’86

Oman’s economic performance depends primarily on the oil industry.87 In terms

of its share in total revenue, net oil revenue stood at 66% in 2004 against 70% in the

previous year. Oman’s nominal GDP has grown from around US$ 2.60 billion in 1993

to around US$ 24.82 billion in 2004.88 This growth was spurred by rising oil output and

services, in particular, by two large exports oriented projects- the Liquefied Natural Gas

(LNG) and the Salalah container port. As can be seen from Table A.1, 42% of the GDP

is comprised of petroleum extraction, of which 39.7% is derived from oil extraction.

Services comprised another 45%. GDP at current market prices witnessed a strong

rebound in 2004, in tandem with the acceleration in the world economy, and in response 85 The Oman economy data for 2005 is not yet available. 86 Oman’s gas reserves are estimated at 30.3 trillion cubic feet at the end of 2004. 87 Though oil is the major source of revenue, there are no oil producing companies listed at the MSM. The only oil related companies listed are the petrol filling stations which we call them oil companies in the thesis. 88 Preliminary data published by the Ministry of National Economy indicate that the nominal GDP grew by about 22% in 2005 to US$ 30.28 billion.

211

to the high oil prices as well as the impressive performance of the non-oil sectors. The

nominal GDP growth at 14.4% in 2004 indicates a robust revival in relation to the 6.9%

recovery in 2003 and the phase of slowdown in growth experienced during 2001 and

2002. Despite the 4.5% fall in the quantity of oil production, the petroleum activities

registered growth of 17.5% in 2004, which could be ascribed to the 23.6% increase in

average prices of Oman crude during 2004 over 2003. Similarly, non-petroleum sectors

including agriculture and services expanded by 12% in 2004 on top of 8% increase in

2003. Among the non-petroleum sectors, ‘Agriculture and Fishing’ contracted by 3%,

while ‘Industry’ and ‘Services’ improved by 21% and 10%, respectively.

Table A.1. The Omani Economy at Glance Category 1999 2000 2001 2002 2003 2004 % of

Total Crude Oil 5,983.80 9,394.70 8,076.90 8,058.40 8,373.00 9,852.00 39.70%Natural Gas

1,727.60 258.2 418.8 426.3 542.3 645.2 2.60%

Total Petroleum Activities

6,156.60 9,652.90 8,495.70 8,504.90 8,936.80 10,497.40 42.30%

Growth - 56.80% -12.00% 0.10% 5.10% 17.50% - Industry 1,272.20 1,708.10 2,333.30 2,273.40 2,624.60 3,176.50 12.80%Agriculture and Fishing

408.3 397.2 418.8 406 433.8 421.9 1.70%

Services 8,166.90 8,520.80 9,094.00 9,560.50 10,151.50 11,142.60 44.90%Total Non-petroleum activities

9,853.80 10,626.10 11,846.20 12,239.80 13,188.30 14,765.80 59.50%

Growth - 7.80% 11.50% 3.30% 7.70% 12.00% - Adjustment (import taxes, etc.)

-304.8 -417.1 -398.9 -446.6 -433.8 -446.7 -

GDP 15,705.60 19,861.90 19,943.00 20,298.20 21,691.30 24,816.50 100% Source: Ministry of National Economy Note: Figures are in US$ million

212

Oman’s financial sector has been considerably strengthened and transformed in

recent years with a modern financial system which facilitates sustainable development.

Banks and other non-bank financial intermediaries have participated in financial reforms

that have impacted favourable on the country’s growth. The financial sector mainly

comprises commercial banks and specialized banks. As at the end of 2004, the number

of commercial banks stood at 14, of which five are locally incorporated banks and nine

are branches of foreign banks. These 14 banks have a branch network of 330. There are

also three specialized banks in operation.

A.2.1. Exchange Rate Regime

Oman has adopted a fixed exchange rate regime, the Omani currency; the Rial

Omani has been pegged to the US dollar since 1973. For a small open economy, the

fixed exchange rate arrangement is perceived as desirable and appears to serve the

purpose well in the case of Oman. Theoretically, there is no right answer to the question

of whether a small country is better off with a fixed or flexible exchange rate system. In

the case of Oman, the economy is open, with around 80 percent openness as measured in

terms of ratio of traded goods to GDP. Oil is the major component of GDP and is a

major foreign exchange earner. Oil prices are fixed in US dollars, so the choice of fixed

exchange rate pegged to the US dollar appears to fit the economic conditions. The fixed

exchange rate regime has served Oman well over the years. The parity rate remained

firm all through, except one episode of devaluation in January 1986.

The exchange rate of Rial Omani was fixed at US dollar 2.8952 in 1973. With

the devaluation of around ten percent, the parity of Rial Omani was revised downwards

213

to US dollar 2.6008.89 The factors leading to the episode of devaluation were many,

though a crash in international oil prices was the most immediate and important reason.

As and when international oil prices nosedive, the balance of payments position, as well

as the government accounts, come under severe pressure. Over the last 30 years, oil

prices have fluctuated considerably and this has caused shocks to the external current

account balance and fiscal position of the nation. The government responded to these

shocks in many ways. In 1986, when the oil price touched an all time low, the currency

was devalued to correct the imbalance in current account and to set right the mismatch in

government receipts and payments, mainly by containing import demand.

The peg should be seen in the context of the country’s oil exports contracts fixed

in US dollars. Oman manages the fixed exchange rate through the balance of payments.

The movements in the balance of payments are directly related to the price of oil. In

fact, external shocks faced by Oman for the most part are associated with the behaviour

of the international oil price. When the oil price surges, there is a positive external

shock and when the international price of oil plummets, the balance of payments goes

into deficit.

Nowadays, the oil prices reached a record level especially in 2004. This sharp

increase in oil prices created a concern of inflation globally arising from the increase in

the cost of production. Even though the actual inflation in advanced countries did not

edge up much in 2004, the prices of tradable showed significant increase.90 For an open

economy like Oman, higher prices of tradable means higher imported inflation. Oman

89 This is the exchange rate used to convert the Omani Rials into US$ in the thesis. 90 Inflation remained low in 2004 at 0.4%, even though there was a reversal in the negative inflation trend that was experienced in the previous four years.

214

came under the pressure of higher import prices in 2004. Even though as per the WTO

estimates prices of traded goods rose by 11% in 2004, the increase in import prices were

much higher for Oman on account of the sustained depreciation of the US dollar against

the major international currencies. In view of the fixed peg to the US dollar, Oman’s

nominal effective exchange rate depreciated cumulatively by about 10% over 2003 and

2004.

A.2.2. Interest Rate Structure

Wide swings or disequilibrium in interest rates affects macroeconomic

performance adversely. While high interest rates discourage investment because new

investments become less profitable, interest rates below some equilibrium level do not

provide incentives for savers. Hence, an equilibrium level of interest rates balances

savings and investment in the economy. The interest rate in a country like Oman, which

has a fixed exchange rate, is determined by the interest rate in the country to whose

currency the domestic currency is pegged. The behaviour of domestic interest rates

generally follows the long run pattern of interest rates in the US. To the extent that

interest rates are out of alignment with US dollar rates, they generally cause capital

flows in and out of the country. However, differences do persist in interest rates mainly

in the short run, for considerations such as the rate of return on capital in the domestic

economy, level and state of bank liquidity, transaction costs, risk premium, etc.

The weighted average interest rates on deposits and lending and the spread

between them are given in Table A.2. The weighted average interest rate on Omani Rial

time deposits fell from 2.9% in 2002 to 2.4% in 2003 but remained more or less

215

Table A.2. Weighted Average Interest Rates (Percent per annum)

Deposits Lending Spread

End of Period

Private Sector

RO Time Deposits

(1)

Total RO Deposits

(2)

Total Deposits

(RO +FC*)

(3)

Private Sector RO Lending

(4)

Total RO Lending

(5)

Total Lending (RO + FC*) (6)

Spread

(4)-(1)

Spread

(5-(2)

Spread

(6)-(3) Mar-00 7.685 5.498 5.421 10.302 110.277 9.696 2.617 4.779 4.275 Jun-00 7.580 5.345 5.336 10.112 10.072 9.677 2.532 4.727 4.340 Sep-00 7.602 5.478 5.460 10.102 10.063 9.699 2.500 4.585 4.239 Dec-00 7.672 5.455 5.434 10.108 10.060 9.678 2.436 4.605 4.244 Mar-01 7.145 4.907 4.880 9.9411 9.900 9.385 2.796 4.993 4.505 Jun-01 6.617 4.203 4.116 9.514 9.472 8.773 2.879 5.269 4.657 Sep-01 5.699 3.720 3.616 9.466 9.425 8.434 3.767 5.705 4.818 Dec-01 4.469 2.856 2.753 9.392 9.234 7.866 4.923 6.378 5.113 Mar-02 3.573 2.247 2.170 9.129 8.948 7.531 5.556 9.701 5.361 Jun-02 3.346 1.860 1.830 8.954 8.806 7.420 5.608 6.946 5.590 Sep-02 3.096 1.813 1.784 8.790 8.702 7.351 5.694 6.889 5.567 Dec-02 3.003 1.673 1.646 8.806 8.549 7.229 5.803 6.876 5.583 Mar-03 2.815 1.540 1.522 8.736 8.479 7.200 5.921 6.939 5.678 Jun-03 2.664 1.363 1.357 8.579 8.267 7.026 5.915 6.904 5.669 Sep-03 2.477 1.324 1.294 8.535 8.373 7.075 6.058 7.049 5.781 Dec-03 2.345 1.261 1.260 8.491 8.237 6.920 6.146 6.976 5.660 Mar-04 2.253 1.144 1.184 8.423 8.125 6.852 6.170 6.981 5.668 Jun-04 2.255 1.114 1.170 8.253 8.011 6.711 5.998 6.897 5.541 Sep-04 2.324 1.096 1.169 8.029 7.814 6.589 5.705 6.718 5.420 Dec-04 2.350 1.131 1.296 7.778 7.571 6.448 5.428 6.440 5.152 Source: Central Bank of Oman * Foreign currency

216

unchanged at 2.3% in 2004. Similarly, the weighted average interest rate on Rial Oman

lending also declined from 8.549% in 2002 to 8.237% in 2003 and further to 7.571% in

2004. Moreover, Table A.2 analyzes the interest rate spreads defined as the difference

between the weighted average rates for lending and deposits. The average interest rate

spread has consistently remained high in recent years although the spread narrowed

during 2004. The average interest rate spread between lending and deposit rates in local

currency widened from an already high of 6.876% in December in 2002 to 6.976% in

December 2003 but dropped to 6.440% in December 2004. Similar trend was evident in

the spread between total lending (RO and FC) combined and total deposits (RO and FC

combined) with the upward movement from 5.583% in December 2002 to 5.66% in

December 2003 and subsequently declining to 5.152% in December 2004.

A.2.3. International Trade and Monetary Policy

Oman has always had a liberal foreign exchange system which facilitates trade

and investment. Broadly, payments and transfers across the border can be effected

without restrictions. While the Rial Omani versus the US dollar reflects the parity rate,

the commercial banks’ rates for other currencies are based on market rates in London.

More specifically, there is no exchange tax imposed or exchange subsidy given.

Management and administration of foreign exchange rests exclusively with the Central

of Bank Oman (CBO) and there is no exchange control legislation. No payment arrears

exist. Control on exports and imports of bank notes do not exist. Similarly, there is no

control on trade in gold, gold coins and other bullion. Import payments can be effected

freely. There is no foreign exchange budgeting whatsoever which inhibits free foreign

217

payment. Financing requirements for import and documentation requirements for

release of foreign exchange for imports are absent. Customs duties are in the range of

five percent for most imports. Import tariffs are not levied on government imports. The

effective rate of import tariffs is less than five percent. Taxes are collected through the

exchange system and there is no state import monopoly.

Regarding export realizations, repatriation requirements do not exist. No tax on

exports is levied and no exports licenses are required. Capital restrictions across the

border are not broadly constrained. Foreign ownership in Omani companies can reach

as high as 100%. There are no controls on derivatives and other instruments. There are

no controls on external credit operations of the commercial banks. However, foreign

currency exposure or open foreign exchange positions of commercial banks is limited to

40% of the bank’s capital and free reserves. Borrowings with a maturity of less than two

years are capped at 100% of a bank’s net worth. Medium term borrowings maturing

between two and five years are allowed up to 100% of net worth including short-term

liabilities. Long-term liabilities with borrowings of five years are allowed up to 300% of

net worth, including both short term and medium term liabilities. Under inward direct

investment, investment in business firms in Oman by nonresidents requires prior

approval. Neither control on liquidation of direct investment nor restrictions on real

estate transactions exist. Non-resident portfolio investors are allowed to invest in bonds

and securities through the primary and secondary market. Similarly, residents are

allowed to hold foreign bonds and securities. However, the banks can neither hold

deposits abroad in Rial Omani nor can they lend to non-residents in Rial Omani.

218

Recently, banks have been allowed to trade in foreign shares up to US dollar one

million, providing this does not exceed five percent of their net worth.

In respect to monetary policy, Oman’s economy is too small to require a

complicated monetary policy. The primary objective of the monetary policy is to

maintain the peg vis-à-vis the US dollar with a view of maintaining price stability. The

CBO directly regulates the flow of currency into the economy. The CBO has a range of

standing facilities such as reserve requirements, treasury bills, rediscount policies, loan

to deposit ratios, currency swaps and interest rate ceilings on loans and deposits. These

instruments are used to regulate the commercial banks, raise revenue, and provide

foreign exchange. However, they are not used to control the money supply.

A.3. Oman Financial Structure

A well-knit and efficient financial system promotes production, capital

accumulation, and growth by encouraging and mobilizing savings, and allocating them

among alternative uses effectively. The efficiency of a given financial system depends

on how well it performs each of these specific functions. The financial system is a loose

assemblage of credit markets and institutions of various types. In concrete terms,

financial institutions, financial assets and financial markets are the three main constitutes

of the Omani financial sector. The financial assets are of two types; primary securities

and secondary securities. Primary securities are claims against real sector units like,

bills, bonds, equities, etc. They are created by the real sector as a form of financing.

The secondary securities are financial claims issued by financial institutions or

intermediaries against themselves to raise funds from the public.

219

Oman’s financial sector is composed of the banking sector, non-bank financial

intermediaries, and financial markets. Oman's banking sector consists of 14 local and

foreign commercial banks and three specialized banks. Many of the local banks have

some foreign shareholders closely involved in their management, with many expatriates

in senior positions. The banks are generally in good financial condition due largely to

close supervision by the CBO. The CBO regulates and supervises the banking industry

under the Banking Law that was originally put in force in 1974 and revised in 2000.

The CBO is the banker, an advisor and the fiscal agent to the government, and the bank

of banks. The banking law is based on universal banking concepts, and provides the

CBO’s regulatory and supervisor powers over investment and merchant banking.

In 2000, the CBO raised the minimum capital requirements, and this action

forced several bank mergers. The most recent merger in the Omani banking sector is

that of Bank Muscat with the Commercial Bank of Oman at the end of 2000. This

merger created Oman's largest bank, Bank Muscat, with deposits of $2.4 billion and a

goal of becoming a key regional player. Foreign banks particularly find it onerous that

the Central Bank requires that banks maintain a 12% level of capital adequacy and

restrict consumer lending to 40% of the loan portfolio. The banks have led other sectors

in meeting Omanization targets. The banking sector is the most active sector in the

MSM and it has the highest market capitalization compared to other sectors. It is

regarded as the primary source of financing for most firms in Oman.

In addition to commercial banks, the Oman Housing Bank and the Oman

Development Bank (ODB) serve as specialized government banks to specific sectors.

ODB absorbed a former agriculture and fisheries bank in 1997. ODB's Export Credit &

220

Financing Unit provides export financing and credit insurance. The main objective of

the ODB was to provide loans to Omani companies registered under Commercial Law of

1974 for development projects in industry, agriculture, petroleum and fisheries. The

Bank was entrusted with the disbursement of interest free loans under the scheme of

“Government Support to the Private Sector”. The ODB is aimed to provide assistance to

development projects by granting loans, administering grants and subsidies, and

providing technical assistance to companies. Projects financed include those related to

agriculture, animal resources, fisheries, industries, tourism, education, health,

professional offices, crafts and workshops. The maximum loan that may be advanced by

the bank to any one project shall not exceed 150% of the paid up capital if the project is

located inside the Muscat region, and not to exceed 250% if it is located outside.

Normally the loans carry a maturity of 10 years with a one-year grace period.

Several institutions engage in investment banking on behalf of the Omani

government. Their activities range from investing and underwriting to advisory services

and fund management for private investors. Among these is a bi-national profit-seeking

entity of Oman and the Emirate of Abu Dhabi: the Oman-Emirates Investment Holding

Company. There are also several non-bank financial companies that raise money from

the public, directly or indirectly, to lend them to ultimate investors. This includes saving

institutions that are purely acting as conduits of mobilization of savings of the public

such as pension funds and mutual funds. Other non-bank financial institutions include

investment institutions, insurance companies, and other institutions such as securities

companies, moneychangers and leasing companies.

221

A financial system operates through financial markets and institutions. They

facilitate the mobilization of savings and efficiently channel required funds into the most

productive uses. Financial markets are composed of money market and capital market.

The following section gives some highlights of both markets.

A.3.1. Money Market

The main function of the money market is to provide short-term funds to deficit

spenders. There are two main components of the organized sector of the money

markets, besides the bank loan market. They are (1) the Inter-bank call money market,

and (2) the Bill market. The Omani money market continues to be limited and to

heavily involve the central bank (Grais and Kantur (2003)). The Omani money market

comprises various sub markets such as call/notice money market and bill market with

Treasury Bills (TB) and Commercial Bills as well as other instruments like Commercial

Papers. The main players in the market are commercial banks.

In the Bill market, the TB market is the most important. TBs are short-term

liabilities of the government. They are issued to meet temporary excess of expenditure

over receipts. In the TB market, all commercial banks and development banks can

subscribe to TBs. The TBs were first issued in June 1987 with 91-day maturity. In

August 1994, 30 day TBs were issued. The issue amounts of TBs change from one year

to another. The size of issuance of TBs amounted to RO 1,986.9 million in 2004 which

is smaller than RO 2,678.6 million issued in 2003.

222

A.3.2. Capital Market

The capital market deals in medium-term and long-term funds. Like money

markets, the capital market is also divisible into two sectors, namely, unorganized and

organized. The unorganized sector includes indigenous bankers and moneylenders,

which are not discussed here. For analytical clarity, the organized sector could be

further segregated broadly into a gilt-edged market and the stock market.

The gilt-edged market is the market in government securities. The term gilt

edged means ‘of the best quality’, as the government securities do not suffer from the

risk of default, the word gilt-edged has become synonymous with them. Government

securities have become a very important component of capital market in several

countries (Central Bank of Oman (2002)). In Oman, they have gained importance

steadily since 1987 and 1991. The gilt-edged market includes both TB and Government

bond market.

The Government mobilizes funds by floating development bonds to finance its

development expenditures. The Government Development Bonds (GDBs) were first

issued in 1991. A total of 34 GDB issues or US$ 4,284.8 million were made as the end

of 2004. GDBs were sold prior to 1998 on an ad-hoc basis, with both maturity and issue

dates chosen at random (Central Bank of Oman (2002)). Bonds were sold on a fixed

price subscription basis, at par. The amount offered was pre-announced, but represents a

nominal figure, as allotments and cut-off prices were allocated arbitrarily. In 1998, the

auction system was introduced.

223

The focus in this thesis is on the stock market because it is the most important

component of the capital market and is a major source of financing for many Omani

firms.

The Omani capital market is at an early stage of development. It is characterized

by low efficiency and low transparency. For these reasons, investor confidence in the

capital market is low. Banks are the major source of debt in Oman. Firms rarely issue

bonds and the market is dominated by GDBs. Besides raising funding through bank

loans, many firms utilize the equity market to cover their funding needs. Having said all

of this, the next sections will provide a detailed discussion of the Omani stock market

and its characteristics.

A.3.2.1. The Emergency and Development of the Omani Securities Market

In Oman, the incorporation of Oman Hotels Company, the first Omani joint

stock company to offer its shares for public subscription in 1971, paved the way for the

foundation of a securities market. No reliable information is available in regard to the

amount raised by the corporate units up to 1989 when the market organization came into

existence. About 71 Omani-joint stock companies had been established before founding

MSM, 23 of which were closed joint stock companies and 48 were public joint stock

companies. The holdings of their 17,000 shareholders were valued at RO 270 million at

the opening of the market.

In spite the issuance and development of economic financial legislation that

governed all aspects of economic and financial activities in the Sultanate, the Omani

securities market remained unregulated and disorganized. Hence, it was necessary to

224

think of organizing the market in a way to achieve the greatest benefit for the Omani

economy.

During the years 1983-1984, the Omani government requested different

institutions to submit proposals on the establishment of rule based securities market in

Oman. International institutions carried out studies and made recommendations that

centered on encouraging the idea of establishing the Omani market through setting up

the necessary means of application and work methodology.

A. The Foundations of Muscat Securities Market

Muscat Securities Market Law was issued according to Royal Decree No. 53/83

dated 21/6/1988. That decree is considered to be the legal framework for the

establishment of the market as an institution to organize, regulate and supervise the

Omani securities market and to join the efforts of other institutions in completing the

infrastructure of the financial sector in Oman.

The promulgation of MSM Law was followed by executive measures concerning

the preparation of a site for the market as well as the completion of the legislative

frameworks and work rules. Moreover, the market issued internal and executive

regulations, the directives of the organizational structure, trading instructions as well as

the directives concerning clearance, settlement and the preparation of questionnaires on

Omani-join stock companies, the members of the market.

After taking all the necessary measures and arrangements, MSM started its

activity, on Saturday, 20/5/1989. The first day of regulated securities trading in Oman

started with the trading of the generous Royal grant as His Majesty Sultan Qaboos

225

issued directives to purchase shares in joint stock companies in the interest of a charity

organizations in Oman. This was a unique and prominent action, not only in the history

of MSM, which took off with this humanitarian action, but also in the history of

securities market all over the world.

B. Structuring the Capital Market

The market was established at the outset as one entity comprising the regulator

(the supervisory body) and the stock exchange where securities selling and buying takes

place. Registration, depositing, and safekeeping of ownership documents and

shareholder registers were made at the joint-stock companies that were listed in the

market. Later, on September 15, 1992, the management of the market established a

center for depositing and transferring to undertake, on behalf of companies, all the

measures of registering, transferring the ownership of securities and issuing safe keeping

certificates. A committee for clearance and settlement was supplemented to this

structure in January 1996 to verify the validity of the exchange contracts, and the

conclusion of deals through handing over credits against ownership documents. A

committee for control and follow-up was added to the above structure in August 1998 to

oversee the trading process and spot violations. The experience showed that such

integration weakened the supervisory role of the market as the staff were occupied with

the matters of trading, settlement, deposit, transfer and the related daily problems at the

expense of the supervisory role and the market development. Therefore, there was a

trend to separate the supervisory body from the stock exchange, deposit and transfer.

226

Such a trend was enshrined with Royal Decree No. 80/98 issuing Capital Market Law

which separated the supervisory body from the stock exchange.

Capital Market Authority (CMA) has been established as a supervisory body to

organize, license, and monitor the issuance and trading of securities as well as

supervising all dealers in the securities market and Muscat Depository and Registration

Company (MDRC). Also Royal Decree No. 82/98 has established MDRC in the form of

closed joint stock company. As per those two Royal Decrees, the capital market was

restructured to allow for the establishment of the following three separate bodies:

1. The Capital Market Authority

CMA aims at enhancing the efficiency of the capital market, regulating its

process, and establishing the professional code of conduct and discipline among all

dealers in securities.

2. Muscat Securities Market

MSM main objective is to regulate the operations of selling and buying of

securities in a way to ensure the protection of the investors against unfair and invalid

dealings.

3. Muscat Depository and Registration Company

The objectives of this company are safekeeping of shareholder registers, issuing

ownership certificates and documents, and issuing dividend cheques to joint-stock

companies.

Nowadays, MSM is considered as one of the more effectively regulated markets

in the region, with strict rules and regulations laid out to check any malpractice or

insider trading. Companies are required to conform to extensive disclosure norms to

227

ensure maximum transparency. Listed companies are required to publish quarterly

financial results, prepared in accordance with International Accounting Standards.

C. Listing and Trading

Listing means registering certain securities with the authority concerned with

regulating and controlling the trading of securities. The aim of listing is to provide a

liquid market in which securities can be offered for buying and selling in a way that is

open to all the interested parties and in a manner set by the concerned authority.

Dealing in the MSM essentially takes two forms: (1) trading in the primary

market, and (2) trading in the secondary market.

1. The Primary Market

Trading activity in the primary market started in November 1989. The primary

market is a preliminary market where new issues of securities are sold. Newly

established companies, whose balance sheets and income statements are not yet

available, are listed in the primary market to give people an incentive to encourage them

to subscribe for the new shares, although the financial information about these

companies is incomplete (Directives for Listing Securities on Muscat Securities Market

(2002)).91

91 See Table A.9 for information on the amount of equity issuing.

228

2. The Secondary Market

The secondary market was activated with the establishment of the MSM in 1989.

This is the market where securities are purchased or sold directly or through brokers and

where the exchange or transfer of ownership takes place on the floor, the brokers’

offices or in the market offices. The secondary market is divided into the following sub-

markets:

i. Regular Market is the part of the secondary market where dealing on the

floor is regulated in respect of companies’ shares subject to special listing

conditions as specified by the Board of CMA. Companies listed under the

regular market are governed by the following three requirements: (1) the

paid-up capital must not be less than RO 2 million, (2) the shareholders

equity must be not less than 100% of the paid-up capital, (3) firms listed in

this market must have achieved net profits during the last two years

preceding the application for listing or transfer to the regular market.

ii. Parallel Market is the market where dealing on the floor is regulated in

respect of companies’ shares subject to simplified listing requirements

allowing trading and the facilitation of early liquidity for the securities listed

therein prior to listing in the regular market. Bonds are also listed in this

market. Firms listed in this market must have been in operation for a

minimum of three years and have published audited financial statements

prepared in accordance with the International Auditing and Accounting

standards. Moreover, they must have achieved a net profit during the year

229

preceding the date of the listing application and their shareholders’ equity is

not less than 50% of the paid-up capital (Directives for Listing Securities on

Muscat Securities Market (2002)).

iii. Third Market is more restrictive compared to the other markets. It consists

of firms that do not satisfy the requirements for listing on the Regular and

Parallel Markets. This is the market where off-floor dealings take place in

the brokers’ offices to which the specific listed conditions for trading on the

floor do not apply. It encompasses the transfer of shares in closed joint stock

companies and the transfer of shares between members of the same family.

Trading can only be effected though brokers licensed and approved by the

CMA. Direct dealings are not allowed between buyers and sellers of

securities.

Securities are traded in accordance with the instructions of the CMA and MSM

and under the supervision of the market representatives who are present at the trading

floor. Since the beginning of the market activities on 20/5/1989, trading was undertaken

through manual writings and crossing on the trading board. As of the first half of 1998,

an electronic trading system has been used. Orders and bids are made through a

computer-based electronic process.

230

A.3.2.2. Characteristics of Muscat Securities Market

A. Types of Industries in MSM

The MSM comprises four industries or sectors: Banking and Investment,

Insurance, Service, and Industry. The following are some highlights about each of them.

Banking and Investment sector

The market is dominated by the banking and investment sectors where there are

29 firms listed out of which five are banks. This industry is the driver of the whole

market and has the majority of trading and the highest market capitalization. Out of a

market capitalization of approximately RO 5.9 billion, the market capitalization of this

sector stood at RO 2.092 billion at the end of 2005 of which RO 1.566 billion is for the

banks. Most of the shares traded in the market are for this sector’s stocks and the

trading volumes amounted to RO 591 million in 2005 compared to RO 421 million in

2004. Moreover, this sector is characterized by being asset-intensive where its total

assets reached a high of RO 5.138 billion in 2005 with banks accounting for 80% of that

total.

Industry sector

This sector houses 53 firms distributed among firms manufacturing detergents,

pharmaceuticals, flour, cement, batteries, aluminum, and others. This sector reflects the

manufacturing strength in the country. This sector had the highest number of firms and

accounts for RO 160 million of trading volume and RO 505 million of market

capitalization. This sector has total assets of RO 615.196 million as at the end of 2005.

231

Service Sector

Petroleum, tourism, hotels, port services, marketing, fisheries, poultry, aviation,

power, and livestock are the main activities of the 39 firms listed in this sector.

Consistent with the increase in trading volume in the overall market, this sector’s trading

volume increased by 235% between 2004 and 2005 to reach RO 506 million.

Furthermore, this sector has the second highest market capitalization of RO 809 million

and its total assets stood at RO 1.499 billion at the end of 2005.

Insurance Sector

This is the smallest industry in the whole market with only two firms listed. The

total assets of these firms increased from RO 891 thousand in 2000 to reach a high of

RO 58.8 million at the end of 2005. The market capitalization mirrored this growth in

assets to reach RO 84.415 million. In 2005, the trading volume for these companies

reached RO 6.91 million.

B. Market Capitalization

The MSM is the only organized securities market in Oman and has a market

capitalization of RO 5,878.5 million as of the end of 2005. As displayed in Figure A.1,

market capitalization of the MSM was only RO 1,484 million in 1996; this increased

sharply after one year to reach RO 3,189 million.

232

Figure A.1. Market Capitalization from 1996 to 2005

0

1000

2000

3000

4000

5000

6000M

illio

n (R

O)

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Market Capitalization

Source: Muscat Securities Market

Starting in 1998, the market capitalization declined by 25% and continued in a

downward trend until the end of 2001. The positive performance of MSM during 2002

resulted in the market value of listed securities reaching RO 1,983.60 million at the end

of December 2002 compared to RO 1,721.8 million at the end of December 2001. The

market capitalization increased to RO 2,789 in 2003 and further to RO 3,587 million in

2004. During 2005, the market capitalization reached the highest level since the

inception of the market at RO 5,878.5 million.

233

C. Turnover of shares

The turnover of shares in the MSM has registered steady growth since the

commencement of trading in 1989. When trading began in 1989, trading of shares was

relatively modest but with signs of steady growth. The exchange was gradually gaining

momentum and was considered as one of the fastest growing markets in the region.

Figure A.2. Number and Value of Traded Shares from 1996 to 2005

0

200

400

600

800

1000

1200

1400

1600

1800

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Mill

ion

(RO

)

Number of TradedShares in Million

Trading Value (ROMillion)


The trading volume of the MSM shares was not substantial until 1997 when it

reached an all time high of RO 1,615 million. The next year experienced a substantial

decline in the trading volume of about 76%. The trading volume continued to decline

until it reached an all time low at the end of 2001 at RO 164 million.

234

Since the beginning of 2002, however, the market has shown considerable

bullishness. As presented in figure A.2, the volume of trading increased from RO 164

million in 2001 to RO 231 million in 2002. This trend continues in 2003 and 2004.

During 2005, trading volume achieved the best performance at all levels during the last

five years. It increased by 85.4% from RO 759 million in 2004 to RO 1,407 million in

2005. More than 515 million securities changed hands in 2005 compared with 352

million securities last year with an increase of 46.3%.

D. Ownership Structure92

Whereas firms in most countries of the world are owned by a diverse group of

investors, Oman ownership is unique. The majority of firms in Oman are owned by a

small number of investors who have controlling interests. This concentrated ownership

reaches up to 80% in some firms for a single group of investors. However, the Omani

government also plays a role in holding stocks in the MSM. The Omani government

holds the major shares of some companies and small amount of shares in almost all

companies.

Even though foreigners do not hold the major proportion of shares, some foreign

ownership exists in most companies listed on the MSM. These foreign investors include

pension funds, financial institutions, and individuals. The major foreign owners are

pension funds and banks. Financial institutions and individuals are marginal owners.

Most of the foreign ownership is for investors from GCC (Oman, Bahrain, Kuwait,

United Arab Emirates, Saudi Arabia, and Qatar) countries. Foreign participation in the 92 While we have data on foreign ownership and institutional ownership at the aggregate level, we do not have these data at the firm level. We also do not have data on inside ownership.

235

capital of the general joint stock companies calculated on the basis of market

capitalization recorded a slight improvement in the year 2002 to reach 11% compared to

9.31% at the end of the year 2001. The foreign participation increased to 16.46% in

2003 and further to 18.22% in 2004. However, this participation declines slightly in

2005 to reach 16.16%.

Figure A.3. Distribution of the Shareholding of the Omani Companies in 2004

7%

36%

18%

39% GovernmentIndividualForeignersInstitutional


Furthermore, as in other countries, institutional investors (banks, pension funds)

hold most of the shares while the government holds the least. Though not shown in

figure A.3, company directors hold a major stake in the companies where they sit as

members of board of directors. One or two owners with significant blocks of shares

may effectively control the affairs of the whole company. However, other insiders like

management and employees rarely hold any stock. One reason for this is that Omani

companies do not have stock options plans or performance shares plans. Further, many

Omani companies are managed by expatriates who are hired because of their expertise

236

and credentials. Furthermore, individuals or families are a major investor in Oman's

companies with a stake of 36%. Families usually have a significant presence on the

companies’ boards.

A.3.2.3. Performance of the MSM

A. Bubble Burst

At the beginning of 1997 the market witnessed a sharp rise. The number of

newly established companies was increasing at a very high rate as the government

encouraged the private sector through very attractive soft loan schemes. Small family

businesses were converted to public joint stock companies. Banks financed initial public

offers to very high levels and over subscription of new IPO’s was very common as more

and more public companies were being established.

According to MSM statistics, there were 23 newly established public stock

companies in 1997. This growth in listings led to more speculative trading activity and

the index rose to 4805.8 points at the end of 1997. This was unprecedented and purely

the result of market speculation (Islam (2003c)). Then, the index nose-dived throughout

1998 until it temporarily bottomed at 2091.6 points in March 1999. The price index

reached a historic low of 1520.8 in December 2001.

Most of the investment was by individual investors or corporate investors

controlled by particular individuals. In 1997, the number of depositor accounts

increased to 226 thousand. Besides 30-50 thousand existing investors, 150-200

237

thousand new investors invested in the MSM during the bubble.93 During the bubble,

banks were making loans aggressively to investors who pledged their purchased

securities as collateral. Tens of thousands of investors were financially overleveraged as

a result, and went into bankruptcy when the “bubble” burst. To minimize the effect of

this, the government intervened and established a RO 40 million fund to invest it in

MSM-listed securities under the management of HSBC. Furthermore, the government

injected another RO 50 million in MSM listed securities.

The dramatic downturn has been attributed to a combination of global and

domestic factors. The domestic factors that contributed include (1) a flurry of new

issues without adequately prudent scrutiny, (2) an unregulated credit extension to

securities investment which leveraged booming equity investment without a reliable risk

control mechanisms in place, (3) a market microstructure without appropriate

mechanisms to control overheated prices (well-regulated short selling) being in place,

(4) a swelling of bank credits in 1994-1995 and subsequent surge of the money base in

the economy with an inadequate money supply control mechanism, (5) an absence of

required institutional infrastructure facilities, (6) a sharp decline in oil prices, (7) a bad

management by brokerage firms and investment companies, and (8) an absence of

professional financial analysts (Islam (2002)).

An external factor that contributed was the global emerging market boom in the

mid-1990s that ended with the Asian Financial Crisis in 1997. The market bubble and

crash originated from the Omani investment community behaviour as a psychological

response to economic phenomena abroad (Central Bank of Oman (1998)). Global 93 There were 226 thousand securities deposit accounts at the end of 1997; 120 thousands accounts at the end of April 2003, of which only 30 thousand accounts were active.

238

economic phenomena traveled quickly to the Omani market in the form of profit

expectation and anxiety loss (Central Bank of Oman (1998)).

Nowadays the stock market weakness has been removed or mitigated making the

economy less vulnerable to future bubbles. For example, the government introduced

several reform measures in an effort to revive the market. In 1999, a new capital market

law was introduced to establish the CMA to regulate the new issuance and trading of

securities on the MSM. The new regulation stressed the importance of disclosure and

transparency. Companies listed in the MSM are required to disclose their financial

positions and provide quarterly, half yearly and annual financial statements. In addition,

new brokers’ regulations have been enacted. They include requirements for suitable

capital adequacy rules, and the introduction of control on Margin Accounts.

Furthermore, the National Investment Fund Company was launched in late 1998 aimed

at channeling pension funds into the stock market. Moreover, in June 1999 the MSM

announced revised criteria for stocks to be included in MSM general index with strict

adherence to reporting requirements. In addition, the CMA organized a seminar on

corporate governance in June 2001 aiming to create public awareness of the market. As

a follow up, CMA constituted a committee comprising representatives of various

sections of the economy including the private sector. This committee was entrusted with

the task of framing a code, drawing from the best practices globally, suitably adapted to

the local needs. This resulted in the introduction of a code of corporate governance in

July 2002. The purpose is to ensure the code promotes a culture of compliance,

transparency and accountability without restraining business initiatives.

239

B. Recent Trend in MSM Index

The Muscat Securities Market performed remarkably well in 2005, recording the

best performance since the inception of the market. The MSM Index advanced by 1500

points registering 4875.11 points in 2005 compared with 3375.05 points in 2004, an

increase of 44.4%. This impressive performance is attributed to several direct and

indirect factors, the most important of which is the improvement in the performance of

the Omani economy as a result of the surge in oil prices in international markets and low

interest rates on deposits which in turn led to a marked increase in investment in

securities. In addition, continued improvements in the profitability of listed companies

have boosted the investor confidence.

It is worth noting that effective from June 1, 2004, the base (points) to calculate

the MSM Index and the sectorial indices such as Banks and Investment, Industry,

Service, and Insurance has been changed from 100 to 1000 points.

Figure A.4. MSM Index over the Years

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Poin

ts

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

MSM Index


240

C. Listed Companies

Public corporations in Oman are quite small in both number and market

capitalization. When trading began in 1989, there were only 48 publicly listed

companies.94 The number of listed companies increased to an all time high to reach 151

in 1999.

Figure A.5. Number of Publicly Listed Companies from 1996 to 2005

020406080

100120140160

Num

ber

of F

irm

s

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Listed Firms


Starting from 2001, some firms changed from publicly listed companies to

privately closed companies resulting in a decline in the number of publicly listed firms

to 123 at the end of 2005 (Figure A.5). A number of developments contributed to

companies wanting to convert from public to private. One of these is the cost involved

with implementing corporate governance rules - like providing quarterly financial

statements, and internal audits which are the requirements of SAOG companies. The

cost element of this is high: firms need additional personnel and also professional fees

94 There are no state-owned companies listed on the MSM.

241

for audit fees, legal fees, etc. Some firms are transferring because they are

uncomfortable with a number of rules relating to disclosure principles, transparency,

related party transactions, adherence to corporate governance and the appointment of

internal auditors.

A.4. Corporate Taxation System in Oman

Taxation is low in Oman, because much of the government's revenue is realized

through oil revenues. In general, the tax system benefits residents of Oman by

extending special tax privileges to companies which have a substantial amount of

participation from Omani nationals.

Capital gains and dividends are not taxed in Oman.95 The country's main tax is

corporate income tax. Businesses are taxed on their Omani-sourced income. Omani

companies with no more than 70% foreign ownership are taxed at a flat rate of 12% on

their income over RO 30,000 (the first RO 30,000 is exempt).96 Other businesses with

over 70% foreign ownership and branches of foreign companies are taxed at stepped-up

rates varying from 5% to 30%. The highest rate of 30% will apply when the taxable

income exceeds RO 100,000. Table A.3 exhibits the tax rates for the different classes of

income.

95 Oman does not levy personal income tax. 96 There are no companies listed at the MSM with over 70% foreign ownership (MSM Information Center).

242

A. Tax Rates97

Tax is levied on companies including partnership and joint ventures registered or

incorporated in Oman, permanently established foreign enterprises, commercial,

industrial, and professional establishments owned or exploited by individuals (Omani

and foreigners) in Oman, and locally registered investment accounts (mutual funds).

Table A.3. Tax Rates for Businesses with Over 70% Foreign Ownership Taxable Income (RO) Rate (%) 0-5,000 0 5,000-18,000 5 18,000-35,000 10 35,000-55,000 15 55,000-75,000 20 75,000-100,000 25 More than 100,000 30 Source: Ministry of National Economy

The taxable entities are required to prepare accounts for the accounting period

corresponding to the calendar year.98 However, they may be allowed to prepare the

accounts for an accounting period of 12 months ending on a date other than 31

December, provided they follow that policy consistently. Income earned during the tax

year (corresponding to the accounting year ending on 31 December) is considered as the

taxable income of the tax year. If the closing date of the account is a day other than 31

December, the income earned during the accounting year ending in a tax year is

considered as the taxable income of that tax year.

97 Marginal relief is granted where the taxable income is slightly higher than the border between one rate and the next. 98 Tax year corresponds to calendar year i.e., 1 January to 31 December.

243

In terms of the deductibility of expenses incurred, the Omani tax law regards all

expenses incurred wholly and exclusively in the production of income as normally

admissible. The law also provides for certain specific deductions and disallowance of

certain expense. There are no specific rules for inventory valuation but first-in-first-out

(FIFO) is typically used.

The Omani tax law requires taxable entities to compute the taxable income in

accordance with a generally accepted method of commercial accounting (as given by

International Accounting Standards). Taxable entities are required to follow the accrual

method of commercial accounting. In exceptional cases, on an application made to the

Secretary General of Taxation, he/she may permit any other method of commercial

accounting.

B. Exemptions and Tax Holidays99

In order to encourage investments in certain identified economic sectors, income

tax exemptions (tax holidays) are granted to companies engaged in these sectors.

Corporations whose main object is manufacturing, agriculture, fishery, tourism,

exportation of local products, public utility projects and infrastructure projects, as well

as companies whose activities are deemed essential for economic development, may be

exempted from tax for five years (Royal Decrees 125 / 94; 102 / 94). These corporations

may carry forward losses incurred during the five-year exemption period for as many

years as are needed to offset the losses against taxable income. However, the losses can

99 We do not have data on firms that have tax holidays.

244

not be carried backwards. Excess tax paid is refunded if a claim is made within two

years from the end of the tax year in which such excess is finally determined.

C. Withholding Tax

Oman does not have a withholding tax, estate or gift tax, or dividend tax. The

only consumption taxes are certain taxes of municipalities, such as a 5% tax on hotel and

restaurant bills, a 2% tax on electricity bills exceeding RO 50 and a 3% tax on lease

agreements payable by the landlord.

D. Change to the Income Tax Law

As part of Oman’s continuing efforts to liberalize taxation laws and to promote

foreign investment, recently the taxation law was amended. Royal Decree 54/2003 was

issued on September 10, 2003 enacting a series of amendments to the Omani Income

Tax Law. The major changes are summarized below:

• The tax rate for all companies registered in Oman, irrespective of the extent of

foreign ownership has been made uniform. The rate applicable is 12% on

taxable profits in excess of RO 30,000.

• Companies wholly owned by nations in the GCC states will be taxed at a flat rate

of 12% irrespective of the nature of their activities. Branches of companies

registered in GCC states, irrespective of the extent of foreign participation will

be taxed at a flat rate of 12%.

• In line with the Government’s increased focus on the education and health care

sectors, the tax laws now provide for a tax exemption to income arising from

245

university education, colleges, higher institutes, private schools, kindergartens,

training colleges or institutes and private hospitals. The exemption is without

any time limit.

A.5. Debt Securities in Oman

Similar to other Arab countries, the corporate bond market in Oman remain

limited with the secondary market being almost absent (Grais and Kantur (2003)).

Access to corporate bonds remains a serious thorn in Oman, but not only that.

Derivatives and other risk management products are virtually absent from the menu of

the financial products (Azzam (2002)). The government is the largest issuer of debt i.e.,

the long dated GDBs and TBs. Other institutions including commercial banks, special

banks, leasing companies, and non-financial corporations have used the capital market

for debt financing, however this happens on a very limited basis.

Debt financing in the capital market is accessible only to joint stock companies.

There were 85 closed joint stock companies100 and 123 public joint companies101 as at

the end of 2005 (MSM Annual Statistical Bulletin (2005)). In spite of this, Omani listed

companies are relatively highly leveraged and the main source of debt is short-term bank

financing. As we can see from Table A.4, Oman has a higher debt ratio compared with

other emerging markets.

100 The minimum required capital is RO 500,000. 101 The minimum required capital is RO 2,000,000.

246

Table A.4. Debt Indicators of Listed Companies (Average ratios for 1999-2001) Country Liabilities/assets Current Liabilities/total liabilities Oman 0.67 0.60 Argentina 0.50 0.51 Brazil 0.50 0.46 Chile 0.50 0.29 Colombia 0.34 0.50 India 0.58 0.55 Indonesia 0.56 0.58 Malaysia 0.55 0.50 Thailand 0.67 0.44 Turkey 0.58 0.71 Hungary 0.45 0.51 Poland 0.55 0.55 Source: Muscat Securities Market data, Worldscope for other countries

This is surprising giving the fact that the corporate bonds market is

underdeveloped. Corporate bonds were introduced in 2000 when the first bond of Bank

Muscat was issued in December 2000. The United Finance’s bond issue on 21/10/2002

was the first public offering of corporate bonds in Oman in the sense that they were

“unspecific” and offered for all investors. The first two issues of Bank Muscat were

offered only to the existing shareholder of Commercial Bank of Oman and the Industrial

Bank of Oman in exchange for their shares in the acquisition of these banks in 2000 and

2002, respectively.

Table A.5 presents the public offering of corporate bonds over the years. The

table shows that there were nine issues of corporate bonds. Of the nine, two were

convertible bond issues. Bank Muscat convertible bonds are mandatorily convertible

into its shares at par at maturity. United Finance’s convertible bonds are embedded with

European options to convert into its shares at a 15% discount. The minimum

247

subscription of the bonds was set RO 10,000 (US$26,008), which considerably restricted

the distribution of the bonds.102

Table A.5. Public Offering of Corporate Bonds in Oman Issuer Type Issue Date Coupon Issue Amount

(In RO mil.) Bank Muscat Straight 31/12/2000 10.000% 16.65 Bank Muscat Convertible 02/04/2002 - 25.00 United Finance Convertible 21/10/2002 6.000% 2.70* Bank Dhofar Straight 13/04/2003 7.000% 7.36 Bank Muscat Straight 06/07/2003 7.000% 25.00 Alliance Housing Bank Straight 31/05/2004 5.550% 6.00 United Finance Straight 13/06/2004 6.000% 4.00 Bank Muscat Straight 20/07/2004 6.250% 29.80 Oman National Dairy Products Straight 16/09/2004 5.850% 1.50 Source: MSM Database System *Undersubscribed against an offered amount of RO 5 million

There were two issues of corporate bonds in 2003 with a total value of RO 32.36

million. During 2004, the corporate bond market witnessed the listing of four bonds

amounting to RO 41.3 million. The common feature among these bonds was that all of

them were straight bonds.103 It is worth noting that all of the bonds are issued by banks

and investment firms except for Oman National Dairy Products.

Table A.6 summarizes the trading volumes of the bonds issues listed on the

MSM for 2001 and 2002.

102 United Finance’s issue was placed on a best effort basis, and eventually under-subscribed. 103 A straight bond, also known as a bullet bond, pays a fixed rate of interest and is redeemed in full on maturity, and is the simplest form of coupon paying debt instrument.

248

Table A.6. Trading Volumes of Corporate Bonds on the MSM104 Individual Investors Institutional Investors Total Year Locals Foreigners Locals Foreigners

2001 1,314,492 130,485 23,213,417 2,374,694 27,033,088 % 4.9% 0.5% 85.9% 8.8% 100% 2002 9,745,436 867,035 15,112,279 810,533 26,535,283 % 36.7% 3.3% 57.0% 3.1% 100.0% Source: Muscat Securities Market

It is clear from the figures that institutional investors more actively trade bonds

than individual investors. The bonds were traded more actively as the interest rate

declined in 2001, until they were finally placed in “firm hands”, but their trading shrank

substantially in 2002. A relatively high volume of secondary market trading of

corporate bonds is probably attributable to their exceptionally high coupon rate.

There are many reasons for the underdevelopment of the corporate bond market.

Most importantly, Omani laws are deficient in provisions for corporate bonds. The

resultant uncertainty of corporate bonds inevitably complicates and protracts their

issuing procedures, and consequently, makes them less attractive to issuers and

investors. The provisions of the Commercial Companies Law of 1974 as amended are

insufficient in facilitating the flexible issuance of corporate bonds in terms of bond type

or structure (Islam (2002)).

Another important reason for the underdeveloped bond market is related to

eligibility or restrictions of corporate bond offering. Joint stock companies listed in the

MSM are eligible for offerings of corporate bonds. However, the CMA has not

established or published criteria or guidelines for its approval of bond issues. Moreover,

the aggregate amount of bonds that a non-bank joint stock company may issue is 104 Starting from 2003, the MSM is no longer publicly publishing these data.

249

restricted to the amount of the company’s capital. The restriction may limit the scope of

debt investment opportunities available to investors in the economy and, consequently,

may result in an inefficient reallocation of capital (Salim (1998)). The intention of this

restriction is assumed to protect bondholders of companies that are not regulated for

prudential purposes as compared to banks that are prudentially regulated by the CBO.

Public offering procedure is another area of concern regarding the corporate

bond market. Public offering procedures (from the board of director’s resolution to the

allotment) in the Omani market are supposed to take 2.5 to 3 months (11 to 13 weeks) to

complete. However, the public offerings of convertible bonds by United Finance took as

long as 11 months from the resolution of the board of directors in November 2001 to the

allotment in October 2002.105 The CBO took four and half months from early December

2001 to mid-April 2002 for the preliminary approval. The CMA took three and a half

more months for the final approval in early August 2002. The uncertainty of rules and

regulations concerning corporate bonds appears to have complicated and protracted

issuing procedures unnecessarily and is partly responsibly for the undersubscribtion of

the bonds (Islam (2003b)).

Pricing mechanisms for corporate bonds in Oman have been distorted and

inefficient. The Omani market is yet to establish a rational basis for pricing corporate

bonds. In fact, pricing of long-tem fixed rate corporate bonds is faced with two

technical difficulties. First, the Omani market has no reliable term structure of interest

rate beyond one year due to the illiquid secondary market for government bonds. There

105 Exercising its approving power for publicly offered bond issues, the CMA imposed a restrictive covenant, that is, a non-distributable reserve fund on the senior convertible bonds issued by United Finance in September 2002 for the sake of protection of investors’ interest.

250

are no benchmark issues available against which corporate bonds can be rationally

priced. Second, the current public offering procedures cause the issuer and investors to

commit themselves to a given rate for too long. If the issuer and the intermediaries take

a safe side for the sake of salability of bonds, the pricing will be considered expensive to

the issuer.

A.5.1. Issuers of Debt Securities

The Ministry of Finance is responsible for issuance of government debt and CBO

issues short-term Certificate of Deposit (CDs) to licensed banks. The CDs are used to

manage market liquidity. No State Owned Enterprise (SOE) has ever issued debt

securities.

Among Commercial Banks, Bank Muscat tapped the domestic market with four

debt issues with a total value of RO 96.45 million; one is convertible and the others are

straight bonds (see Table A.5). Two other straight bonds were issued by Bank Dhofar

and Alliance Housing Bank. Apart from these, commercial banks such as Bank Muscat

and Oman International Bank issued Negotiable Certificates of Deposit (NCD)s from

time to time outside the capital market regulatory framework.

None of the non-financial firms have ever issued bonds except for the Oman

National Dairy Products. This limits the firm’s ability to grow because of the lack of

relatively cheaper financing, namely, an active bond market. This tends to have an

adverse impact on profitability because firms are forced to borrow from banks at higher

interest rates.

251

A.5.2. Investors in Debt Securities

As the case in other Arab markets, individual investors are not the main players

in debt securities in Oman (Bolbol and Omran (2004)). They represented only 5.75%

(RO 24.0 million) in 2002. Commercial Banks are the main clients for government debt

securities in emerging markets and the same pattern is observed in Oman. Commercial

Banks own all or most of the TBs outstanding, and 21.61% of GDBs outstanding. Their

holdings accounted for 25.4% of all government debt securities outstanding.

Commercial banks’ investment in GDBs may need a cautious approach in light of

GDB’s market risk. Issues with low coupon rates, which were issued in the

environments of rapidly declining interest rates since 2001, have been increasing their

share in the GDB portfolio of Omani commercial banks. Once the interest rate trend

reverses and starts rising, the banks will likely be required to revalue their GDB

portfolios at lower values and charge lost values to their income statements.

Pension funds are another major investor in the capital market. They are

considered the primary institutional investors in Oman. The total assets of the Omani

pension funds were estimated at RO 850 to 1,200 million as at the end of 2004. Cash

and bank deposits exceed 50% of assets. The stock market crash in 1997 caused pension

funds to shift to cash and deposits, which are usually in a 20-30 percent range (Central

Bank of Oman (1998)). However, pension funds quickly increased their share in GDBs

holding from 1998.

Mutual funds are a powerful vehicle to bridge between the general public’s

savings and a highly professional market of bonds. Oman’s experience with investment

funds is however limited. There is no framework of mutual funds or open-end funds.

252

A.6. Structure of Financing in Oman

The focus of this section is to provide information about the structure of

financing in Oman. In particular, the section describes the capital structure based on

sources of financing.

A.6.1. Internal Sources of Financing

Internal sources of financing by companies include the funds that are directly

invested by the shareholders (share capital) and by keeping the profit in the companies

(retained earnings) and legal reserves. Legal reserves, which are not available for

distriubution, are accuumulated in accordance with article 106 of the Commercial

Companies Law 1974. The objective of these reserves is to keep some money in the

company to cover expenses rising mainly from borrowings. In fact, legal reserves are

considered as a supplement to the company’s capital and are regarded as being a

guarantee for creditors. Article 106 of the Commercial Companies Law 1974 states that

the annual appropriation shall be 10% of the net profit for each year after taxes, until

such time as the reserve amounts to at least one third of the share capital.

General reserve is another source of internal financing for Omani firms. Article

106 of the Commercial Companies Law of 1974, allow firms to transfer 10% of a

company’s net profit after legal reserve allocation, to a distributable general reserve until

it reaches half of the company issued capital. This approach is utilized as a major source

of financing for some Omani firms. Some firms set aside a distributable reserve for

furture investments in capital assets. This is known as Development reserve.

253

In some cases, Omani firms tend to increase their capital through private

placements to specified persons. This means that companies will receive the full

consideration, allot shares and get these listed in MSM within 60 days from the date of

approval of the Extraordinary General Meeting. The shares offered must be at a price

not less than their nominal value. The privatley placed shares will be “locked in” for a

period of one year from the date of listing. This means that the allottees can not sell

their shares for a period of one year from the date of listing, however, they can use them

as collateral to buy other shares. Despite this lengthy and detailed procedure, when

companies raise capital through the capital markets, in many cases they utilize this

approach.

The utilization of profit generated by a company through retained earnings

requires the approval of the shareholders. This has to be approved in the Annual

General Meeting of shareholders. However, it is worth mentioning that most Omani

firms do not retain their earnings, rather, they tend to distribute their earnings in

dividends.

A.6.2. External Sources of Financing

The main external sources of financing that are available to Omani firms include

loans from commercial banks, soft loans from the government, and equity. We next

explain each source in more detail.

Loans from commercial banks are a major source of financing for Omani

corporations. Commercial banks provide working capital loans, loans for equipment

financing, and trade finance. Omani companies are able to obtain a line of credit at the

254

rate of interest charged by the bank. The terms under which banks provide companies

with loans are very similar to those in the US and other parts of the world. Reputation is

the leading term and the five C’s (Character, Capacity, Collateral, Capital, and Credit)

are applicable in Oman as they are anywhere in the developed countries (Central Bank

of Oman Annual Report (2002)). Although banks do not rely on market information

when granting a loan, they require detailed studies of an applicant before making any

loan.

The Omani banking system is highly regulated and quite advanced (Islam

(2003a)). The commercial banking sector in Oman consists of five locally incorporated

banks and nine branches of foreign banks as at the end of 2004. The Banking sector is

extremely concentrated in Oman. Three major banks dominate the sector: Bank Muscat,

the National Bank of Oman, and the Oman International Bank (see Table A.7). The

sector has been consolidated to manage the aftermath of the bubble burst in 1997/1998.

Bank Muscat acquired the Commercial Bank of Oman in 2000 and the Industrial Bank

of Oman in 2002. Bank Dhofar merged with the Majan International Bank in March

2003.

Table A.7. Commercial Banks Listed on MSM at the end of 2004 Bank No. of operating

offices Paid in Capital (RO mil.)

Total Assets (RO mil.)

Bank Muscat 90 59.8 1,900.3 National Bank of Oman 52 70 747.3 Oman International Bank 82 62.9 717.8 Source: Capital Market Authority

255

Omani commercial banks engage in both commercial and investment banking

businesses. The commercial banking has grown over the years in tandem with the

overall economic development. During the year 2004, total assets of commercial banks

rose by 8.9% to RO 4,888.7 million. Table A.8 presents credit by commercial banks to

various sectors since 1998. Total credit rose by 6% to RO 3,505.7 million or 36.7% of

GDP as at the end of 2004. Similarly, credit to the private sector registered an increase

of 6% over the year. Investment by commercial banks in TBs stood at RO 149 million

while holdings of GDBs amounted to RO 146.5 million as at the end of 2004. Although

there is no restriction on banks owning shares of companies, their average shareholdings

are not significant. Investment in shares and securities in the domestic market increased

to RO 30.9 million as at the end of 2004 from RO 25.1 million a year earlier. The fact

that Omani banks are able to both underwrite corporate securities and to own equity

adds to their importance in corporate financing decisions.

As explained before, the issuance of bills and bonds is not frequently employed

in Oman. Even when companies issue bonds, they are not liquid due to the nonexistance

of secondary bond market. Furthermore, in Oman, bonds are not known to appreciate in

price; most bonds are held until maturity. For the reasons mentioned earlier, firms

prefer bank debt.

256

Table A.8. Credit by Commercial Banks to Various Sectors (In RO Million) % ∆ Category 1998 1999 2000 2001 2002 2003 2004

2004/2003

Credit to private sector

2,590.0 2,830.1 2,885.1 3,072.3 3,054.6 3,089.9 3,274.1 6.0

Credit to public enterprises

- 4.1 16.3 28.1 46.0 69.0 87.3 26.5

Credit to Government

39.8 64.7 79.3 140.6 169.7 149.4 144.3 -3.4

Securities 1.Treasury bills (at cost)

87.6 127.8 40.0 160.0 69.0 138.0 149.0 8.0

2.Government Bonds

70.6 117.3 120.9 126.2 118.4 130.4 146.5 12.3

3.Other domestic securities

31.6 36.0 33.3 32.7 24.1 25.1 30.9 23.1

4.Foreign securities

124.6 89.6 78.8 74.9 85.9 83.4 121.7 45.9

5. Others*

- 25.6 83.4 28.6 119.0 167.1 55.0 -67.1

Total Credit 2629.8 2898.9 2980.7 3241.0 3270.3 3308.3 3505.7 6.0

Source: Central Bank of Oman *includes investments in Certificates of Deposit

As part of its efforts to attract investment, Oman offers several financial

incentives for investors. The government grants soft loans (loans that are given at low

interest rate or in some cases even interest free) for Omani firms through the Oman

Development Bank. Loans are given for acquiring fixed assets for new projects, buying

machinery and equipment required for expansion of existing projects, and infusion of

finance into a “sick” industry. For example, the government launched industrial

257

diversification programs in 1994 and 1995, which provided Omani firms with soft loans

of approximately RO 300 million.

Sole proprietorships and corporate firms are eligible for these grants. The grant

is also paid to new as well as existing projects which face investment problems,

provided they are in agriculture and fisheries, industry, tourism, general education,

higher education, and the health sectors.

The soft loans are to be repaid in annual installments within a maximum period

of ten years after the expiration of the grace period from the date of signing the loan

agreement. The grace period is dependent on the type of the project but it cannot exceed

five years from the date of singing the loan agreement.

Besides loans from banks and government, Omani companies raise a significant

amount of funding through equity. Table A.9 exhibits annual numbers and amounts of

equity issues in Oman since the inception of the MSM in 1989. Over the 17 years, a

total of RO 1,958 million was raised which corresponds to 33% of the market

capitalization at the end of 2005. Looking at the figures in the table, it can be seen

clearly that the Omani market began functioning as a marketplace to supply capital to

domestic companies around 1993-1994, several years after its initial commencement.

The number of issues by existing public joint stock companies far exceeds those by new

public joint stock companies and closed joint stock companies. However, the value of

issues for new public joint stock companies is much higher than those by existing public

joint stock companies and closed joint stock companies.

258

Table A.9. Annual Number and Amount of Equity Issues in Oman (1989-2005) Inv. Funds Closed Joint

Stock Comp. New Public Joint Stock

Comp.

Existing Public Joint Stock Comp.

Total Period

No. of issues

(Value RO mil.)

No. of issues

(Value RO mil.)

No. of issues

(Value RO mil.)

No. of issues

(Value RO mil.)

No. of issues

(Value RO mil.)

1989 0 0.0 3 1.7 7 26.1 1 0.7 11 28.5 1990 1 1.0 3 10.1 1 14.7 5 8.5 10 34.3 1991 0 0.0 3 0.4 2 3.7 1 3.1 6 7.2 1992 1 1.0 6 14.6 2 1.4 4 4.3 13 21.3 1993 0 0.0 3 1.1 7 38.9 0 0.0 10 40.0 1994 1 20.4 6 1.1 11 51.9 6 33.7 24 107.1 1995 2 7.4 4 4.3 10 25.3 5 10.2 21 47.2 1996 2 10.5 5 12.6 17 60.6 2 1.3 26 85.0 1997 1 10.5 0 0.0 23 180.3 11 103.1 35 293.9 1998 2 62.3 20 83.7 10 81.9 13 132.1 45 360.0 1999 0 0.0 12 39.9 1 2.0 3 12.4 16 54.3 2000 0 0.0 5 7.9 1 5.5 11 18.8 17 32.2 2001 0 0.0 8 28.8 0 0.0 14 46.9 22 75.7 2002 1 6.4 4 2.5 2 10.8 11 15.1 18 34.8 2003 0 0.0 3 8.7 2 8.0 23 47.9 28 64.6 2004 0 0.0 8 152.9 4 30.8 30 67.3 42 251.0 2005 2 13.8 12 11.8 4 314.9 34 80.1 52 420.6 Total 13 133.3 105 382.1 104 856.8 174 585.5 396 1,957.7Source: Capital Market Authority

While leasing provides an important financing alternative to traditional funding

sources in many countries, this is not the case in Oman. In an attempt to “beef up”

supply and to encourage firms to use this source, the government introduced leasing

legislation in 2000. Unfortunately, not many firms take an advantage of the leasing

industry and it remains relatively unused as a source of financing in Oman (Central

Bank of Oman Annual Report (2001)).

259

Appendix B

A Review of the Literature on Capital Structure

B.1. Introduction

How do firms choose their capital structure? What are the driving factors behind

capital structure decisions? While numerous studies attempted to address these

questions, the answers are still far from conclusive. The number of theories has

expanded rapidly since the path breaking theory formation by Modigliani and Miller

(1958; MM hereafter). They show that in an idealized world without taxes, the value of

a firm is independent of its debt-equity mix. Therefore, an optimal capital structure can

not be identified. In short, the value of a firm is invariant to its capital structure.106 This

proposition is based on some restrictive assumptions, e.g. a perfect capital market, no

bankruptcy costs, no taxes, and full information. By gradually replacing the perfect

capital market assumptions by a more realistic one’s, many potential answers are added

to the original theoretical framework. However, the picture is far from complete, and

the issue continues to offer a wide range of unresolved problems and controversies to be

tackled.

106 Recently, Jayaraman (2006) finds a positive association between debt and firm value when he accounts for the endogeneity of debt. In particular, he shows that increasing the level of debt by a dollar increases firm value by 13 cents. Consistent with the tax penalty of debt, they find that the tax benefit of debt is higher for firms that pay dividends than for those that do not.

260

The literature on the choice of capital structure can be divided into two parts:

theoretical models and empirical studies. In this appendix, the theoretical literature is

presented in Section B.2 and the empirical literature is discussed in Section B.3.107

B.2. Capital Structure Theory

In their efforts to understand the incentives for firms to use debt, finance scholars

put forward different theories. Each theory explains one or more of the determinants.

This section presents an overview of these capital structure theories. The structure of

this part follows the main line in the literature. In section B.2.1, the theorems of

Modigliani and Miller (1958) are presented. Section B.2.2 discusses the agency theories

of capital structure. The tradeoff theory of capital structure is presented in Section

B.2.3. In Section B.2.4, packing order theory is analyzed. Finally in Section B.2.5, we

describe market timing theory.

B.2.1. Modigliani and Miller Theorem

The first modern theory of corporate capital structure began with the celebrated

paper of MM (1958). In this paper Nobel laureates Franco Modigliani and Merton

Miller provide the formal proof of their now famous MM irrelevance proposition. To

derive their propositions, MM assume a world without any market imperfections like

taxes, transaction costs or asymmetric information. Their premise is that valuation of

firms depends solely on the company’s investment policy and not on how they are

financed. 107 See Frank and Goyal (2005) for a detailed review of the capital structure literature.

261

Modigliani and Miller theorem reveals that there would be arbitrage

opportunities in perfect capital markets if the value of the firm depends on how it is

financed. Furthermore, their theorem argues that if investors and firms can borrow at

the same rate, investors can neutralize any capital structure decisions the firm’s

management may take.

While MM capital structure irrelevance theorem clearly rests on unrealistic

assumptions, it can serve as a starting point to search for factors that influence capital

structure policies. In this vein, MM (1958, p. 296) conclude their article with the

following statement regarding the assumptions in their study: “having served their

purpose they can now be relaxed in the direction of greater realism and relevance, a task

in which we hope others interested in this area will wish to share.”

Since then, there have been numerous studies which have investigated

imperfections in the real world and have rejected the theory of capital structure

irrelevancy. The theoretical hypotheses tested in this study are mostly related to the

tradeoff theory, pecking order theory, agency theory, and market timing theory.

B.2.2. Agency Theory of Capital Structure

A significant portion of research has been devoted to models in which capital

structure is determined by agency costs, i.e., costs due to conflicts of interest.108 Ever

since Berle and Means (1932), research on corporate governance has stressed the

adverse consequences of the separation of ownership and control in corporations.

Jensen and Meckling (1976) initiate research on this area by building on the earlier work 108 See Fleming, Heaney, and McCosker (2005) for a discussion of the agency costs and ownership structure.

262

of Fama and Miller (1972). Under this framework, Jensen and Meckling (1976) argue

for the inevitability of agency costs in corporate finance. Managers are agents of the

shareholders and their interest may be in conflict. Managers may act in their own

interest, seek higher than market salaries, perks, power, empire building, and job

security. In order to increase their bargaining’s power, they may undertake entrenching

investments, which adapt the firm’s assets and operations to the managers’ skills and

knowledge (Shleifer and Vishny (1989)).109 According to Jensen and Meckling (1976),

agency costs can be triggered by two types of conflicts; conflicts between managers and

shareholders and shareholders and bondholders.

The separation of ownership and control between managers and shareholders

arise when managers hold less than 100% of the residual claim. As a result, managers

do not capture the entire gain from their profit while they bear the entire cost of wealth

maximizing activities. Consequently, managers have the incentive to invest less effort

in managing the firm’s resources and may transfer firm resources to their own personal

benefit. Such misbehaviour can be redirected by share ownership, compensation

schemes, or other incentives. This leads us to Jensen’s (1986, p. 323) free cash flow

theory which states “The problem is how to motivate managers to disgorge the cash

rather than investing it below the cost of capital or wasting it on organizational

inefficiencies.”

As Myers (2001, 2003) postulates, the answer to Jensen’s problem can, in some

circumstances, be debt financing. An increase in the relative amount of debt increases

109 Berger, Ofek and Yermack (1997) find an inverse relationship between leverage and several measures of managerial entrenchment. Garvey and Hanka (1999) report evidence that legal changes that protects firms from takeovers lead to lower leverage.

263

the fixed obligations of the firm and reduces the funds over which the management has

discretion. If managers spend excessively on prerequisites, and as a consequence, fail to

meet the fixed debt obligations, the debtor will have the firm declare bankrupt.

Bankruptcy is costly for managers since they may be displaced and thus lose their job

benefits. Grossman and Hart (1982) point out that if bankruptcy is costly for managers

because they lose benefits of control and reputation, then debt can create an incentive for

managers to work harder, consume fewer perquisites, and make better investment

decisions. In the same vein, Lang, Ofek, and Stulz (1996) articulate that managers lose

their jobs and reputations in the event of bankruptcy. They may wish to choose a debt

ratio that is less than optimal to reduce the risk of going bankrupt.

In Jensen (1986) as in Grossman and Hart (1982), managers who make decisions

regarding the financial structure of the firm will voluntarily commit to use debt such that

agency problems are reduced. Zwiebel (1996) describes a model of voluntarily

bonding.110 In this dynamic model, constant pressure from a potential discipliner,

partially limited by managerial entrenchment, ensures that the management commits

voluntarily to debt. Similar to Jensen (1986), Stulz (1990) argues that since debt

commits the firm to pay out cash, it reduces the amount of cash available to managers to

indulge themselves with perquisites and value destroying investments.111

Another type of agency conflict is the one between shareholders and

bondholders.112 These conflicts may arise because of the firms’ incentive to maximize

110 Similar arguments are described in Garvey and Hanka (1996) and Novaes (2003). 111 See also Harris and Raviv (1990), Hart (1993), and Hart and Moore (1995). 112 Recently, Titman and Tsyplakov (2005) develop and calibrate a dynamic capital structure model and find that the conflicts of interest between shareholders and bondholders and financial distress costs have a first order effect not only on the level of target debt ratio but also on how debt ratios evolve over time.

264

market value of equity rather than total firm value. The shareholders are willing to

invest suboptimally in more risky projects. If a risky investment succeeds, the

shareholders realize a good return; if it fails, the firm goes bankrupt and the bondholders

bear most of the consequences of the default because of limited liability to shareholders.

Consequently, shareholders may benefit from investing in risky projects, even if this

investment results in reduction in firm value. This effect is generally called “asset

substitution effect” which is an agency cost of debt. Asset substitution effect suggests

that shareholders expropriate wealth from the bondholders by substituting the current

assets for more risky assets.

Smith and Warner (1979) describe direct wealth transfer conflicts. By means of

an excessive increase in dividends, shareholders can increase their wealth at the expense

of bondholders. Likewise, the issuance of debt with high priority can expropriate wealth

from current bondholders. Myers (1977) describes the underinvestment problem that is

caused by shareholder-bondholder conflict. He points out that when firms are likely to

go bankrupt in the near future, shareholders may have no incentive to contribute new

capital, even for value increasing projects. The reason is that while shareholders bear

the entire cost of the investment, the bondholders may capture most of the returns. On

the other hand, Harris and Raviv (1990) suggest that firms’ managers are willing to

continue current operations even if the shareholders prefer liquidation due to poor cash

flow. In this case, debt financing reduces the shareholders’ costs of conflicts by giving

the firm’s bondholders the option of liquidation if cash flow is low. However,

bondholders require information about the firm’s prospects prior to making a liquidation

decision. The optimal capital structure is defined as a tradeoff between the benefits of

265

debt financing, resulting from an improvement in liquidation decision, and required

investigation costs.

In summary, agency theory of capital structure imply that debt is chosen, in a

rather complex fashion, to reduce the capacity of the managers to act in a manner

contrary to the welfare of shareholders and to reduce the capacity of shareholders to act

in a manner contrary to bondholders interests. This theory results in both costs and

benefits of debt versus equity. The presence of characteristics that are likely to increase

(decrease) the conflict between shareholders and bondholders are expected to result in

an increase (decrease) in the costs of debt. These characteristics are expected to be

inversely associated with debt. On the other hand, conflicts of interest between

management and shareholders may be controlled by debt. Characteristics that induce

(reduce) perquisite consumption, such as perks and empire building, are expected have a

positive (negative) relationship with debt.

B.2.3. Tradeoff Theory of Capital Structure

The tradeoff theory of capital structure has dominated the capital structure

literature. This theory says that a firm will borrow up to the point where marginal

benefit of tax savings on additional unit of debt is just offset by the increase in the

present value of possible costs of financial distress.113 The tradeoff theory is

summarized in Myers (1984, p. 577) as follows: “The firm is portrayed as balancing the

value of interest tax shields against various costs of bankruptcy of financial

113 There are many studies that investigate financial distress costs including Baxter (1967), Kim (1978), Andrade and Kaplan (1998), and Damodaran (2002). Warner (1977) documents that direct financial distress costs are around 4% of the market value of the firm one year prior to bankruptcy. One the other hand, Altman (1984) estimates indirect financial distress costs at 10.5% of firm value.

266

embarrassment. Of course, there is controversy about how valuable the tax shields are,

and which, if any, of the costs of financial embarrassment are material, but these

disagreement gives only variations on a theme. The firm is supposed to substitute debt

for equity, or equity for debt, until the value of the firm is maximized.”

Robichek and Myers (1966) provide an early formal treatment of the tradeoff

between the tax advantage of debt and the costs of financial distress. In a state-

preference framework, corporate taxes and costs of bankruptcy are included. They

suggest that there is a positive association between market value and leverage for firms

with little debt. However, the value of the firm should decrease if leverage is very high.

Kraus and Litzenberger (1973), Scott (1976), and Kim (1978) provide alternative models

that also yield a firm-specific optimal capital structure, based on the tradeoff between

tax benefits and financial distress costs of debt.114 Myers (1984) reviews this framework

and refers to it as the static tradeoff framework. Within this framework, an interior

optimal capital structure exists. Each firm has an optimal debt ratio and aiming at

maintaining the actual debt ratios as close as possible to the optimum. The optimal debt

ratio is referred to as the target debt ratio. The target debt ratio differs between firms

because of the influence of taxation and financial distress costs. In addition, this ratio

depends on weighting the savings advantage of debt against the deadweight costs of

financial distress. In case immediate adjustment is costly, the theory implies a target-

adjustment model which is not observed directly (Myers (2003)). Successful early tests

of target-adjustment models include Taggart (1977), Jalilvand and Harris (1984),

114 Kraus and Litzenberger (1973) provide a state-preference model with wealth taxes and bankruptcy costs. Scott (1976) assumes risk indifference, bankruptcy costs due to imperfections in secondary markets, and corporate taxes. Kim (1978) employs capital asset pricing model, costly and stochastic bankruptcy, and corporate taxes.

267

Auerbach (1985), and Hovakimian et al. (2001). The tradeoff theory of capital structure

has been developed in many papers including DeAngelo and Masulis (1980), Bradley et

al. (1984), Barclay and Smith (1999), and Myers (2003).

In summary, the tradeoff theory posits that each firm can maximize its market

value by choosing the optimal debt ratio. In this context, firms try to rebalance the tax

benefits of debt with costs of firm distress. This theory predicts that firms will increase

their value by moving towards their target debt ratio, while a value reduction should be

observed if they move further from their target debt ratio.

B.2.4. The Pecking Order Theory

In their pioneering work, Myers (1984) and Myers and Majluf (1984) propose an

alternative to the tradeoff theory of capital structure.115 Their theory is based upon the

idea of asymmetric information between managers and investors. Myers and Majluf

(1984) propose that capital structure is constructed to alleviate inefficiencies caused by

the fact that managers know more about the true value of the firm and the firm’s

riskiness than less informed outside investors. If the information asymmetry results in

an underpricing of the firm’s equity and the firm are required to finance a new project by

issuing equity, the underpricing may be so severe that new investors capture most of the

net present value (NPV) of the project, resulting in a net loss to existing shareholders.116

115 Myers (1984) notes that the pecking order hypothesis is not new (Donaldson (1961)), even if the term is new. Much literature has extended the pecking order theory. See Lucas and McDonald (1990) and Viswanath (1993). 116 When managers are aware that the current market value of the firm is lower than the fair value based on their superior information about the firm, then they will be reluctant to issue new securities at the depressed price. In contrast, managers may be more willing to issue new securities when they view the firm to be overvalued. If shares are issued under such circumstances, there will be a wealth transfer from

268

Hence, managers who work in the best interest of the current shareholders will reject the

project even if its NPV is positive. To avoid this underinvestment problem, they finance

projects first with retained earnings, which have no adverse selection problem, then with

safe debt, for which the adverse selection problem is negligible, then with risky debt,

and with equity only as a last resort.

The pecking order theory is able to explain why firms tend to depend on internal

sources of funds and prefer debt to equity if external financing is required. It also

explains why more profitable firms borrow less which is because profitable firms have

more internal financing available. Firms that do not generate a lot of profits required

more external financing and as a result accumulate more debt. Hence, the firms’ debt

ratio is not driven by the tradeoff theory, but it is simply the cumulative results of the

firm’s attempts to mitigate information asymmetry. This is a theory of leverage in

which there is no notion of an optimal debt ratio. This theory predicts that the financing

deficit is the main determinant of debt issue and firms will use external financing only if

retained earnings are inadequate to finance the firm’s growth opportunities. If external

financing is required, the pecking order theory predicts firms to issue the safest security

it can, given that the cost of financial distress is ignored. This implies that firms will

first issue debt and then equity. Firms will issue equity (suffer from serious adverse

selection problem) only when debt is costly, for example when the firm is already at

dangerously high debt ratio where managers and investors foresee costs of financial

distress (Myers (2003)). Myers (1984) refers to this hierarchy of financing that starts

new to old shareholders when prices eventually settle at their fair value. The result of this behaviour is that new issues imply bad news and are likely to be associated with price reduction.

269

with retained earnings, followed by safe debt, then risky debt, and finally with equity as

pecking order theory of financing.

Several empirical studies such as Baskin (1989), Norton (1991), and Griner and

Gordon (1995) have reported evidence in support of the pecking order theory. Shyam-

Sunder and Myers (1999) test the tradeoff theory against the pecking order model. Their

study reports evidence that the pecking order theory is an excellent first order descriptor

of corporate finance behaviour.

In short, the pecking order theory is an important theory of capital structure.117

This theory fundamentally relies upon information asymmetry and adverse selection

costs. It predicts that firms will use internal funds first, debt second, and equity last.

B.2.5. Market Timing Theory

Equity market timing is one of the primary factors that shape corporate financing

decisions. A large body of work documents the fact that firms time the equity markets

in their security issuance decisions. Starting with Taggart (1977), numerous studies

have demonstrated the tendency of firms to issue equity when their market valuations

are high relative to book values or past market returns.118 Subsequent studies by Marsh

(1982), Asquith and Mullins (1986), Korajczyk et al. (1991), Jung et al. (1996), and

Hovakimian et al. (2001) report evidence of a positive association between seasoned

equity offerings and market valuations. Loughran et al. (1994) and Pagano et al. (1998) 117 Brennan and Kraus (1987), Noe (1988), and Constantinides and Grundy (1989) document that the pecking order does not necessarily obtain if financing choice include hybrid securities or share repurchases. 118 Studies of Taggart (1977), Marsh (1982), Jalilvand and Harris (1984), and Asquith and Mullins (1986) use past stock returns to measure market timing. Recent studies by Rajan and Zingales (1998), Jung et al. (1996), Pagano, Panetta, and Zingales (1998), Hovakimian et al. (2001), and Kayhan and Titman (2006) employ market-to-book ratio as a measure of market timing.

270

show that initial public offerings coincide with high market valuations. Ikenberry et al.

(1995) report evidence of a negative association between equity repurchases and market

valuations. Loughran and Ritter (1995) and Spiess and Affleck-Graves (1995) report

evidence of firm underperformance following equity issues. On the debt side, there is

evidence that firms time their debt issues to periods when conditions are favourable. In

this line, Guedes and Opler (1996) postulate that firms issue long-term debt when its

future returns are predictability low. Baker et al. (2003) assert that managers time their

long-term debt issues to periods when prices of long-term debt are high. In the Graham

and Harvey (2001) survey, CFOs admit that timing consideration play a very important

role in their financing decisions.

The market timing theory of capital structure is recently advanced by Baker and

Wurgler (2002). In this influential study, Baker and Wurgler attempt to capture market

timing by focusing on historical market-to-book ratio. In particular, their timing

measure is a weighted average of the firm’s past market-to-book ratios, where the

weights are the past amounts of external capital raised by the firm. Their study report

evidence that firms with low debt ratio tend to raise funding when the market valuations

are high, and vice versa. Baker and Wurgler claim that equity market timing has large

and lasting effect on capital structure that persists for at least a decade. The theory

asserts that a firm’s capital structure is merely the cumulative results of past attempts to

time the equity market. In particular, they argue that firms fail to readjust their debt

ratio after issuing equity in an attempt to time the market. In this theory, there is no

optimal capital structure. Consequently, capital structure is solely the cumulative

271

outcome of attempts to time equity markets and firms are no more or less likely to

rebalance their debt ratio in response to these timed equity market issuances.

A close relative paper to Baker and Wurgler is Welch (2004). While both Baker

and Wurgler and Welch (2004) investigate the influence of past stock returns on capital

structure, there is an important difference between the two studies. Baker and Wurgler

are more interested in how the past stock returns affect the active issuing activity of

firms and fail to consider the implied change. Welch focuses more on the implied

change. Welch argues that firms fail to readjust their capital structure in response to

shocks in the market value of their equity despite fairly active net debt issuing. He

asserts that variation in market equity is the primary known explanatory determinant of

capital structure and capital structure changes, and the motivation behind corporate net

issuing activity is largely a mystery. Welch finds that over one year, the average firms

show no tendency to readjust to its previous debt ratio and rather allows its debt ratio to

drift almost one to one with stock returns. In longer horizons (over five to 10 years),

firms start to readjust but the impact of stock return remains to dominate any effect of

rebalancing. Thus, Welch concludes that firms fail to readjust their capital structures,

even over horizons as long as five years.

B.3. Review of Related Empirical Studies

B.3.1. Introduction

The objective of this section is to present the important contributions in the

empirical capital structure literature. We focus on the factors that determine capital

structure dynamics. The organization of this section is based on approaches used in

272

other empirical studies. Section B.3.2 discusses empirical studies on the US. Studies on

other countries are described in section B.3.3.

B.3.2. Empirical Studies in the US

Due to the easy accessibility to reliable data, most of the studies on capital

structure are carried using data on firms in the US. Schwartz and Aronson (1967) are

among the first to examine the determinants of capital structure in the US on four

industries with eight firms. They find that differences exist between industries and these

differences persist in their period of study which is from 1923 to 1962. Subsequent

studies for the US by Ferri and Jones (1979), Castanias (1983), and Bradley et al. (1984)

use several proxies that are based on accounting and stock price data to examine the

determinants of leverage.119 Notably none of these studies included variables to

represent profitability -the key factor said to affect the capital structure, according to the

pecking order theory.

A growing strand of the literature focuses their attention on testing capital

structure theories. For example, Baskin (1989) tests the pecking order theory by

studying the debt ratios of firms and their relationship to past profitability. The results

strongly support the argument that firms with higher past profits typically tend to have

lower leverage. However, Baskin does not include proxies for most of the “traditional”

determinants, such as risk, asset composition, and NDTS. In a test of the stakeholder

theory, Barton, Hill and Sundaram (1989) include a measure of the product-relatedness

criterion suggested by Rumelt (1974) as a proxy for the presence of stakeholders, in

119See Harris and Raviv (1991) survey for a discussion and summary of these papers.

273

addition to proxies for profitability, growth, risk and other commonly used determinants.

Their results indicate that the presence of “stakeholders” tend to decrease leverage.

One of the most insightful capital structure studies is Titman and Wessels (1988).

They undertake a comprehensive study, testing both tradeoff and pecking order theories

in a more general framework. They use three types of debt instruments as measures of

short-term, long-term, and convertible debt instead of an aggregate measure of total

debt. The innovative aspect of Titman and Wessels is the treatment of the proxy

problem. They apply a confirmatory factor analysis technique for estimating the impact

of unobservable attributes on the choice of corporate debt ratios. Using 469 US firms

over 1974-1982, they observe that debt levels are related negatively to the uniqueness of

a firm's line of business and transaction costs is an important determinant of capital

structure choice. They find a negative association between short-term debt ratios and

firm size. Using market values, they report a significant negative association between

debt ratios and profitability. For the book values, they find a significant positive

association between debt ratios and growth. Titman and Wessels findings are consistent

with the predictions of the pecking order theory. In contrast, Helwege and Liang (1996)

investigate a small sample of IPO firms. They find that issuance decisions are weakly

related to the size of the financing deficit, leading them to reject the pecking order

theory.

Shyam-Sunder and Myers (1999) test both tradeoff theory and pecking order

theory. Their study provides empirical support for the pecking order theory among U.S.

firms. They find little empirical support for the static tradeoff model that predicts that

firms adjust toward an optimal debt ratio. They show that many of the current empirical

274

tests lack sufficient statistical power to distinguish between the theories. On the other

hand, Chirinko and Singha (2000) use three examples to criticize the test conducted by

Shyam-Sunder and Myers (1999) and suggest that the test generates misleading

inferences and that their empirical evidence reported by Shyam-Sunder and Myers can

evaluate neither the pecking order nor static tradeoff models. Hovakimian et al. (2001)

test the tradeoff theory where they find that debt ratios deviate from their suggested

optimum level. The evidence shows that firms tend to accumulate past profits in a

manner that is consistent with the pecking order theory. In contrast, Frank and Goyal

(2002) argue that predictions of the pecking order theory do not hold for samples larger

than Shyam-Sunder and Myers’ and over a longer period. Fama and French (2002)

report evidence that both of the theories explain some of company’s financing

behaviour; and none of them can be rejected.

Lemmon and Zender (2004), using panel data methodology to test Shyam-

Sunders and Myers results, find evidence consistent with the pecking order theory. They

use debt capacity constraint to explain why small growth firms issue equity. Contrary to

Frank and Goyal findings that smaller firms have more potential for asymmetric

information than larger firms, Lemmon and Zender provide evidence that small high

growth firms face lower adverse selection costs than larger firms when issuing equity,

thus argue that the issuing of equity by young, high growth firms is not contrary to the

pecking order theory. Similarly, Agca and Mozumdar (2004) demonstrate that firms

prefer debt to equity before reaching their debt capacity. Mayer and Sussman (2004)

examine capital structure changes for a sample of firms making large investments. They

find that most large investments initially financed with new debt, consistent with the

275

pecking order theory. Following the event year, however, they find some evidence

consistent with the tradeoff theory, as firms move back toward their historic debt ratios.

Autore and Kovacs (2005) find that firms take adverse selection costs into account by

timing their use of internal versus external and debt versus equity. They also find that

firms are increasingly raising equity capital via methods that are less prone to adverse

selection costs. These results are in line with the pecking order hypothesis. On the other

hand, Leary and Roberts (2005b) find that firms often violate the pecking order’s

hierarchy, both by issuing external securities when internal securities are sufficient and

issuing equity in place of debt. They conclude that “even as a conditioner theory of

capital structure, the pecking order appears to struggle” (p. 34). Similarly, Fama and

French (2005) find that equity issues are common even for large firms that are not under

duress which violate the pecking order hypothesis. They state that “our results reject the

pecking order’s central predictions about how often and under what circumstances firms

issue and repurchase equity”. (p. 579).

There is an intensive debate on whether firms rebalance their capital structure

with some studies reporting evidence supporting and others failing to do so. In this vein,

Baker and Wurgler (2002) and Welch (2004) questions whether firms engage in capital

structure rebalancing as implied by the tradeoff theory. Baker and Wurgler (2002) argue

that the impact of firm’s efforts to time the market is highly persistent, and capital

structure is the cumulative results of timed trips to the equity market. Consistent with

inertia, Welch (2004) suggests that firms fail to rebalance their capital structure and

stock returns are the primary determinant of capital structure dynamics. In the same

vein, Kayhan and Titman (2006) investigate how cash flows, investment expenditures,

276

and stock price histories affect capital structure. They use market-to-book timing

measures that are in the spirit of Baker and Wurgler (2002) and show that the firms’

history has a major influence on capital structure. Similar to Welch (2004), Kayhan and

Titman report evidence that stock returns have a primary impact on capital structure

dynamics, and that these effects are at least partially persist for at least 10 years. They

also document that changes in leverage due to stock returns reverse very little.

Likewise, Titman and Tsyplakov (2005) find that changes on stock prices have a strong

effect on capital structure changes and firm move slowly towards their target capital

structures. Huang and Ritter (2005) examine time-series patterns of external financing

decisions. They find that publicly traded U.S. firms fund much a larger proportion of

their financing deficit with external equity when the relative cost of equity capital is low

which is consistent with the market timing theory. In particular, they find that equity

issues are strongly negatively related to the equity risk premium, and that debt issues are

strongly related to the real interest rate. They also find that firms adjust very slowly

toward target leverage even after controlling for the traditional determinants of capital

structure, firm fixed effects, and short time dimension bias. Cai and Zhang (2005) study

the relationship between capital structure dynamics and stock returns using a sample of

U.S. public firms during 1975-2002. They document a significant negative relationship

between leverage changes and the contemporaneous stock returns. In the same vein,

Chen and Zhao (2005a) find that the tradeoff theory does a poor job in explaining the

issuing decisions. Jenter (2005) documents that managers try to actively time the market

both in their private trades and in firm-level decisions. Henderson, Jegadeesh, and

Weisbach (2006) investigate the extent to which firms from different countries rely on

277

alternatives sources of capital and find evidence that market timing considerations play

an important role in security issuance decisions. Xu (2006) examines how fast firms that

rebalance over time adjust their capital structures. Using system GMM, the results show

that firms adjust toward their target capital structure slowly. The observed slow speed of

adjustment is not caused by transaction costs. In particular, large firms do not appear to

adjust more quickly than small firms.

In contrast, Strebulaev (2006) argues that costly adjustment can explain the

phenomenon in Baker and Wurgler (2002) and Welch (2004). Similarly, Leary and

Roberts (2005a) argue that the persistence results of Baker and Wurgler and Welch are

more likely due to adjustment costs and not necessarily market timing or inertia,

respectively. Using unbalanced panel of 127,308 firm-quarter observations for the years

1984-2001, Leary and Roberts (2005a) empirically examine the tradeoff theory of

capital structure, allowing for costly adjustments. After showing that the behaviour of

financing decisions is consistent with direct evidence on external financing costs, they

use a dynamic duration model to show that firms behave as though adhering to dynamic

tradeoff policy in which they actively rebalance their debt level to stay within an optimal

range. These findings are consistent with the previous empirical work that finds mean

reversion in leverage (Jalilvand and Harris (1984), Roberts (2002), and Roper (2002)).

Consistent with Leary and Roberts (2005a), Flannery and Rangan (2006) use

partial adjustment model and report evidence that firms do have target capital structure

which is consistent with the tradeoff theory. In particular, they find that firms closes

about one-third of the gap between its actual and its target debt ratios each year.

Similarly, Liu (2005) and Hovakimian (2006) documents that firms gradually adjust

278

their capital structure in response to various shocks which is in contrast with the market

timing theory.

Alti (2006) examines the capital structure implication of market timing. While

Baker and Wurgler use market-to-book ratio to identify market timers, Alti (2006)

identifies market timers as firms that go public in a hot issue market. His study reports

results that are in contrast with Baker and Wurgler (2002) findings that suggest high

persistence of market timing effects on capital structure. In fact, Alti reports evidence

that the influence of market timing on leverage has very low persistence. His paper

shows that the capital structure impact of this market timing behaviour is largely

transitory. At the end of the second year following the IPO, the influence of market

timing on leverage completely vanishes.120

In a similar vein, Lemmon et al. (2006) find that firms use net security issuances

to maintain leverage ratios in relatively confined regions around their long run mean

which is in line with a dynamic rebalancing of capital structure. Using a panel of

twenty-nine countries, both developed and emerging markets, Farhat et al. (2006) find

that firms partially adjust their capital structures at a higher speed than that observed in

the U.S. firms. In particular, they find that the adjustment rate varies across countries

from 41.4% (Japan) to 67.8% (Norway).

While several studies concentrate on the determinants of capital structure using

debt ratio, there are other studies that attempt to focus on determinates of leverage

changes surrounding some unique events. For instance, Givoly et al. (1992) take

advantage of the Tax Reform Act in 1986 to examine the determinants of capital 120 Inconsistent with Alti (2006), Huang and Ritter find that debt and equity issues last for more than ten years, once the determinants of leverage are controlled for.

279

structure by focusing on the relationship between taxes and leverage. Their study

provides evidence that both corporate taxes and NDTS are determinants of leverage.

Moreover, they provide indirect evidence that personal taxes play a role in firm’s choice

between debt and equity. In general, their results support tax based theories of capital

structure.

Other empirical studies shed some light on some specific characteristics of firms

and industries that appear to determine debt ratios and provide direct evidence on the

likely determinants of the debt ratio. In this area, Barclay et al. (1995) study the effects

of size, growth, signaling, and regulation on debt levels. The study reports a small

economic effect of size on leverage level where results were mixed when regressing the

leverage on total sales as a measure of size. In studying signaling effect, they find a

significant positive relation between the size of the company’s earnings increase and its

leverage ratio. They expected that regulation effectively reduce the possibility for

corporate under-investment agency problem simply by transferring much of

management's discretion over-investment decision to regulatory authorities. Their

results matched the expectation that leverage increases with regulation.

On the other hand, there are some studies that concentrate on the type of debt in

the firm’s capital structure. In this line, Johnson (1998) conducts a study on the effect of

the existence of bank debt on a firm's capital structure. Theoretical and empirical

research suggested that bank debt mitigate the agency costs. His findings are consistent

with the proposition that firms can have higher optimal leverage if they borrow from

banks. This is due to benefits from bank screening and monitoring.

280

Other studies that attempted to examine the determinants of capital structure by

focusing on the choice between an issue of debt or an issue of equity or a combination of

both (this is known as incremental capital structure). For instance, using a data set of

1,747 debt or equity issues over 1977-1987, MacKie-Mason (1990) investigates the

relationship between tax shield and debt equity choice. The results show that firms with

tax loss carry forwards are less likely to issue debt. For these firms, the marginal tax

benefit of debt is less valuable. Investment tax credits do not reduce the likelihood of

issuing debt because these firms are more profitable and pay more taxes. Furthermore,

MacKie-Mason (1990) documents that the probability of issuing equity is increased by

cash deficits, business risk, R&D expenditure, and a change in stock price.

A paper that builds on MacKie-Mason is Graham (1996). The most important

different between the two papers is that Graham (1996) considers changes in the debt

level, and does not exclusively consider debt and equity issues. Graham (1996) argues

that some of the proxies used to calculate tax rates could be misleading and suggests that

a simulated tax variable could perform better. He also asserts that the ability of firms to

carry loss backwards and forwards makes it difficult to use current financial statements

to calculate company’s tax rates. He reports a positive relationship between debt level

and marginal tax rates. Moreover, it is reported that high tax rates firms are more likely

to increase debt, than low tax firms. Furthermore, the study reports that relative taxation

of debt and equity at the personal level has no impact on debt, and the probability of

bankruptcy is insignificant. Building on the Graham (1996), Graham (2000) develops a

new method of calculating the tax rates by estimating a tax benefit function with a kink,

which is supposed to be a guide of whether the firm has fully utilized its debt capacity.

281

His results suggest that firms that are large, liquid and profitable with low expected costs

of financial distress are conservative in their debt usage.

Jung et al. (1996) investigate 276 debt and 192 equity issues over 1977 to 1984

to disentangle the pecking order theory, the agency model, and timing model. They test

the theories using a logistic regression of the incremental security choice. They report a

significant positive coefficient for the market-to-book variable, which indicates that

firms with higher market-to-book ratios are more likely to issue equity.

Opler and Titman (1997) provide a novel idea that allows a test of the influence

of the concept of an optimal capital structure on optimal choices. This paper compares

U.S. firms that issued or repurchased significant amounts of equity between 1978 and

1993 to those that issued or repurchased debt. They find that firms are most likely to

increase debt and repurchase equity when they have less debt than is predicted by a

cross-sectional leverage regression. In addition, the likelihood of issuing debt rises with

the firms' past profitability. Overall, their study confirms previous findings that firms

are most likely to issue equity after experiencing a share price increase.

In a comprehensive study, Frank and Goyal (2004) investigate the importance of

many factors in the capital structure choice of publicly traded firms from 1950 to 2000.

They find that leverage increases with collateral, log of assets, expected inflation, and

median industry leverage and decreases with market-to-book ratio, profits, and

dividends.

An important strand of literature examines the valuation of real options when the

capital structure of the underlying project/firm is levered. In this vein, Mauer and

Triantis (1994) present a real option model of a flexible production plant with a capital

282

structure changing over time as a consequence of an optimal dynamic financing policy.

They provide evidence that operating and financial flexibility are partial substitute.

However, they find no relationship between debt financing and investment policy.

Mauer and Ott (2000) study the influence of agency costs of debt on the optimal

investment policy according to the real options approach. The model taking into

account the benefits of debt and bankruptcy costs shows that equity holders postpone

investment in the growth options compared to the first best strategy of maximizing total

firm value. The difference in value is a measure of agency costs of underinvestment.

Mauer and Sarkar (2005) use a similar setting to Mauer and Ott (2000) and find that

equityholders have a strong incentive to overinvest which significantly decreases firm

value and optimal leverage and significantly increases the credit spread of risky debt. In

the same vein, Childs, Mauer, and Ott (2005) analyze the agency problems of debt on

the optimal investment policy for the firm’s growth options. They document that

partially financing the firm growth options with debt could encourage management to

adopt an investment policy which maximize firm value rather than equity value. Stated

differently, the agency cost of underinvestment is reduced when investments is financed

with debt. They also provide evidence that financial flexibility encourages the firm to

choose short-term debt and hence reducing the agency costs of under- and

overinvestment. Leỏn, Gamba, and Sick (2003) study the influence of debt financing on

both the value of real options and on the investment policy. The main result from their

analysis is that a higher leverage increases the value of the option to delay investment

and increases the likelihood of investing, hence reducing the time-value of the option to

delay investment. Likewise, Hackbarth (2004) investigates the interactions between

283

financing and investment decisions in the presence of managerial optimism and

overconfidence. He integrates an earnings-based capital structure model into a real

option framework. He shows that the framework is consistent with a negative

association between leverage and investment opportunities.

B.3.3. Studies on Other Countries

There are few studies that attempted to validate capital structure theories using

international data. The works of Stonehill and Stitzel (1969), Remmers, Stonehill,

Wright, and Beekhuisen (1974), and Toy, Stonehill, Remmers, Wright and Beekhuisen

(1974), may be regarded as the first empirical studies that investigated directly capital

structure choice using international data. The combined evidence in these studies

suggests that the home country of a corporation is a significant determinant of capital

structure. Conflicting evidence is reported regarding the impact of other variables,

including risk, growth, industry, and firm size. Aggarwal (1981) analyzes the capital

structure of the 500 largest European corporations and report evidence suggesting

industry and home country as the most significant determinants of corporate leverage.

Errunza (1979) and Aggarwal and Baliga (1987) report similar results for corporations

from Latin American countries. In a recent paper, Aggarwal (1991) examines capital

structure differences among large Asian corporations and suggests that country and

industry classifications are important determinants of capital structure. For the UK,

Marsh (1982) analyzes the choice of financing instruments and find company debt level

to be influenced by market conditions and historical security prices. Specifically, using

a logit model, Marsh provides evidence that UK firms are more likely to issue debt

284

(equity) when they expect other firms to issue debt (equity) and more likely to issue

equity if the previous share return exceeds that of the risk-adjusted market portfolio.

Furthermore, his results suggest that the likelihood of issuing debt and equity in the UK

is a function of the deviation of the debt ratio from its target level. In particular, his

study reports that firms are more likely to issue debt if their current long term debt is

below a target measured by the average of the previous 10 years. The paper also

provides evidence that long-term target debt levels are influenced by operating risk,

company size, and asset compositions.

Another study that examines the determinants of capital structure for the UK is

Ozkan (2001). In this paper, Ozkan extends the empirical research on this topic by

focusing on the dynamics of capital structure decisions and the nature of adjustment

process. The innovation in this paper is the use of a much stronger estimation technique

which is panel data and GMM which help control for endogeneity. The endogeneity

problem arises because observable as well as unobservable shocks affecting capital

structure are also likely to affect some of other firm specific characteristics like market

value of equity. The use of panel data and GMM help mitigates this problem by

including firm-specific effects and time dummies. He documents that firms have target

debt ratios and they adjust to the target ratio relatively fast. Another major finding is

that liquidity and profitability are negatively associated with the debt level whereas there

is a positive association between past profitability and leverage. Other empirical work

on capital structure for the UK include Bennett and Donnelly (1993), Lasfer (1995a),

and Walsh and Ryan (1997). Bennett and Donnelly (1993) examine the determinants of

capital structure for non-financial UK firms and report evidence that NDTS, asset

285

structure, size and profitability have a significant impact on the choice of capital

structure. Lasfer (1995a) examines the impact of the corporation tax and agency costs

on the firm’s capital structure choice by exploiting both the cross-sectional and time-

series variations in the capital structure of firms. His results suggest that firms that are

more likely to have free cash flow problems borrow less and firms with fewer growth

opportunities have more debt. He also provides evidence that corporate tax is not an

important determinant of firm’s capital structure decision in the short run. In contrast,

Walsh and Ryan (1997) examine a binomial choice model based upon observed debt and

equity issues. Their results suggest that agency and tax considerations are important in

firm’s capital structure choice in the UK.

In the same vein, Bhaduri (2002) investigates capital structure of Indian firms

where he addresses the measurement problem that arises due to the unobservable nature

of the attributes affecting the optimal capital structure. Similar to previous studies,

Bhaduri documents that the optimal capital structure is determined by size, cash flow,

growth, and product and industry characteristics. For Australia, Chiarella, Pham, Sim,

and Tan (1992) use a sample of 226 firms from 1977 to 1985. They report evidence

consistent with the DeAngelo and Masulis (1980) theory that firms with NDTS can use

them as substitutes for interest tax shields. They also find a significant negative

association between profitability and debt which is in line with the pecking order

hypothesis. More recently, Akhtar (2005) examines capital structure of Australian

multinational and domestic corporations from 1992 to 2001. He documents that the

level of leverage does not differ significantly between multinational and domestic firms.

286

Using data from Switzerland, Drobetz and Fix (2005) test leverage predictions of

the tradeoff and the pecking order model. They document that more profitable firms

utilize less leverage which is consistent with the pecking order theory. They also find

that firms with more investment opportunities have less leverage which is consistent

with both the tradeoff model and a complex version of the pecking order theory. Chen

(2004) examines the determinants of capital structure of Chinese-listed firms using panel

data. He reports evidence that neither the tradeoff theory nor the packing order model

has robust explanatory power in explaining capital structure of Chinese firms. For the

same country, Tong and Green (2005) test the pecking order theories using a cross-

section of the largest companies in China. They find a significant negative association

between leverage and profitability. They conclude that the pecking order theory

explains the capital structure of Chinese listed companies better than the tradeoff theory.

Chang et al. (2006) examine whether Japanese firms time the market by

scheduling their equity issuances at times when the stock prices are high. They report

evidence consistent with equity market timing. They also find that keiretsu firms time

the market more than non-keiretsu firms.

There are few studies focusing on cross-country analysis, although Singh and

Hamid (1992) is a notable exception. They used data from nine developing countries

from various locations over the world for the period 1980-1988. They show debt to be

positively correlated with firm size and negatively related to growth and profitability.

They also document that firms in developing countries follow an exact reverse of the

pecking order theory. Singh (1995) extends the data in the original paper to include

more firms and one more developing country. He documents that external equity is the

287

major source of financing for developing countries. By contrast, developed countries

use external equity to finance mergers. Furthermore, he shows that the conclusion of

Singh and Hamid are robust to the inclusion of the new data.

Though Singh and Hamid (1992) are among the first to focus on cross country

analysis on the developing countries, the first study to publish an international

comparison on determinants of capital structure in one of the leading finance journals is

Rajan and Zingales (1995). They analyze financing patterns and examine the

determinants of capital structure in the G-7 countries. The determinants are the four

year (1987-1990) averages of fixed assets scaled by total assets as a measure of

tangibility, the logarithm of sales as a size proxy, the market to book ratio, and a

measure of profitability. The countries involved in the study are the US (2079) firms,

Canada (175) firms, France (117), the United Kingdom (552) firms, Japan (316) firms,

Italy (96) firms, and Germany (175) firms. In an effort to test the robustness of capital

structure models developed with US data, they observe that all countries have

approximately the same level of debt, but the UK and Germany appeared to have the

lowest debt level. When examining external financing patterns (debt vs. equity) they

also could not find any differences between market based and bank based countries.

Rajan and Zingales (1995) find that factors correlated with leverage in the U.S appear to

be similarly correlated in other industrialized countries. Specifically, there is a negative

association between the debt level and growth and profitability and a positive

association with size and tangible assets.

Wald (1999) examines capital structure in the US, Germany, France, and the UK,

and provides evidence that differences in tax policies and agency problems explain

288

differences across countries. The results suggest links between capital structure

decisions and legal and institutional differences. Demirgüç-Kunt and Maksimovic

(1999) test firm debt maturity in 30 countries during the period 1980-1991. Their results

suggest that large firms in countries with active markets have more long-term debt,

whereas small firms in countries with large banking sectors tend to have longer maturity

debt.

In the same vein, Antoniou, Guney, and Paudyal (2002) analyze the determinants

of capital structure of French, German, and British firms using panel data. They find

that leverage ratios are positively related to the size of the firm and negatively related to

the market-to-book ratio, term-structure of interest rates, and share price performance in

all sample countries. However, they document that fixed-assets ratio, equity risk

premium, profitability, and effective tax rates have different degree and direction of

influence on leverage across the sample countries.

While these studies deal with developed countries, Booth et al. (2001) extend the

international study of capital structure determinants to ten developing countries. In this

study, they assess whether capital structure choices is portable across countries with

different institutional structures. They provide evidence that the factors that are relevant

in explaining capital structures choice in developed countries are also relevant in

developing countries. On the other hand, there are systematic differences in the way this

factors work across countries, which suggests that country-specific factors are major

determinants of capital structure in emerging markets. These country-specific factors

include institutional framework, legal and accounting practices, financial development,

and the macroeconomic environment. Similar to Rajan and Zingales (1995), they report

289

that leverage is positively associated with tangible assets and firm size, but negatively

related to profitability. However, the signs on some of the coefficients, particularly

business risk and market-to-book ratio are, sometimes the opposite of what we would

expect. They explain that by the high dependence of firms in developing countries on

short-term debt and trade credit, which have different determinants than long-term debt.

Furthermore, they point out that empirically distinguishing between the tradeoff and

pecking order theories has proven difficult because variables that describe one model

can also be classified as other model variables. Partly because of this, many recent

empirical studies have engaged cross-sectional tests and a variety of factors that can be

justified using any of these two models.

Recently, Deesomask et al. (2004) examine the determinants of capital structure

of firms in four Asia-Pacific countries namely, Thailand, Malaysia, Singapore, and

Australia. They find that the capital structure choice is not only the product of a firm’s

own characteristics but also the results of legal framework and institutional environment

of the countries where they operate. Using a sample from 39 countries, Fan, Titman,

and Twite (2004) provide evidence that country-specific factors have a strong influence

on firm’s capital structure decision. In a similar vein, Song and Philippatos (2004) study

capital structure using data from 30 OECD countries and document that most cross-

sectional deviations in capital structure are caused by heterogeneities of firm, industry,

and country-specific factors. De Jong et al. (2005) examine the importance of firm-

specific and country-specific factors in explaining capital structure using a larger sample

from 42 countries for a period from 1997 to 2001. Their sample comprises of 11,819

firms (59,095 firm-year observations). They document across a large number of

290

countries that the influence of risk, firm size, tangibility, profitability, and growth are

significant and in line with the extant capital structure models. They also show that

country-specific variables have a strong impact on firm’s capital structure. In the same

vein, De Hass and Peeters (2006) investigate the capital structure dynamics of Central

and Eastern European firms and find that profitability and age are the most robust

determinants of capital structure.

Using survey data, Brounen, Jong, and Koedijk (2004) compare managerial

views from four European countries (UK, The Netherlands, Germany, and France) on

the theory and practice of corporate finance. They document that firm size is the most

important determinant of capital structure and national differences play only a minor

role in explaining cross-sectional variations of capital structure. Using a larger sample,

Bancel and Mittoo (2004) investigate the determinants of capital structure in 16

European countries. They follow the same approach in Graham and Harvey (2001).

They provide evidence that financial flexibility and earnings per share dilution are the

most important determinants in issuing debt and equity, respectively. They also find that

managers use “window of opportunity” to raise capital.

291

Appendix C

Variable Definitions

The next section presents the definitions of variables used in Chapter 2.

Dt: The sum of current liabilities and long-term liabilities.

Et: Market Value, the number of shares outstanding multiplied by the closing price at the

end of the fiscal year.

Assets: the sum of current assets and long-term assets.

tADR : Actual Debt Ratio: )( ttt EDD +

kttIDR +, : Implied Debt Ratio: )]1([ , kttttt xEDD ++⋅+

kttx +, : Stock returns without dividends, from “Share-Holding Guide of MSM Listed

Companies”

kttr +, : Stock returns with dividends, from “Share-Holding Guide of MSM Listed

Companies”

kttTDNI +, : Difference in total debt value: tkt DD −+ .

kttENI +, : Difference in total equity value without return and dividend effects:

).1( ,, ktttktt xEE ++ +⋅−

tkttkttktt ExrDiv ⋅− +++ )(: ,,,

Government Ownership: Percentage of government ownership as obtained from

“Share-Holding Guide of MSM Listed Companies”

Signaling, Dividends: dividend payment divided by net income. Winsorized at 2% and

98%.

292

Interest coverage: earnings before interest and tax divided by interest expense.

Winsorized at 2% and 98%.

Profitability, Assets: operating income divided by total assets. Winsorized at 2% and

98%.

Profitability, Return on Assets: earnings after tax dividend by total assets. Winsorized

at 2% and 98%.

Profitability, Sales: operating income divided by sales. Winsorized at 2% and 98%.

Profitability Changes: Profitability divided by sales, an average from t to t+k, minus

profitability divided by sales at t-2. Not winsorized.

Tangibility: property, plant, and equipment, divided by total assets. Winsorized at 2%

and 98%.

Size, Sales: log of sales. Not winsorized.

Size, Assets: log of total assets. Not winsorized.

Non-debt Tax Shields: depreciation expense dividend by total assets. Winsorized at

2% and 98%.

Growth: book-to-market ratio; book value of equity divided by market value.

Winsorized at 2% and 98%.

Log Equity Volatility: standard deviation of returns, timed from t-1 to t. Logged, not

winsorized.

Log Firm Volatility: Equity Volatility multiplied by )/( ttt DEE + . Logged, not

winsorized.

Soft Loans: a dummy of 1 if the firm receives a subsidy, and zero otherwise.

Tax: Total income tax dividend by the sum of earnings and income tax.

293

Industry Deviation: ADR of a firm minus the ADR average of the sector.

Liquidity: current assets dividend by current liabilities.

Future Stock Return Reversal: stock return from t+k multiplied by stock returns from

t+k, t+2k. Not winsorized.

294

Appendix D

Robustness of the Results

We conduct extensive robustness checks to investigate the extent to which our

results are sensitive to changes in parameter values and estimation procedure. First,

using means rather than median in Table 2.2 does not change the results. Second,

pooling all firm-years in one regression in Table 2.3 gives virtually identical results. For

example, a 1-year pooled regression has coefficients of 8.73%, 13.03%, and 71.32%

instead of 9.2%, 15.0%, and 68.3% in F-M regression. Similarly, the 5-year pooled

regression has coefficients of 21.56%, 7.79%, and 53.86% instead of 21.1%, 13.4%, and

48.3% in F-M regressions. Furthermore, we estimate equation (2.3) using the system

GMM and find similar results to the F-M. In particular, the GMM regression has a

coefficient of 67.43% on IDR and a coefficient of 12.44% on ADR. Using the fixed

effects lowers the ADR coefficient to -7.96% and the IDR to 60.33%. Moreover, we

estimate the model using random effects which results in coefficients very similar to the

F-M. Specifically, random effects regression has a coefficient of 10.32% on ADR

whereas the coefficient on IDR is 70.02%. In all cases, coefficients on IDR remains to

exert more influence on firms debt ratios. This suggests that our results are robust to

different estimation methods.

To check for multicollinearity, we estimate equation (2.3) and compute the

variance inflation factors for the independent variables for years one through five.121

We find that in all cases, the VIFs are less than the standard cutoff value of ten,

121 Professor Tom Smith suggested checking for multicollinearity in Table 2.3 in the 18th PhD Conference of Economics and Business at the University of Western Australia.

295

indicating that multicollinearity does not appear to be a significant factor. In essence,

the average VIFs for the one year is 6.44, 6.19 for the two years, 5.72 for the three years,

5.08 for the four years, and 2.07 for the five years. It is worth noting that the average

VIFs declines as the horizon increases.

Third, as we show in Table 2.4, using different definitions of debt such as short-

term and long-term does not alter our conclusions. Fourth, the results in Table 2.7 are

robust to the use of bank debt (Table 2.8). Fifth, we examine whether Leary and Roberts

argument that the persistent effects of shocks on leverage documented in previous

studies are due to adjustment costs. We find evidence that adjustment costs are unlikely

to be the main reason behind our results (Table 2.5). Finally, we employ Flannery and

Rangan partial adjustment model and we estimate it using F-M, fixed effects, and the

system GMM. We find that our results are robust to these methods (Table 2.9). Overall,

the findings of this chapter appear to be quite robust to changes in firm specific

parameters and changes in estimation procedure.

296

Appendix E Table E1. Correlation Matrix and Variance Inflation Factors (VIF) for the Explanatory Variables. We present the correlation matrix and the VIFs for the explanatory variables. Panel A presents the correlation matrix and VIFs for the non-financial firms while Panel B describes them for financial firms. Panel A: Non-Financial Firms Variables PROFIT LOGS DR STOCKS DROI GOVOWN AGE TANG MB PROFIT 1 LOGS 0.1797 1 DR -0.0643 -0.0838 1 STOCKS -0.0246 0.3449 -0.0271 1 DROI 0.0620 -0.0466 0.1387 0.0140 1 GOVOWN -0.0224 0.2182 -0.0706 0.2539 -0.0540 1 AGE 0.0439 0.3214 -0.1291 -0.0358 -0.0218 0.1821 1 TANG -0.1673 0.0085 0.2003 0.0103 0.0535 0.0572 0.0029 1 MB 0.0093 -0.0349 -0.0899 -0.0418 0.0094 -0.0186 -0.0387 -0.0954 1 VIF 1.09 1.37 1.09 1.24 1.03 1.13 1.19 1.08 1.02 Panel B: Financial Firms PROFIT 1 LOGS 0.2107 1 DR 0.0182 0.3089 1 STOCKS 0.0989 0.3206 0.0306 1 DROI -0.1171 -0.1292 -0.051 -0.0841 1 GOVOWN 0.1163 0.1856 0.0805 0.123 -0.0416 1 AGE 0.0187 0.4891 0.2511 -0.0358 -0.0581 0.2209 1 TANG -0.1092 -0.0831 -0.0679 -0.0643 0.1622 -0.0576 -0.1547 1 MB 0.0931 0.047 -0.1135 -0.0556 -0.0525 0.0398 0.0447 -0.0528 1 VIF 1.09 1.73 1.15 1.21 1.05 1.08 1.5 1.07 1.04 Note: Variables are defined in Table 5.1.

297

Table E2. Random Effects Tobit Regressions for the Determinants of Dividend Policy of Non-Financial Firms. We estimate random effects tobit regressions for all non-financial firms listed at the MSM during 1989-2004. The dependent variable is the dividend yield. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.5523*** -6.3207 PROFIT 0.0451* 1.7128 LOGS 0.1101*** 7.1093 DR -0.0592*** -2.8584 STOCKS -0.0811 -1.6218 DROI -0.3568*** -4.4148 GOVOWN 0.0026*** 4.3295 AGE 0.0018* 1.6841 TANG -0.0054 -0.4027 MB 0.0004 0.2678 No of Observations 1,057 Log Likelihood -12.7022 Wald Test [χ2 (9)]a 111.1700 P-value 0.0000 *, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom.

298

Table E3. Random Effects Tobit Regression for the Determinants of Dividend Policy of Financial Firms. We estimate random effects tobit regressions for all financial firms listed at the MSM during 1989-2004. The dependent variable is the dividend yield. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.2581*** -3.9052 PROFIT 0.1674*** 2.8308 LOGS 0.0399*** 3.5202 DR -0.0007 -0.1124 STOCKS -0.0067 -0.4985 DROI -0.2120*** -2.6252 GOVOWN 0.0005 0.7937 AGE 0.0011 0.9637 TANG -0.0852 -1.4891 MB -0.0004 -0.1677 No of Observations 413 Log Likelihood 83.3073 Wald Test [χ2 (9)]a 42.9500 P-value 0.0000 *, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom.

299

Table E4. Random Effects Probit Regressions to Explain Which Non-Financial Firms Pay Dividends We estimate random effects probit regressions for all non-financial firms listed at the MSM during 1989-2004. The dependent variable is a binary variable that equals to one if the firm pays dividends and zero otherwise. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -6.7192*** -5.6862 PROFIT 0.3549* 1.9290 LOGS 1.0500*** 5.6932 DR -0.8512*** -3.7117 STOCKS -0.1131 -0.4795 DROI -4.4563*** -5.1213 GOVOWN 0.0146* 1.8100 AGE 0.0047* 1.7322 TANG -0.0891 -0.6654 MB 0.0042 0.2721 No of Observations 1,057 Log Likelihood -456.3822 Wald Test [χ2 (9)]a 81.1500 P-value 0.0000


300

Table E5. Random Effects Probit Regressions to Explain Which Financial Firms Pay Dividends We estimate random effects probit regressions for all financial firms listed at the MSM during 1989-2004. The dependent variable is a binary variable that equals to one if the firm pays dividends and zero otherwise. The explanatory variables are the profitability (PROFIT), firm size (LOGS), leverage (DR), agency costs (STOCKS), business risk (DROI), government ownership (GOVOWN), maturity of the firm (AGE), tangibility (TANG), and growth opportunities (MB). The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -3.1145*** -3.1482 PROFIT 1.7306** 2.3110 LOGS 0.5226*** 3.1692 DR 0.1237 1.1326 STOCKS -0.1064 -0.4932 DROI -2.3128** -2.4375 GOVOWN 0.0162 1.3668 AGE -0.0105 -0.5576 TANG -1.4631 -1.5621 MB 0.0053 0.1719 No of Observations 413 Log Likelihood -214.4981 Wald Test [χ2 (9)]a 35.8700 P-value 0.0000


301

Table E6. Random Effects Tobit Regression of Lintner Model Estimates for Non-Financial Firms We estimate random effects tobit regression for all non-financial firms listed at the MSM over the period 1989-2004. The dependent variable is the dividend per share. The explanatory variables are the lagged DPS and the current EPS. The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.5660*** -8.8758 DPS-1 0.5494*** 9.7673 EPS 0.1214*** 4.1149 No of Observations 969 Log Likelihood -541.0625 Wald Test [χ2 (2)]a 109.7100 P-value 0.0000

*, **, and *** represents significance at the 10, 5, 1 percent levels, respectively. a The number in parenthesis is the degrees of freedom. Table E7. Random Effects Tobit Regression of Lintner Model Estimates for Financial Firms We estimate random effects tobit regression for all financial firms listed at the MSM over the period 1989-2004. The dependent variable is the dividend per share. The explanatory variables are the lagged DPS and the current EPS. The table shows the variable, their coefficients, and their corresponding t-statistics. Variable Coefficient T-Statistic C -0.1962*** -5.9653 DPS-1 0.0398** 1.9625 EPS 0.5293*** 48.4472 Observations 377 Log Likelihood -125.8128 Wald Test [χ2 (2)]a 2351.4700 P-value 0.0000


302

References

Abeyratna, G., A. Lonie, D. Power, and C. Sinclair, 1996. The influence of company financial performance on the interpretation of dividend and earnings signals: A study of accounting and market based data. British Accounting Review 28, 229-247.

Acharya, V., K. John, and R. Sundaram, 2005. Cross-country variations in capital

structures: The role of bankruptcy codes. Working Paper, London Business School.

Adaoglu, C., 2000. Instability in the dividend policy of the Istanbul Stock Exchange

(ISE) corporations: Evidence from an emerging market. Emerging Market Review 1, 252-270.

Adedeji, A., 1998. Does the pecking order hypothesis explain the dividend payout

ratios of firms in the UK? Journal of Business Finance and Accounting 25, 1127-1155.

Admati, A., and P. Pfleiderer, 1988. A theory of intraday patterns: Volume and

price variability. Review of Financial Studies 1, 3-40. Agca, S., and A. Mazumder, 2004. Firm size, debt capacity, and the pecking order

of financing choices. Working Paper, Washington University. Aggarwal, R., 1981. International differences in capital structure norms: An

empirical study of large European countries. Management International Review 21, 75-88.

Aggarwal, R., 1991. Capital structure differences among large Asian corporations.

ASEAN Economic Bulletin 7, 39-53. Aggarwal, R., and G. Baliga, 1987. Capital structure among Latin American

companies. Managerial Finance 13, 3-11. Agrawal, A., and N. Jayaraman, 1994. The dividend policies of all-equity firms: A

direct test of the free cash flow theory. Managerial and Decisions Economics 15, 139-148.

Aharony, J., H. Falk, and I. Swary, 1988. Information content of dividend increases:

The case of regulated utilities. Journal of Business Finance and Accounting 15, 401-414.

Aharony, J., and I. Swary, 1980. Quarterly dividend and earnings announcements

and stockholders return: An empirical analysis. Journal of Finance 35, 1-12.

303

Aivazian, V., L. Booth, and S. Cleary, 2003a. Dividend policy and the organization

of capital markets. Journal of Multinational Financial Management 13, 101-121.

Aivazian, V., L. Booth, and S. Cleary, 2003b. Do emerging market firms follow

different dividend policies from the U.S. firms? Journal of Financial Research 26, 371-387.

Aivazian, V., L. Booth, and S. Cleary, 2006. Dividend smoothing and debt ratings.

Journal of Financial and Quantitative Analysis 41, 439-453.

Akhtar, S., 2005. The determinants of capital structure for Australian multinational and domestic corporations. Australian Journal of Management 30, 321-341.

Allen, F., A. Bernardo, and I. Welch, 2000. A theory of dividends based on tax

clienteles. Journal of Finance 55, 2499-2536. Allen, F., and R. Michaely, 1995. Dividend policy. In R.A. Jarrow, V. Maksimovic,

and W.T. Ziemba (Eds.), Handbooks in Operations Research and Management Sciences. Elsevier, New York, 793-837.

Alli, K., A. Khan, and G. Ramirez, 1993. Determinants of corporate dividend

policy: A factorial analysis. The Financial Review 28, 523-547. Al-Malkawi, H., 2005. Dividend policy of publicly quoted companies in emerging

markets- The case of Jordan. Unpublished Ph.D. Dissertation, University of Western Sydney, Australia.

Alti, A., 2006. How persistent is the impact of market timing on capital structure?

Journal of Finance 61, 1681-1710. Altman, E., 1984. A further investigation of the bankruptcy cost question. Journal

of Finance 39, 1067-1089. Amihud, Y., and M. Murgia, 1997. Dividends, taxes, and signaling: Evidence from

Germany. Journal of Finance 52, 397-408. Anderson, G., 1986. An application of the Tobit model to panel data: Modelling

dividend behaviour in Canada. Working Paper No. 85-22, McMaster University.

Anderson, H., S. Cahan, and L. Rose, 2001. Stock dividend announcement effects in

an imputation tax environment. Journal of Business Finance and Accounting 28, 653-653-669.

304

Anderson, T., and C. Hsiao, 1981. Estimation of dynamic models with error components. Journal of the American Statistical Association 76, 598-606.

Andrade, G., and S. Kaplan, 1998. How costly is financial (not economic) distress?

Evidence from highly leveraged transactions that became distressed. Journal of Finance 53, 1443-1493.

Ang, J., 1987. Do dividends matter? A review of corporate dividend theories and

evidence. Salomon Brothers Center for the Study of Financial Institutions and the Graduate Schools of Business Administration of New York University, New York.

Ang, J., J. Chua, and J. McConnell, 1982. The administrative costs of corporate

bankruptcy: A note. Journal of Finance 37, 219-226. Ang, J., and D. Peterson, 1985. Return, risk, and yield: Evidence from ex-ante data.

Journal of Finance 40, 537-548.

Annuar, M., and M. Shamsher, 1993. Earnings and dividend behaviour. Journal of Social Science and Humanities 1, 171-177.

Antoniou, A., Y. Guney, and K. Paudyal, 2002. Determinants of corporate capital

structure: Evidence from European Countries. Working Paper, University of Durham.

Arellano, M., and S. Bond, 1991. Some tests of specification for panel data: Monte-

Carloe evidence and an application to employment equations. Review of Economic Studies 38, 277-297.

Arellano, M., and O. Bover, 1995. Another look at instrumental-variable estimation

error-components models. Journal of Econometrics 68, 29-52. Ariff, M., and L. Johnson, 1994. Securities markets and stock pricing: Evidence

from a developing market in Asia, Singapore, Sydney, and London. Journal of Social Science and Humanities 1, 171-177.

Asquith, P., and D. Mullins, 1983. The impact of initiating dividend payments on

shareholders’ wealth. Journal of Business 56, 77-96. Asquith, P., and D. Mullins, 1986. Signaling with dividends, stock repurchases and

equity issues. Financial Management 15, 27-44. Athanassakos, G., and D. Fowler, 1993. New evidence on the behavior of Canadian

stock prices in the days surrounding the ex-dividend day. Quarterly Journal of Business and Economics 47, 127-159.

305

Auerbach, A., 1985. Real determinants of corporate leverage. In Benjamin J. Friedman (ed.), Corporate Capital Structures in the United States. University of Chicago Press, Chicago, 325-348.

Autore, D., and T. Kovacs, 2005. The pecking order theory and time-varying

adverse selection costs. Working Paper, Virginia Tech. Azzam, H., 2002. The Arab World: Facing the Challenge of the New Millennium.

I.B. Tauris, London. Bajaj, M., and A. Vijh, 1990. Dividend clienteles and the information content of

dividend changes. Journal of Financial Economics 26, 193-219. Bajaj, M., and A. Vijh, 1995. Trading behavior and the unbiasedness of the market

reaction to dividend announcements. Journal of Finance 50, 255-279.

Baker, H., and G. Farrelly, 1988. Dividend achievers: A behavioral look. Akron Business and Economic Review 19, 79-92.

Baker, H., G. Farrelly, and R. Edelman, 1985. A survey of management views on

dividend policy. Financial Management 14, 78-84. Baker, H., T. Mukherjee, O. Paskelian, 2005. How Norwegian managers view

dividend policy. Working Paper, University of New Orleans. Baker, H., and G. Powell, 1999. How corporate managers view dividend policy.

Quarterly Journal of Business and Economics 38, 17-35. Baker, H., G. Powell, and E. Viet, 2002. Revisiting the dividend puzzle - Do all of

the pieces now fit? Review of Financial Economics 11, 241-261. Baker, M., R. Greenwood, and J. Wurgler, 2003. The maturity of debt issues and

predictable variation in bond returns. Journal of Financial Economics 70, 261-291.

Baker, M., and J. Wurgler, 2002. Market timing and capital structure. Journal of

Finance 62, 1-32.

Balachandran, B., 2003. UK interim and final dividend reductions: A note on price reaction. The European Journal of Finance 9, 379-390.

Balachandran, B., R. Faff, and S. Tanner, 2004. Further evidence on the

announcement effect of bonus shares in an imputation tax setting. Global Finance Journal 15, 147-170.

306

Bali, R., 2003. An empirical analysis of stock returns around dividend changes. Applied Economics 35, 51-61.

Bali, R., and G.L. Hite, 1998. Ex-dividend day stock price behavior: Discreteness or

tax-induced clientele? Journal of Financial Economics 47, 127-159. Ball, R., P. Brown, and F. Finn, 1977. Share capitalization changes, information,

and the Australian equity market. Australian Journal of Management 2, 105-125.

Ball, R., P. Brown, F. Finn, and R. Officer, 1979. Dividend and the value of the

firm: Evidence from the Australian equity market. Australian Journal of Management 4, 13-26.

Baltagi, B., 1995. Econometric Analysis of Panel Data. John Wiley and Sons, New

York. Baltagi, B., 2001. Econometric Analysis of Panel Data, 2nd ed. John Wiley and

Sons, New York. Baltagi, B., 2005. Econometric Analysis of Panel Data, 3rd ed. John Wiley and

Sons, New York. Bancel, F., N. Bhattacharyya, and U. Mittoo, 2005. Cross-country determinants of

payout policy: A survey of European firms. Working Paper, University of Manitoba.

Bancel, F., and U. Mittoo, 2004. Cross-country determinants of capital structure

choice: A survey of European firms. Financial Management 33, 103-132.

Barclay, M., 1987. Dividends, taxes, and common stock prices before the income tax. Journal of Financial Economics 13, 31-44.

Barclay, M., C. Holderness, and D. Sheehan, 2006. Dividends and corporate

shareholders. Working Paper, University of Rochester. Barclay, M., and C. Smith, 1999. The capital structure puzzle: Another look at the

evidence. Journal of Applied Corporate Finance 12, 8-20. Barclay, M., C. Smith, and R. Watts, 1995. The determinants of corporate leverage

and dividend policies. Journal of Applied Corporate Finance 7, 4-19. Barker, C., 1959. Price changes of stock-dividends shares at ex-dividend dates.

Journal of Finance 14, 373-378.

307

Bartov, E., 1991. Open-market stock repurchases as signals for earnings and risk changes. Journal of Accounting and Economics 14, 275-294.

Bartholdy, J., and K. Brown, 1999. Ex-dividend day pricing in New Zealand.

Accounting and Finance 39, 111-129. Barton, S., N. Hill, and S. Sundaram, 1989. An empirical test of stakeholder theory

predictions of capital structure. Financial Management 18, 36-44. Bar-Yosef, S., and L. Huffman, 1986. The information content of dividends: A

signalling approach. Journal of Financial and Quantitative Analysis 21, 47-58.

Bar-Yosef, S., and O. Sarig, 1992. Dividend surprises inferred from option and

stock prices. Journal of Finance 47, 1623-1640. Baskin, J., 1989. Dividend policy and the volatility of common stock. Journal of

Portfolio Management 15, 19-25. Baxter, N., 1967. Leverage, risk of ruin, and the cost of capital. Journal of Finance

22, 395-403.

Beaver, W., P. Kettler, and M. Scholes, 1970. The association between market determined and accounting determined risk measures. Accounting Review 45, 654-682.

Bebczuk, R., 2004. Explaining dividend policies in Argentina. Working Paper No.

50, Universidad Nacional de La Plata. Becher, D., T. Campbell II, and M. Frye, 2005. Incentive compensation for bank

directors: The impact of deregulation. Journal of Business 78, 1753-1778 Beck, T., and R. Levine, 2004. Stock markets, banks, and growth: Panel evidence.

Journal of Banking and Finance 28, 423-442. Bellamy, D., 1994. Evidence of imputation clienteles in the Australian equity

market. Asia Pacific Journal of Management 11, 275-287. Bell, L., and T. Jenkinson, 2002. New evidence on the impact of dividend taxation

and on the identity of the marginal investor. Journal of Finance 57, 1321-1346.

Belsley, D., E. Kuh, and R. Welsch, 1980. Regression Diagnostics, Identifying

Influential Data and Sources of Collinearity. John Wiley and Sons, New York.

308

Benartzi, S., R. Michaely, and R. Thaler, 1997. Do changes in dividends signal the future or the past? Journal of Finance 52, 1007-1034.

Benesh, G., A. Keown, and J.M. Pinkerton, 1984. Examination of market reaction to

substantial shifts in dividend policy. Journal of Financial Research 7, 131-142.

Benito, A., and G. Young, 2003. Hard times or great expectations? Dividend

omissions and dividend cuts by UK firms. Oxford Bulletin of Economics and Statistics 65, 531-555.

Ben Naceur, S., and M. Goaied, 2002. The relationship between dividend policy,

financial structure, profitability and firm value. Applied Financial Economics 12, 843-849.

Bennett, M., and R. Donnelly, 1993. The determinants of capital structure: Some

UK evidence. British Accounting Review 25, 43-59. Berger, G., E. Ofek, and D. Yermack, 1997. Managerial entrenchment and capital

structure decisions. Journal of Finance 56, 87-130. Berle, A., and G. Means, 1932. The Modern Corporation and Private Property.

Macmillan, New York. Bernstein, P., 1996. Dividends: The puzzle. Journal of Applied Corporate Finance

9, 16-22. Bessler, W., and T. Nohel, 1996. The stock-market reaction to dividend cuts and

omissions by commercial banks. Journal of Banking and Finance 20, 1485-1508.

Bevan, A., and J. Danbolt, 2004. Testing for inconsistencies in the estimation of UK

capital structure determinants. Applied Financial Economics 14, 55-66. Bhaduri, S., 2002. Determinants of capital structure choice: A study of the Indian

corporate sector. Applied Financial Economics 12, 655-665. Bhattacharya, S., 1979. Imperfect information, dividend policy and ‘the bird in the

hand’ fallacy. Bell Journal of Economics 10, 259-270. Binder, J., 1998. The event study methodology since 1969. Review of Quantitative

Finance and Accounting 11, 111-137. Black, F., 1976. The dividend puzzle. Journal of Portfolio Management 2, 5-8.

309

Black, H., D. Ketcham, and R. Schweitzer, 1989. The reaction of bank holding company stock prices to dividend cuts and omissions. Working Paper FC89-5, University of Delaware.

Black, F., and M. Scholes, 1974. The effects of dividend yield and dividend policy

on common stock prices and returns. Journal of Financial Economics 1, 1-22.

Blume, M., 1980. Stock returns and dividend yields: Some more evidence. Review

of Economics and Statistics 62, 567-577. Blume, M., J. Crockett, and I. Friend, 1974. Stock ownership in the United States:

Characteristics and trends. Survey of Current Business 54, 16-40. Blundell, R., and S. Bond, 1998. Initial conditions and moment restrictions in

dynamic panel data models. Journal of Econometrics 87, 115-143. Blundell, R., and S. Bond, 2000. GMM estimation with persistent panel data: An

application to production functions. Econometric Review 19, 321-340. Blundell, R., S. Bond, and F. Windmeijer, 2000. Estimation in dynamic panel

models: Improving on the performance of the standard GMM estimator. In B. Baltagi (Ed.), Advances in Econometrics 15: Non-Stationary Panels, Panel Cointegration, and Dynamic Panels. JAI Elsevier Science, Amsterdam.

Boehmer, E., J. Musumeci, and A. Poulsen, 1991. Event-study methodology under

conditions of event-induced variance. Journal of Financial Economics 30, 253-272.

Bolbol, A., and M. Omran, 2004. Arab stock markets and capital investment.

Working Paper, Arab Monetary Fund. Bond, S., 2002. Dynamic panel data models: A guide to micro data models practice.

Working Paper, Institute for Fiscal Studies. Booth, L., V. Aivazian, A. Demirguc-Kunt, and V. Maksimovic, 2001. Capital

structures in developing countries. Journal of Finance 56, 87-130. Booth, L., and D. Johnston, 1984. The ex-dividend day behavior of Canadian stock

prices: Tax changes and clientele effects. Journal of Finance 39, 457-476. Borokhovich, K., K. Brunarski, Y. Harman, and J. Kehr, 2005. Dividends, corporate

monitors and agency costs. The Financial Review 40, 37-65. Bowen, R., L. Daley, and C. Huber, 1982. Evidence on the existence and

determinants of inter-industry in leverage. Financial Management 11, 10-20.

310

Boyd, J., and R. Jagannathan, 1994. Ex-dividend price behavior of common stocks.

Review of Financial Studies 7, 711-741. Brav, A., J. Graham, C. Harvey, and R. Michaely, 2005. Payout policy in the 21st

century. Journal of Financial Economics 77, 483-527. Brealey, R., and S. Myers, 2003. Principles of Corporate Finance. McGraw-Hill

Irwin. Brennan, M., and A. Kraus, 1987. Efficient financing under asymmetric

information. Journal of Finance 42, 1225-1243. Bradley, M., D. Capozza, and P. Seguin, 1998. Dividend policy and cash-flow

uncertainty. Real Estate Economics 26-555-580. Bradley, M., G. Jarrell, and E. Kim, 1984. On the existence of an optimal capital

structure: Theory and evidence. Journal of Finance 39, 857-880. Brennan, M., 1970. Taxes, market valuation and corporate financial policy.

National Tax Journal 23, 417-427. Brickley, J., 1983. Shareholder wealth, information signaling and the specially

designated dividend. Journal of Financial Economics 12, 187-209. Brittain, J., 1964. The tax structure and corporate dividend policy. American

Economic Review 54, 272-287. Brittain, J., 1966. Corporate Dividend Policy. Brookings Institution, Washington

DC. Brooke, J., and B. Oliver, 2005. The source of abnormal returns from strategic

alliance announcements. Pacific-Basin Finance Journal 13, 145-161. Brounen, D., A. Jong, and K. Koedijk, 2004. Corporate finance in Europe:

Confronting theory with practice. Financial Management 33, 71-101. Brown, P., F. Finn, and P. Hancock, 1977. Dividend changes, earnings reports, and

share prices: Some Australian findings. Australian Journal of Management 2, 127-147.

Brown, P., and T. Walter, 1986. Ex-dividend day behaviour of Australian share

prices. Australian Journal of Management 11, 139-152. Brown, S., and J. Warner, 1980. Measuring security price performance. Journal of

Financial Economics 8, 205-258.

311

Brown, S., and J. Warner, 1985. Using daily stock returns: The case of event

studies. Journal of Financial Economics 14, 3-31. Brown, T., and Y. Zhang, 2006. Ex-dividend day price behaviour: The case of 2003

dividend tax cut. Working Paper, University of Nebraska. Cai, J., and Z. Zhang, 2005. Capital structure dynamics and stock returns. Working

Paper, Singapore Management University. Callaghan, S., and C. Barry, 2003. Tax-induced trading of equity securities:

Evidence from the ADR market. Journal of Finance 58, 1583-1911. Campbell, J., and W. Beranek, 1955. Stock price behavior on ex-dividend dates.

Journal of Finance 10, 425-429. Campbell, J., A. Lo, and A. MacKinlay, 1997. The Econometrics of Financial

Markets. Princeton University Press, Princeton. Cantillo, M., and J. Wright, 2000. How do firms choose their lenders? An empirical

investigation. Review of Financial Studies 13, 155-189. Capital Market Authority, Annual Reports 1989 – 2005, Muscat, Oman. Carvalhal-da-Silva, A., and R. Leal, 2004. Corporate governance, market valuation

and dividend policy in Brazil. Frontiers in Financial Economics 1, 1-16. Casey, K., and R. Dickens, 2000. The effect of tax and regulatory changes in

commercial bank dividend policy. Quarterly Review of Economics and Finance 40, 279-293.

Castanias, R., 1983. Bankruptcy risk and optimal capital structure. Journal of

Finance 38, 1617-1635.

Central Bank of Oman, 1998. Muscat Securities Market what caused the downside. Al-Markazi 23, 2-20.

Central Bank of Oman, Annual Reports 2001 – 2005, Muscat, Oman. Central Bank of Oman, 2002. 25 Years of Central Bank of Oman. Muscat, Oman

Press. Chang, X., G. Hilary, C. Shih, and L. Tam, 2006. Keiretsu membership, market

timing, and capital structure. Working Paper, University of Melbourne.

312

Chang, R., and S. Rhee, 1990. The impact of personal taxes on corporate dividend policy and capital structure decisions. Financial Management 19, 21-31.

Chaplinsky, S., and G. Niehaus, 1993. Do inside ownership and leverage share

common determinants? Quarterly Journal of Business and Economics 32, 51-65.

Charest, G., 1978. dividend information, stock returns, and market efficiency –II.

Journal of Financial Economics 6, 297-330. Chateau, J., 1979. Dividend policy revisited: Within- and without-of-sample tests.

Journal of Business Finance and Accounting 6, 355-372. Chay, J., and J. Suh, 2005. Cross-sectional determinants of dividend payments:

International evidence. Working Paper, Sungkyungkwan University. Chen, J., 2004. Determinants of capital structure of Chinese-listed companies.

Journal of Business Research 57, 1341-1351. Chen, J., and N. Dhiensiri, 2005. Determinants of dividend policy: The evidence

from New Zealand. Working Paper, Massey University. Chen, N.F., B. Grundy, and R. Stambaugh, 1990. Changing risk, changing risk

premiums, and dividend yield effects. Journal of Business 63, S51-S70. Chen, L., and X. Zhao, 2005a. Firm financing decisions. Working Paper, Michigan

State University. Chen, L., and X. Zhao, 2005b. Profitability, mean reversion of leverage ratios, and

capital structure choices. Working Paper, Michigan State University. Chetty, R., J. Rosenberg, and E. Saez, 2005. The effects of taxes on market

responses to dividend announcements and payments: What can we learn from the 2003 dividend tax cut? Working Paper, University of California Berkeley.

Chiang, R., I. Davidson, and J. Ckunev, 1997. Some further theoretical and

empirical implications regarding the relationship between earnings, dividends and stock prices. Journal of Banking and Finance 21, 17-45.

Chiarella, C., T. Pham, A. Sim, and M. Tan, 1992. Determinants of corporate capital

structure: Australian evidence. In S. Rhee and R. Chang (Eds.), Pacific-Basin Capital Markets Research, vol 3. Elsevier Science Publishers, Amsterdam.

313

Childs, P., D. Mauer, and S. Ott, 2005. Interactions of corporate financing and investment decisions: The effects of agency conflicts. Journal of Financial Economics 76, 667-690.

Chirinko, R., and A. Singha, 2000. Testing static tradeoff against pecking order

models of capital structure: A critical comment. Journal of Financial Economics 58, 417-425.

Chowdhury, G., and D. Miles, 1989. Modeling companies’ debt and dividend

decisions with company accounts data. Applied Economics 21, 1483-1508.

Clarke, A., 1992. Ex-dividend day behaviour of Australia share prices pre and post- imputation. Managerial Finance 18, 34-48.

Cleary, S., 1999. The relationship between firm investment and financial status.

Journal of Finance 54, 673-692. Cloyd, C., O. Li, and C. Weaver, 2002. Tick and tax: The joint effects of discrete

(vs. decimal) pricing and taxation on ex-dividend day returns and trading volume. Working Paper, University of Illinois at Urbana-Champaign.

Cloyd, C., O. Li, and C. Weaver, 2004. Tick and tax: The joint effects of price

discreteness and taxation on ex-dividend day returns. Working Paper, University of Illinois at Urbana-Champaign.

Collins, M., A. Saxena, and J. Wansely, 1996. The role of insiders and dividend

policy: A comparison of regulated and unregulated firms. Journal of Financial and Strategic Decisions 9, 1-9.

Conroy, R., K. Eades, and R. Harris, 2000. A test of the relative pricing effects of

dividends and earnings: Evidence from simultaneous announcements in Japan. Journal of Finance 55, 1199-1227.

Constantinides, G., and B. Grundy, 1989. Optimal investment with stock repurchase

and financing as signals. Review of Financial Studies 2, 445–465.

Copeland, T., 1979. Liquidity changes following stock splits. Journal of Finance 34, 115-141.

Crutchley, C., and R. Hansen, 1989. A test of the agency theory of managerial

ownership, corporate leverage, and corporate dividends. Financial Management 18, 36-46.

Crutchley, C., M. Jensen, J. Jahera Jr., and J. Raymond, 1999. Agency problems and

the simultaneity of financial decision making: The role of institutional ownership. International Review of Financial Analysis 8, 177-179.

314

Damodaran, A., 2002. Corporate Finance-Theory and Practice, 2nd ed. John Wiley

and Sons, New York. Daunfeldt, S-O., 2002. Tax policy changes and ex-dividend behavior: The case of

Sweden. Working Paper, Umeå University.

DeAngelo, H., and L. DeAngelo, 1990. Dividend policy and financial distress: An empirical investigation of troubled NYSE firms. Journal of Finance 45, 1415-1431.

DeAngelo, H., and L. DeAngelo, 2006. The irrelevance of the MM dividend

irrelevance theorem. Journal of Financial Economics 79, 293-315. DeAngelo, H., L. DeAngelo, and D. Skinner, 1996. Reversal of fortune: Dividend

signaling and the disappearance of sustained earnings growth. Journal of Financial Economics 40, 341-371.

DeAngelo, H., L. DeAngelo, and R. Stulz, 2004. Dividend policy, agency costs, and

earned equity. Working Paper, University of Southern California. DeAngelo, H., and R. Masulis, 1980. Optimal capital structure under corporate and

personal taxation. Journal of Financial Economics 8, 3-29. Deesomask, R., K. Paudyal, and G. Pescetto, 2004. The determinants of capital

structure: Evidence from the Asia Pacific region. Journal of Multinational Financial Management 14, 387-405.

De Jong, A., R. Kabir, and T. Nguyen, 2005. Capital structure around the world:

What firm- and country-specific determinants really matter? Working Paper, RSM Erasmus University.

De Hass, R., and M. Peeters, 2006. The dynamic adjustment towards target capital

structures of firms in transition economies. Economics of Transition 14, 133-169.

Demirguc-Kunt, A., and R. Levine, 1999. Bank-based and market-based financial

systems: Cross-country comparisons. Working Paper No. 2143, World Bank. Demirguc-Kunt, A., and V. Maksimovic, 1999. Institutions, financial markets, and

firm debt maturity. Journal of Financial Economics 54, 295-336. Dempsey, S., and G. Laber, 1992. Effects of agency and transaction costs on

dividend payout ratios: Further evidence of the agency-transaction cost hypothesis. Journal of Financial Research 15, 317-321.

315

Denis, D., D. Denis, and A. Sarin, 1994. The information content of dividend changes: Cash flow signaling, overinvestment, and dividend clienteles. Journal of Financial and Quantitative Analysis 29, 567-587.

Denis, D., and V. Mihov, 2003. The choice among bank debt, non-bank private

debt, and public debt: Evidence from new corporate borrowings. Journal of Financial Economics 70, 3-28.

Deshmukh, S., 2003. Dividend initiations and asymmetric information: A hazard

model. The Financial Review 38, 351-368. Dewenter, K., and V. Warther, 1998. Dividends, asymmetric information, and

agency conflicts: Evidence from a comparison of the dividend policies of Japanese and U.S. firms. Journal of Finance 53, 879-904.

Dhaliwal, D., and O. Li, 2006. Investor tax heterogeneity and ex-dividend day

trading Volume. Journal of Finance 61, 463-490. Diamond, J., 1967. Earnings distribution and the valuation of shares: Some recent

evidence. Journal of Financial and Quantitative Analysis 2, 15-30. Dickens, R., K. Casey, and J. Newman, 2002. Bank dividend policy: Explanatory

factors. Quarterly Journal of Business and Economics 41, 3-12. Dielman, T., and H. Oppenheimer, 1984. An examination of investor behavior

during period of large dividend changes. Journal of Financial and Quantitative Analysis 19, 197-216.

Directives for Listing Securities on Muscat Securities Market, 2002. Capital Market

Authority, Muscat, Oman. Divecha, A., and D. Morse, 1983. Market responses to dividend increases and

changes in payout ratios. Journal of Financial and Quantitative Analysis 18, 163-173.

Donaldson, G., 1961. Corporate debt capacity: A study of corporate debt policy and

the determination of corporate debt capacity. Harvard Business School, Division of Research.

Drobetz, W., and R. Fix, 2005. What are the determinants of the capital structure?

Some evidence from Switzerland. Swiss Journal of Economics and Statistics 141, 71-131.

Dubofsky, D., 1992. A market microstructure explanation of ex-day abnormal

returns. Financial Management 21, 32-43.

316

Durand, D., and A. May, 1960. The ex-dividend behavior of American telephone and telegraph stock. Journal of Finance 15, 19-31.

Dutta, S., V. Jog, and S. Saadi, 2005. Re-examination of the ex-dividend day

behavior of Canadian stock prices. Working Paper, Carleton University. Dyckman, T., D. Philbrick, J. Stephan, and W. Ricks, 1984. A comparison of event

study methodologies using daily stock returns: A simulation approach. Journal of Accounting Research 22, 1-33.

Eades, K., 1982. Empirical evidence on dividends as a signal of firm value. Journal

of Financial and Quantitative Analysis 17, 471-500. Eades, K., P. Hess, and E. Kim, 1984. On interpreting security returns during the ex-

dividend period. Journal of Financial Economics 13, 3-35. Eades, K., P. Hess, and E. Kim, 1985. Market rationality and dividend

announcements. Journal of Financial Economics 14, 581-604. Eades, K., P. Hess, and E. Kim, 1994. Time series variation in dividend pricing.

Journal of Finance 49, 1617-1638. Easterbrook, F., 1984. Two agency-cost explanations of dividends. American

Economic Review 74, 650-659. Easton, S., 1991. Earnings and dividends: Is there an interaction effect? Journal of

Business Finance and Accounting 18, 255-266. Elton, E., and M. Gruber, 1970. Marginal stockholder tax rates and the clientele

effect. Review of economics and Statistics 52, 68-74. Elton, E., M. Gruber, and C. Blake, 2005. Marginal stockholder tax effects and ex-

dividend-day price behavior: Evidence from taxable versus nontaxable closed-end funds. Review of Economics and Statistics 87, 579-586.

Elton, E., M. Gruber, and J. Rentzler 1984. The ex-dividend day behavior of stock

prices: A re-examination of the clientele effect: A comment. Journal of Finance 39, 551-556.

Errunza, V., 1979. Efficiency and the programs to develop capital markets: The

Brazilian experience. Journal of Banking and Finance 3, 355- 382. Faccio, M., L. Lang, and L. Young, 2001. Dividend and expropriation. American

Economic Review 91, 54-78.

317

Fama, E., 1974. The empirical relationship between the dividend and the investment decisions of firms. American Economic Review 64, 304-318.

Fama, E., 1976. Foundations of Finance. Basic Books, New York. Fama, E., and H. Babiak, 1968. Dividend policy: An empirical analysis. Journal of

American Statistical Association 63, 1132-1161. Fama, E., L. Fisher, M. Jensen, and R. Roll, 1969. The adjustment of stock prices to

new information. International Economic Review 10, 1-21. Fama, E., and K. French, 1992. The cross-section of expected stock returns. Journal

of Finance 47, 427-465. Fama, E., and K. French, 1998. Taxes, financing decisions, and firm value. Journal

of Finance 53, 819-843. Fama, E., and K. French, 2001. Disappearing dividends: Changing firm

characteristics or lower propensity to pay? Journal of Financial Economics 60, 3-43.

Fama, E., and K. French, 2002. Testing tradeoff and pecking order predictions about

dividends and debt. Review of Financial Studies 15, 1-33. Fama, E., and K. French, 2005. Financing decisions: Who issues stock? Journal of

Financial Economics 76, 549-582. Fama, E., and M. Jensen, 1983. Agency problems and residual claims. Journal of

Law and Economics 26, 327-349. Fama, E., and J.D. MacBeth, 1973. Risk, return and equilibrium: Empirical tests.

Journal of Political Economy 81, 607-636. Fama, E., and M. Miller, 1972. The Theory of Finance. Holt, Rinehart, and

Winston, New York. Fan, J., S. Titman, and G. Twite, 2004. An international comparison of capital

structures and debt maturity choices. Working Paper, Australian Graduate School of Management.

Farhat, J., C. Cotie, and B. Abugri, 2006. Partial adjustment toward target capital

structure- International comparison. Working Paper, Southern Connecticut State University.

Farrelly, G., H. Baker, and R. Edelman, 1986. Corporate dividends: Views of the

policy makers. Akron Business and Economic Review 17, 62-74.

318

Faulkender, M., and M. Petersen, 2006. Does the source of capital affect capital

structure? Review of Financial Studies 19, 45-79.. Fazzari, S., R. Hubbard, and Petersen, 1988. Financing constraints and corporate

investment. Brookings Paper for Economic Activity 1, 141-95. Fedenia, M., and T. Grammatikos, 1993. Risk premia and the ex-dividend stock

price behavior: Empirical evidence. Journal of Banking and Finance 17, 575-589.

Ferri, M., and W. Jones, 1979. Determinants of financial structure: A new

methodological approach. Journal of Finance 34, 631-644. Firth, M., 1996. Dividend changes, abnormal returns and intra-industry firm

valuations. Journal of Financial and Quantitative Analysis 31, 189-211. Fisher, G., 1961. Some factors influencing share prices. Economic Journal 71, 121-

141. Fischer, E., R. Heinkel, and J. Zechner, 1989. Dynamic capital structure choice:

Theory and tests. Journal of Finance 44, 19-40. Flannery, M., and K. Rangan, 2006. Partial adjustment toward target capital

structures. Journal of Financial Economics 79, 469-506. Fleming, G., R. Heaney, and R. McCosker, 2005. Agency costs and ownership

structure in Australia. Pacific-Basin Finance Journal 13, 29-52. Florentsen, B., and K. Rydqvist, 2001. Ex-day behavior when investors and

professional traders assume reverse roles: The case of Danish lottery bonds. Journal of Financial Intermediation 11, 152-157.

Foster, T., and D. Vickrey, 1978. The information content of stock dividend

announcements. The Accounting Review 53, 360-370. Foster, F.D., and S. Viswanathan, 1990. A theory of interday variations in volumes,

variances, and trading costs in securities markets. Review of Financial Studies 3, 593-624.

Foster, F.D., and S. Viswanathan, 1993. Variations in trading volume, return

volatility, and trading costs: Evidence on recent price formation models. Journal of Finance 48, 187- 211.

Frank, M., and V. Goyal, 2003. Testing the pecking order theory of capital structure.

Journal of Financial Economics 67, 217-248.

319

Frank, M., and V. Goyal, 2004. Capital structure decisions: Which factors are

reliably important? Working Paper, University of British Colombia. Frank, M., and V. Goyal, 2005. Tradeoff and pecking order theories of debt.

Working Paper, University of British Colombia. Frank, M., and R. Jagannathan, 1998. Why do stock prices drop by less than the

value of the dividend? Evidence from a country without taxes. Journal of Financial Economics 47, 161-188

Friend, I., and I. Hasbrouck, 1988. Determinants of capital structure. In J. Chen

(ed.), Research in Finance. JAI Press, London. Friend, I., and M. Puckett, 1964. Dividend and stock prices. American Economic

Review 54, 656-682. Galai, D., and R. Masulis, 1976. The option pricing model and the risk factor of

stock. Journal of Financial Economics 3, 53-81. Gardner, J., and C. Trzcinka, 1992. All-equity firms and the balancing theory of

capital structure. Journal of Financial Research 15, 77-90. Garver, J., and K. Garver, 1993. Additional evidence on the association between the

investment opportunity set and corporate financing, dividend, and compensation policies. Journal of Accounting and Economics 16, 125-160.

Garvey, G., and G. Hanka, 1999. Capital structure and corporate control: The effect

of antitakeover statutes on firm leverage. Journal of Finance 54, 519-546. Ghosh, C., and J. Woolridge, 1988. An analysis of shareholder reaction to dividend

cuts and omissions. Journal of Financial Research 11, 281-294. Ghosh, C., and J. Woolridge, 1991. Dividends omissions and stock market

rationality. Journal of Business Finance and Accounting 18, 315-330. Givoly, D., C. Hahn, A. Offer, and O. Sarig, 1992. Taxes and capital structure:

Evidence from firm’s response to the tax reform act of 1986. Review of Financial Studies 5, 331-355.

Glen, J., Y. Karmokolias, R. Miller, and S. Shah, 1995. Dividend policy and

behavior in emerging markets. Discussion Paper No. 26, International Finance Corporation.

320

Goergen, M., L. Renneboog, and L. Correia da Silva, 2004. Dividend policy of German firms: A dynamic panel data analysis of partial adjustment models. Working Paper, Tilburg University.

Gonedes, N., 1978. Corporate signaling, external accounting and capital market

equilibrium: Evidence on dividends income and extraordinary items. Journal of Accounting Research 16, 26-79.

Gordon, M., 1959. Dividends, earnings, and stock prices. Review of Economics

and Statistics 41, 99-105. Gordon, M., 1963. Optimal investment and financing policy. Journal of Finance 18,

264-272. Gordon, M., and E. Shapiro, 1956. Capital equipment analysis: The required rate of

profit. Management Science 3, 102-110. Graham, J., 1996. Debt and the marginal tax rate. Journal of Financial Economics

41, 41-73. Graham, J., 2000. How big are the tax benefits of debt? Journal of Finance 55,

1901-1941.

Graham, J., 2003. Taxes and corporate finance: A review. Review of Financial

Studies 16, 1075-1129.

Graham, B., and D. Dodd, 1951. Security Analysis, 3rd ed. McGraw-Hill Inc., New York.

Graham, J., and C. Harvey, 2001. The theory and practice of corporate finance:

Evidence from the field. Journal of Financial Economics 60, 187-243. Graham, J., and A. Kumar, 2006. Do dividend clienteles exist? Evidence on

dividend preferences of retail investors. Journal of Finance 61, 1305-1336. Graham, J., M. Lemmon, and J. Schallheim, 1998. Debt, leases, taxes, and the

endogeneity of corporate tax status. Journal of Finance 53, 131-161. Graham, J., R. Michaely, and M. Roberts, 2003. Do price discreteness and

transactions costs affect stock returns? Comparing ex-dividend pricing before and after decimalization. Journal of Finance 58, 2611-2636.

Grais, W., and Z. Kantur, 2003. The changing financial landscape: Opportunities

and challenges for the Middle East and North Africa. Working Paper No. 3050, World Bank Policy Research.

321

Grammatikos, T., 1989. Dividend stripping, risk exposure, and the effect of the

1984 tax reform act on the ex-dividend day behavior. Journal of Business 62, 157-173.

Green, J., 1980. Taxation and the ex-dividend day behavior of common stock prices.

Working Paper, Harvard University. Green, R., and K. Rydqvist, 1999. Ex-day behavior with dividend preference and

limitations to short-term arbitrage: The case of Swedish lottery bonds. Journal of Financial Economics 53, 145-187.

Grinblatt, M., R. Masulis, and S. Titman, 1984. The valuation effect of stock splits

and stock dividends. Journal of Financial Economics 13, 461-490. Griner, E., and L. Gordon, 1995. Internal cash flow, insider ownership, and capital

expenditures: A test of the pecking order and managerial hypotheses. Journal of Business Finance and Accounting 22, 179

Grinstein, Y., and R. Michaely, 2005. Institutional holdings and payout policy.

Journal of Finance 60, 1389-1426. Grossman, S., and O. Hart, 1982. Corporate financial structure and managerial

incentives. In J. McCall (Ed.), The Economics of Information and Uncertainty. University of Chicago Press, Chicago.

Grullon, G., and R. Michaely, 2002. Dividends, share repurchases, and the

substitution hypothesis. Journal of Finance 57, 1649-1684. Grullon, G., and R. Michaely, 2004. The information content of share repurchase

programs. Journal of Finance 59, 651-680. Grullon, G., R. Michaely, and B. Swaminathan, 2002. Are dividend changes a sign

of firm maturity? Journal of Business 75, 387-424. Grundy, B., 1985. Trading volume and stock returns around ex-dividend dates.

Working Paper, University of Chicago. Grundy, B., 2001. Merton H. Miller: His contribution to financial economics.

Journal of Finance 56, 1183-1206. Guay, W., and J. Harford, 2000. The cash-flow permanence and information content

of dividend increases versus repurchases. Journal of Financial Economics 57, 385-415.

322

Guedes, J., and T. Opler, 1996. The determinants of the maturity of corporate debt issues. Journal of Finance 51, 1809-1833.

Gugler, K., 2003. Corporate governance, dividend payout policy, and the interaction

between dividends, R&D, and capital investment. Journal of Banking and Finance 27, 1297-1321.

Gugler, K., and B. Yurtoglu, 2003. Corporate governance and dividend payout

policy in Germany. European Economic Review 47, 731-758. Gul, F., 1999. Government share ownership, investment opportunity set and

corporate choice in China. Pacific-Basin Finance Journal 7, 157-172 Gustafsoon, U., 2005. The impact of new information on the return in shares and the

implicit volatility in call options. Thesis, University of Lund. Hackbarth, D., 2004. Determinants of corporate borrowing: A behavioral

perspective. Working Paper, Washington University at Saint Louis. Hallock, K., and F. Mashayekhi, 2003. Are formal corporate news announcements

still newsworthy? Evidence from three decades of US data on earnings, splits, and dividends. Working Paper, University of Illinois.

Han, K., S. Lee, and D. Suk, 1999. Institutional shareholders and dividends. Journal

of Financial and Strategic Decisions 12, 53-62. Hand, J., R. Holthausen, and R. Leftwich, 1992. The effect of bond rating agency

announcements on bond and stock prices. Journal of Finance 47, 733-752. Handjinicolaou, G., and A. Kalay, 1984. Wealth redistributions or changes in firm

value: An analysis of returns to bondholders and stockholders around dividend announcements. Journal of Financial Economics 13, 35-63.

Hanlon, M., J. Myers, and T. Shevlin, 2006. The information content of dividends:

Do dividends provide information about future earnings? Working Paper, University of Michigan.

Harris, M., and A. Raviv, 1990. Capital structure and the informational role of debt.

Journal of Finance, 45, 321-350. Harris, M., and A. Raviv, 1991. The theory of capital structure. The Journal of

Finance, 46, 297-355. Hart, O., 1993. Theories of optimal capital structure: The managerial discretion

perspective. In M. Blair (ed.), The Deal Decade: What Takeovers and

323

Leveraged Buyouts Mean for Corporate Governance. Brookings Institutions, Washington DC, 19-53.

Hart, O., and J. Moore, 1995. Debt and seniority: An analysis of the role of hard

claims in constraining management. American Economic Review 85, 567-585.

Healy, P., and K. Palepu, 1988. Earnings information conveyed by dividend

initiations and omissions. Journal of Financial Economics 21, 149-175. Heath, D., and R. Jarrow, 1988. Ex-dividend stock price behavior and arbitrage

opportunities. Journal of Business 61, 95-108. Helwege, J., and N. Liang, 1996. Is there a pecking order? Evidence from a panel of

IPO firms. Journal of Financial Economics 40, 429-458. Henderson, B., N. Jagadeesh, and M. Weisbach, 2006. World markets for raising

new capital. Journal of Financial Economics, Forthcoming. Hietala, P., 1990. Equity markets and personal taxation: The ex-dividend behavior

of Finnish stock prices. Journal of Banking and Finance 14, 327-350. Ho, H., 2003. Dividend policies in Australia and Japan. International Advances in

Economics 9, 91-100. Ho, S., K. Lam, and H. Sami, 2004. The investment opportunity set, director

ownership, and corporate policies: Evidence from an emerging market. Journal of Corporate Finance 10, 383-408.

Hoberg, G., and N. Prabhala, 2006. Dividend policy, risk, and catering. Working

Paper, University of Maryland. Holder, M., F. Langrehr, and J. Hexter, 1998. Dividend policy determinants: An

investigation of the influence of stakeholder theory. Financial Management 27, 73-82.

Hooks, L., and T. Opler, 1993. The determinants of corporate bank borrowing.

Federal Reserve Bank of Dallas Financial Industry Studies, Working Paper No. 1-93.

Hovakimian, A., 2004. The role of target leverage in security issuance and

repurchases. Journal of Business 77, 1041-1072. Hovakimian, A., 2006. Are observed capital structures determined by equity market

timing? Journal of Financial and Quantitative Analysis 41, 221-243.

324

Hovakimian, A., T. Opler, and S. Titman, 2001. The debt-equity choice. Journal of Financial and Quantitative Analysis 36, 1-24.

Howe, K., J. He., and G. Kao, 1992. One-time cash flow announcements and free

cash-flow theory: Share repurchases and special dividends. Journal of Finance 47, 1963-1975.

Hsiao, C., 2003. Analysis of Panel Data, 2nd ed. Cambridge University Press,

Cambridge. Hu, S., and Y. Tseng, 2004. Who wants to trade around ex-dividend days? Working

Paper, National Taiwan University. Huang, H., 2001a. Bayesian analysis of the dividend behavior. Applied Financial

Economics 11, 333-339. Huang, H., 2001b. Bayesian analysis of SUR Tobit model. Applied Economics

Letters 8, 617-622.

Huang, G., and F. Frank, 2006. The determinants of capital structure: Evidence from China. China Economic Review 17, 14-36.

Huang, R., and J. Ritter, 2005. Testing the market timing theory of capital structure.

Working Paper, University of Florida. Ikenbery, D., J. Lakonishok, and T. Vermaelen, 1995. Market underreaction to open

market repurchases. Journal of Financial Economics 39, 181-208. Ikenberry, D., G. Rankine and E. Stice, 1996. What do stock splits really signal?

Journal of Financial and Quantitative Analysis 31, 357-75. Islam, M., 2002. Performance and prospects of Muscat Securities Market: A profile

for investors and some policy issues. Mirat Al’ Jama 5, 10-18. Islam, M., 2003a. Characteristics, performance and prospects of Muscat Securities

Market: Facts and figures for international investors. Journal of American Academy of Business 3, 230-236.

Islam, M., 2003b. Money and credit in the monetary transmission mechanism in

Oman: Evidence from cointegration and vector autoregressive models. International Journal of Applied Business and Economic Research 1, 47-72.

Islam, M., 2003c. Regulation and supervision of financial institutions in GCC

countries. Managerial Finance 29, 17-42.

325

Jain, P., 1992. Equity issues and changes in expectations of earnings by financial analysis. Review of Financial Studies 5, 669-683.

Jain, R., 2006. The effect of taxes, trading frictions, and fund premium on the ex-

dividend day price behavior of closed-end funds. Working Paper, Indian School of Business.

Jakob, K., and T. Ma, 2004. Tick size, NYSE Rule 118 and ex-dividend stock price

behavior. Journal of Financial Economics 72, 605-625.

Jakob, K., and T. Ma, 2005. Limit order adjustment mechanisms and ex-dividend day stock price behavior. Financial Management 34, 89-101.

Jakob, K., and T. Ma, 2006. Are ex-day dividend clientele effects dead? Dividend

yield versus dividend size. Journal of Empirical Finance, forthcoming. Jalilvand, A., and R. Harris, 1984. Corporate behavior in adjusting to capital

structure and dividend targets: An econometric study. Journal of Finance 39, 127-145.

Jayaraman, S., 2006. Firm value and tax benefits of debt: Large sample evidence of

Modigliani and Miller (1963). Working Paper, University of North Carolina at Chapel Hill.

Jayaraman, N., and K. Shastri, 1988. The valuation of specially designed dividends.

Journal of Financial and Quantitative Analysis 23, 301-312. Jensen, M., 1986. Agency costs of free cash flow, corporate finance, and takeovers.

American Economic Review 76, 323-329. Jensen, M., and W. Meckling, 1976. Theory of the firm: Managerial behavior,

agency costs and ownership structure. Journal of Financial Economics 3, 305-360.

Jensen, G., D. Solberg, and T. Zorn, 1992. Simultaneous determination of insider

ownership, debt, and dividend policies. Journal of Financial and Quantitative Analysis 27, 247-264.

Jenter, D., 2005. Market timing and managerial portfolio decisions. Journal of

Finance 60, 1903-1949. Jin, Z., 2000. On the differential market reaction to dividend initiations. Quarterly

Review of Economics and Finance 40, 263-277. John, K., and H. Lang, 1991. Insider trading around dividend announcements:

Theory and evidence. Journal of Finance 46, 1361-1389.

326

John, K., and J. Williams, 1985. Dividends, dilution and taxes: A signaling

equilibrium. Journal of Finance 40, 1053-1070. Johnson, S., 1998. The effect of bank debt on optimal capital structure. Financial

Management 26, 47-56. Johnson, S., J. Lin, and K. Song, 2006. Dividend policy, signaling, and discounts on

closed-end funds. Journal of Financial Economics, Forthcoming. Jones, E., and J. Danbolt, 2005. Empirical evidence on the determinants of the stock

market reaction to product and market diversification announcements. Applied Financial Economics 15, 623-629.

Jordan, J., 1999. Bank managers’ opportunistic trading of their firms’ shares.

Financial Management 28, 36-51. Jung, K., Y. Kim, and R. Stulz, 1996. Timing, investment opportunities, managerial

discretion, and the security issue decision. Journal of Financial Economics 42, 159-185.

Kadapakkam, P., 2000. Reduction of constraints on arbitrage trading and market

efficiency: An examination of ex-day returns in Hong Kong after introduction of electronic settlement. Journal of Finance 55, 2841-2861.

Kadapakkam, P., and V. Martinez, 2005. Ex-dividend returns: The Mexican puzzle.

Working Paper, University of Texas at San Antonio. Kalay, A., 1982a. The ex-dividend day behavior of stock prices: A reexamination of

the clientele effect. Journal of Finance 37, 1059-1070. Kalay, A., 1982b. Stockholder-bondholder conflict and dividend constraints.

Journal of Financial Economics 10, 211-233. Kalay, A., and U. Lowenstein, 1985. Predictable events and excess returns: The

case of dividend announcement. Journal of Financial Economics 14, 423-449.

Kalay, A., and R. Michaely, 2000. Dividends and taxes: A reexamination. Financial

Management 29, 55-75. Kane, A., Y. Lee, and A. Marcus, 1984. Earnings and dividend announcements: Is

there a corroboration effect? Journal of Finance 39, 1091-1099. Kania, S., and F. Bacon, 2005. What factors motivate the corporate dividend

decision? ASBBSE-Journal 1, 97-107.

327

Kaplan, S. and L. Zingales, 1997. Do financing constraints explain why investment

is correlated with cash flow? Quarterly Journal of Economics112, 169-215. Karpoff, J., and R. Walking, 1988. Short-term trading around ex-dividend days:

Additional evidence. Journal of Financial Economics 21, 291-198. Karpoff, J., and R. Walking, 1990. Dividend capture in NASDAQ stocks. Journal

of Financial Economics 28, 39-66. Kato, K., and U. Loewenstein, 1995. The ex-dividend day behavior of stock prices:

The case of Japan. The Review of Financial Studies 8, 817-847. Kayhan, A., and S. Titman, 2006. Firms’ histories and their capital structure.

Journal of Financial Economics, Forthcoming. Keen, H., 1983. The impact of a dividend cut announcement on bank share prices.

Journal of Bank Research 13, 274-291 Keim, D., 1985. Dividend yields and stock returns: Implications of abnormal

January returns. Journal of Financial Economics 14, 473-489.

Keim, D., 1989. Trading patterns, bid-ask spreads and estimated security returns: The case of common stocks at the turn of the Year. Journal of Financial Economics 25, 75-97.

Kester, C., 1986. Capital and ownership structure: A comparison of United States

and Japanese corporations. Financial Management 15, 5-16. Kester, G., and M. Isa, 1996. Dividend policy in Malaysia: A comparative analysis.

Malaysian Journal of Economic Studies 33, 33-48. Kim, E., 1978. A mean-variance theory of optimal capital structure and corporate

debt capacity. Journal of Finance 33, 45-64.

Kim, B., and G. Maddala, 1992. Estimation and specification analysis of models of dividend behavior based on censored panel data. Empirical Economics 17, 111-124.

Kim, W., and E. Sorensen, 1986. Evidence on the impact of the agency costs of debt

on corporate debt policy. Journal of Financial and Quantitative Analysis 21, 131-144.

Kisgen, D., 2006. Credit ratings and capital structure. Journal of Finance 61, 1035-

1072.

328

Koch, A., and A. Sun, 2004. Dividend changes and the persistence of past earnings changes. Journal of Finance 59, 2093-2116.

Koski, J., 1996. A microstructure analysis of ex-dividend stock price behavior

before and after the 1984 and 1986 tax reform acts. Journal of Business 69, 313-338.

Koski, J., and J. Scruggs, 1998. Who trades around the ex-dividend day? Evidence

from NYSE audit file data. Financial Management 27, 58-72. Korajzcyk, R., and A. Levy, 2003. Capital structure choice: Macroeconomic

conditions and financial constraints. Journal of Financial Economics 68, 75-109.

Korajczyk, R., D. Lucas, and R. McDonald, 1991. The effect of information releases

on the pricing and timing of equity issues. Review of Financial Studies 4, 685-708.

Kothari, S., and J. Warner, 2006. Econometrics of event studies. Working Paper,

University of Rochester. Kraus, A., and R. Litzenberger, 1973. A state-preference model of optimal financial

leverage. Journal of Finance 28, 911-922. Kwan, C., 1981. Efficient market tests of the information content of dividend

announcements: Critique and extension. Journal of Financial and Quantitative Analysis 16, 193-206.

Lakonishok, J., and S. Smidt, 1984. Volume and turn-of-the-year behavior. Journal

of Financial Economics 13, 435-455. Lakonishok, J., and T. Vermaelen, 1983. Tax reform and ex-dividend day behavior.

Journal of Finance 38, 1157-1179. Lakonishok, J., and T. Vermaelen, 1986. Tax-induced trading around the ex-

dividend days. Journal of Financial Economics 16, 287-319. Lamoureux, C. and P. Poon, 1987. The market reaction to stock splits. Journal of

Finance 42, 1347-70. Lang, L., and R. Litzenberger, 1989. Dividend announcements: Cash flow signaling

vs. free cash flow hypothesis? Journal of Financial Economics 24, 181-91. Lang, L., E. Ofek, and R. Stulz, 1996. Leverage, investment, and firm growth.


329

La Porta, R., F. Lopez-De-Silanes, and A. Shleifer, 1999. Corporate ownership around the world. Journal of Finance 54, 471-517.

La Porta, R., F. Lopez-De-Silanes, A. Shleifer, and R. Vishny, 2000. Agency

problems and dividend policies around the world. Journal of Finance 55, 1-33.

Lasfer, M., 1995a. Agency costs, taxes and debt: The UK evidence. European

Financial Management 1, 265-285. Lasfer, M., 1995b. Ex-day price behavior: Tax or short-term trading effects?

Journal of Finance 50, 875-897. Lasfer, M., 1996. Taxes and dividends: The UK evidence. Journal of Banking and

Finance 20, 455-472. Lasfer, M., and M. Zenonos, 2003. Taxes and ex-day behavior in Europe. Working

Paper, City University.

Laub, P., 1976. On the informational content of dividends. Journal of Business 49, 73-80.

Leary, M., and M. Roberts, 2005a. Do firms rebalance their capital structures?

Journal of Finance 60, 2575-2619. Leary, M., and M. Roberts, 2005b. The pecking order, debt capacity, and

information asymmetry. Working Paper, University of Pennsylvania. Lease, R., K. John, A. Kalay, U. Loewenstein, and O. Sraig, 2000. Dividend Policy:

Its Impact on Firm Value. Harvard Business School Press, Massachusetts. Lease, R., R. Masulis, and J. Page, 1991. An investigation of market microstructure

impacts on event study returns. Journal of Finance 46, 1523-1536. Leftwich, R., and M. Zmijewski, 1994. Contemporaneous announcements of

dividends and earnings. Journal of Accounting, Auditing and Finance 9, 725-762.

Leither, S., and H. Zimmerman, 1993. Market value and aggregate dividends: A

reappraisal of recent tests and evidence from European markets. Swiss Journal of Economics and Statistics 129, 99-119.

Leledakis, G., G. Papaioannou, N. Travlos, and N. Tsangarakis, 2005. Stock splits

on the Athens Stock Exchanges. Working Paper, Athens Laboratory of Business Administration.

330

Lemmon, M., M. Roberts, and J. Zender, 2006. Back to the beginning: Persistence and the cross-section of corporate capital structure. Working Paper, University of Colorado at Boulder.

Lemmon, M., and J. Zender, 2004. Debt capacity and tests of capital structure

theories. Working Paper, University of Utah.

Leỏn, C., A. Gamba, and G. Sick, 2003. Real options, capital structure, and taxes. Working Paper, University of Navarra.

Levine, R., and S. Zervos, 1998. Stock markets, banks and economic growth.

American Economic Review 88, 537-558. Li, O., 2005. Trading clienteles, tax attributes, and ex-dividend returns. Working

Paper, University of Norte Dame. Liano, K., W. Hardin, and G. Huang, 2003. The ex-dividend day stock price

behavior and decimalization. Working Paper, Mississippi State University. Lie, E., 2000. Excess funds and agency problems: An empirical study of

incremental cash disbursements. Review of Financial Studies 13, 219-248. Liljeblom, E., 1989. The informational impact of announcements of stock dividends

and stock splits. Journal of Business Finance and Accounting 16, 681-698.

Lintner, J., 1956. Distribution of income of corporations among dividends, retained earnings and taxes. American Economic Review 46, 97-113.

Lintner, J., 1962. Dividends, earnings, leverage, stock prices and supply of capital to

corporations. Review of Economics and Statistics 64, 243-269. Lipson, M., and S. Mortal, 2006. Capital structure decisions and equity market

liquidity. Working Paper, University of Virginia. Litzenberger, R., and K. Ramaswamy, 1979. The effect of personal taxes and

dividends on capital asset prices. Journal of Financial Economics 7, 163-195.

Litzenberger, R., and K. Ramaswamy, 1980. Dividends, short selling restrictions,

tax-induced investor clienteles and market equilibrium. Journal of Finance 35, 469-482.

Litzenberger, R., and K. Ramaswamy, 1982. The effects of dividend on common

stock prices: Tax effects or information effects? Journal of Finance 37, 429-443.

331

Liu, L., 2005. Do firms have target leverage ratios? Evidence from historical market-to-book and past returns. Working Paper, Hong Kong University of Science and Technology.

Lloyd, W., J. Jahera, and D. Page, 1985. Agency costs and dividend payout ratios.

Quarterly Journal of Business and Economics 34, 53-64. Long, J., 1978. The market valuation of cash dividends: A case to consider. Journal

of Financial Economics 6, 235-264. Long, M., and L. Malitz, 1985. Investment patterns and corporate leverage. In B.M.

Friedman (Ed.), Corporate Capital Structure in the United States. National Bureau of Economic Research, Chicago, 325-351.

Lonie, A., G. Abeyratna, D. Power, and C. Sinclair, 1996. The stock market reaction

to dividend announcements: A UK study of complex market signals. Journal of Economic Studies 23, 32-52.

Loughran, T., and J. Ritter, 1995. The new issue puzzle. Journal of Finance 50, 23-

51. Loughran, T., J. Ritter, and K. Rydqvist, 1994. Initial public offerings: International

insights. Pacific-Basin Finance Journal 2, 165-199. Lucas, D., and R. McDonald, 1990. Equity issues and stock price dynamics. Journal

of Finance 45, 1019-1043. MacKay, P., and G. Phillips, 2005. How does industry affect firm financial

structure? Review of Financial Studies 18, 1433-1466. MacKie-Mason, J., 1990. Do taxes affect corporate financing decisions? Journal of

Finance 45, 1471-1493. MacKinlay, A., 1997. Event studies in economics and finance. Journal of Economic

Literature 35, 13-39. Maddala, G., 1987. Limited dependent variable models using panel data. Journal of

Human Resources 22, 307-338. Maloney, M., and J. Mulherin, 1992. The effects of splitting on the ex: A

microstructure reconciliation. Financial Management 21, 44-59. Manos, R., 2002. Dividend policy and agency theory: Evidence on Indian firms.

Working Paper No. 41, University of Manchester.

332

Marsh, P., 1982. The choice between equity and debt: An empirical study. Journal of Financial and Quantitative Analysis 27, 539-560.

Marsh, P., 1993. Dividend announcements and stock price performance. Paper

Presented at the Financial Markets Group Conference on Dividend and Earnings Forecasting and Valuation, London School of Economics, March 23.

Martin, J., and D. Scott 1975. Industry influence on financial structure. Financial

Management 4, 67-73. Masse, I., J. Hanrahan, and J. Kushner, 1997. The effect of Canadian stock splits,

stock dividends and reverse splits on the value of the firm. Quarterly Journal of Business and Economics 36, 51-62.

Mauer, D., and S. Ott, 2000. Agency costs, underinvestment, and optimal capital

structure: The effect of growth options to expand. In M. Brennan and L. Trigeorgis (Eds), Project Flexibility, Agency, and Competition. Oxford University Press, New York, 151-180.

Mauer, D., and S. Sarkar, 2005. Real options, agency conflicts, and optimal capital

structure. Journal of Banking and Finance 29, 1405-1428. Mauer, D., and A. Triantis, 1994. Interaction of corporate financing and investment

decisions: A dynamic framework. Journal of Finance 49, 1253-1277. Maury, C., and A. Pajuste, 2002. Controlling shareholders, agency problems, and

dividend policy in Finland. The Finnish Journal of Business Economics 51, 15-45.

Mayer, C., and O. Sussman, 2004. A new test of capital structure. Working Paper,

Oxford University. McDonald, R., 2001. Cross-border investing with tax arbitrage: The case of German

tax credit. Review of Financial Studies 14, 617-657. McDonald, J., B. Jacquillat, and M. Nussenbaum, 1975. Dividend, investment and

financing decisions: Empirical evidence on French firms. Journal of Financial and Quantitative Analysis 10, 741-755.

McNichols, M., and A. Dravid, 1990. Stock dividends, stock splits, and signaling.

Journal of Finance 45, 857-879. Menyah, K., 1993. Ex-dividend equity pricing under U.K. tax regimes. Journal of

Business Finance and Accounting 20, 61-82.

333

Michaely, R., 1991. Ex-dividend day stock price behavior: The case of the 1986 tax reform act. Journal of Finance 46, 845-860.

Michaely, R., and M. Murgia, 1995. The effect of tax heterogeneity on prices and

volume around the ex-dividend day: Evidence from the Milan Stock Exchange. Review of Financial Studies 8, 369-399.

Michaely, R., R. Thaler, and K.L. Womack, 1995. Price reactions to dividend

initiations and omissions: Overreaction or drift? Journal of Finance 50, 573-608.

Michaely, R., and J. Vila, 1995. Investors’ heterogeneity, prices, and volume around

the ex-dividend day. Journal of Financial and Quantitative Analysis 30, 171-198.

Michaely, R., and J. Vila, 1996. Trading volume with private valuation: Evidence

from the ex-dividend day. Review of Financial Studies 9, 471-509. Michaely, R., J. Vila, and J. Wang, 1996. A model of trading volume with tax-

induced heterogeneous valuation and transaction costs. Journal of Financial Intermediation 5, 340-371.

Michel, A., and I. Shaked, 1986. Country and industry influence on dividend policy:

Evidence from Japan and the U.S.A. Journal of Business Finance and Accounting 13, 365-381.

Miller, M., 1986. Behavioral rationality in finance: The case of dividends. Journal

of Business 59, 451-468. Miller, M., 1988. The Modigliani-Miller propositions after thirty years. Journal of

Economic Perspectives 2, 99-120. Miller, M., and F. Modigliani, 1961. Dividend policy, growth, and the valuation of

shares. Journal of Business 34, 411-433. Miller, M., and K. Rock, 1985. Dividend policy under asymmetric information.

Journal of Finance 40, 1031-1051. Miller, M., and M. Scholes, 1978. Dividends and taxes. Journal of Financial

Economics 6, 333-364. Miller, M., and M. Scholes, 1982. Dividend and taxes: Some empirical evidence.

Journal of Political Economy 90, 1118-1141.

334

Milonas, N., and N. Travlos, 2001. The ex-dividend day stock price behavior in the Athens Stock Exchange. Working Paper, Cardiff University Business School.

Milonas, N., N. Travlos, J. Xiao, and C. Tan, 2006. The ex-dividend day stock price

behavior in the Chinese Stock Market. Pacific-Basin Finance Journal 14, 155-174.

Ministry of National Economy, Various Publications, Muscat, Oman. Mishra, A., 2005. An empirical analysis of market reaction around the bonus issues

in India. Journal of Applied Finance 11, 21-39. Mitra, D., 1997. The information content of specially designated dividend

announcements. Mid-Atlantic Journal of Business 33, 37-47. Modigliani, F., and M. Miller, 1958. Corporate income taxes and the cost of capital:

A correction. American Economic Review 53, 261-297.

Mollah, A., K. Keasey, and H. Short, 2000. The influence of agency costs on dividend policy in an emerging market: Evidence from the Dhaka Stock Exchange. Working Paper, University of Bath.

Morgan, G., and S. Thomas, 1998. Taxes, dividend yields and returns in the UK

equity market. Journal of Banking and Finance 22, 405-423. Muradoglu, G., and J. Huskey, 2005. The impact of SEC litigation on firm value.

Working Paper, City University. Muscat Securities Market, Annual Reports 1989 – 2005, Muscat, Oman. Muscat Securities Market, Annual Statistical Bulletin 2005, Muscat, Oman.

Myers, S., 1977. Determinants of corporate borrowing. Journal of Financial

Economics 5, 147-175. Myers, S., 1984. The capital structure puzzle. Journal of Finance 39, 575-592. Myers, S., 2001. Capital structure. Journal of Economic Perspectives 15, 81-102. Myers, S., 2003. Financing of corporations. In G.M. Constantinides, M. Harris, and

R. Stulz (eds), Handbook of the Economics and Finance, Vol. 1A, Corporate Finance. Elsevier B.V, 215-253.

335

Myers, S., and N. Majluf, 1984. Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics 13, 187-221.

Naceur, S., M. Goaied, and A. Belanes, 2005. A re-examination of dividend policy:

A dynamic panel data analysis. Working Paper, Institut des Etudes Commerciales.

Nakamura, M., 1989. Asymmetry in dividend behavior of US and Japanese firms.

Managerial and Decision Economics 10, 261-274. Nam, J., J. Thornton Jr, P. Viswanath, and J. Wang, 2005. Information revelation

through dividend initiations. Working Paper, Kent State University. Naranjo, A., M. Nimalendran, and M. Ryngaert, 2000. Time variation of ex-day

stock returns and corporate dividend capture: A reexamination. Journal of Finance 55, 2357-2372.

Neter, J., W. Wasserman, and M. Kunter, 1985. Applied Linear Statistical Models.

2nd ed. Irwin Inc, Homewood, IL. Nissim, D., and A. Ziv, 2001. Dividend changes and future profitability. Journal of

Finance 6, 2111-2133. Noe, T., 1988. Capital structure and signaling game equilibria. Review of Financial

Studies 1, 331-356. Norton, E., 1991. Similarities and differences in small and large corporations beliefs

about capital structure policy. Small Business Economics 2, 229-245. Novaes, W., 2003. Capital structure choice when managers are in control:

Entrenchment versus efficiency. Journal of Business 76, 49-82. Ofer, A., and D. Siegel, 1987. Corporate financial policy, information, and market

expectations: Empirical investigation of dividends. Journal of Finance 42, 889-911.

Olsen, R., 1987. Note on uniqueness of the maximum likelihood estimator for the

Tobit model. Econometrica 46, 1211-1215. Omet, G., 2004. Dividend policy behavior in the Jordanian capital market.

International Journal of Business 9, 287-299. Opler, T., and S. Titman, 1997. The debt-equity choice. Working Paper No. 97-9,

Ohio State University.

336

Ozkan, A., 2001. Determinants of capital structure and adjustment to long run target: Evidence from UK company panel data. Journal of Business Finance and Accounting 28, 175-199.

Pagano, M., F. Panetta and L. Zingales, 1998. Why do companies go public? An

empirical analysis. Journal of Finance 50, 1421-1460. Pandey, I., 2003. Corporate dividend policy and behaviour: The Malaysian

evidence. Asian Academy of Management Journal 8, 17-32. Pandey, I., and R. Bhat, 2004. Dividend behaviour of Indian companies under

monetary policy restrictions. Working Paper, Indian Institute of Management.

Papaioannou, G., and C. Savarese, 1994. Corporate dividend policy response to the

tax reform act of 1986. Financial Management 23, 56-63. Papaioannou, G., N. Travlos, and N.V. Tsangarakis, 2000. Valuation effects of

Greek stock dividend distributions. European Financial Management 6, 515-531.

Park, M., D. Yang, C. Nam, and Y. Ha, 2002. Mergers and acquisitions in the

telecommunication industry: Myths and reality. Electronics and Telecommunications Research Institute Journal 24, 56-64.

Partington, G., 1985. Dividend policy and its relationship to investment and

financing policies: Empirical evidence. Journal of Business Finance and Accounting 12, 531-542.

Partington, G., 1989. Variables influencing dividend policy in Australia: Survey

results. Journal of Business Finance and Accounting 16, 165-182. Penman, S., 1983. The predictive content of earnings forecasts and dividends.

Journal of Finance 38, 1181-1199. Pettit, R., 1972. Dividend announcements, security performance and capital market

efficiency. Journal of Finance 27, 993-1008. Pettit, R., 1976. The impact of dividend and earnings announcements: A

reconciliation. Journal of Business 49, 89-96. Plesko, G., 2001. The role of short-term debt in capital structure. Proceedings of the

Ninety-Third Annual Conference, Washington D.C.: National Tax Association – Tax Institute of America, 135-140.

337

Porter, D., 1992. The probability of a trade at the ask: An examination of intraday and interday behavior. Journal of Financial and Quantitative Analysis 27, 209-227.

Poterba, J., 1986. The market valuation of cash dividends: Citizens utilities case

reconsidered. Journal of Financial Economics 15, 395-406. Poterba, J., and L. Summers, 1984. New evidence that taxes affect the valuation of

dividends. Journal of Finance 39, 1397-1415. Prowse, S., 1990. Institutional investment patterns and corporate financial behavior

in the United States and Japan. Journal of Financial Economics, 27, 43-66

Rajan, R., and L. Zingales, 1995. What do we know about capital structure? Some evidence from international data. Journal of Finance 50, 1421-1460.

Rajan, R., and L. Zingales, 1998. Which capitalism? Lessons from the East Asian

crisis. Journal of Applied Corporate Finance 11, 40-48. Rankine, G., and E. Stice, 1997. The market reaction to the choice of accounting

method for stock splits and large stock dividends. Journal of Financial and Quantitative Analysis 32, 161-182.

Redding, L., 1997. Firm size and dividend payouts. Journal of Financial

Intermediation 6, 224-248. Remmers, L., A. Stonehill, R. Wright, and T. Beekhuisen, 1974. Industry and size

as debt ratio determinants in manufacturing internationally. Financial Management 3, 24-32.

Richardson, G., S. Sefcik, and R. Thompson, 1986. A test of divided irrelevance

using volume reactions to a change in dividend policy. Journal of Financial Economics 17, 313-333.

Roberts, M., 2002. The dynamics of capital structure: An empirical analysis of a

partially observable system. Working Paper, University of Pennsylvania. Robichek, A., and S. Myers, 1966. Problems in the theory of optimal capital

structure. Journal of Financial and Quantitative Analysis 1, 1-35. Roper, A., 2002. Life cycle patterns in capital structure dynamics. Working Paper,

University of Wisconsin. Ross, S., 1977. The determinants of financial structure: The incentive signaling

approach. Bell Journal of Economics 8, 23-40.

338

Rossi, S., 2005. Technological innovations and capital structure. Working Paper, London Business School.

Roy, S., and J. Cheung, 1985. Target payout and the association between dividends

and share prices. Accounting and Finance 25, 57-76. Rozeff, M., 1982. Growth, beta, and agency costs as determinants of dividend

payout ratios. Journal of Financial Research 5, 249-259. Rumelt, R., 1974. Strategy, Structure, and Economic Performance. Harvard

University Press, Cambridge. Salas, J., and C. Chahyadi, 2005. A decomposition of the dividend payout ratio

trend in the 20th century. Working Paper, University of Oklahoma. Salim, A., 1998. Muscat Securities Market – An overview. Al Mawarid Securities

Co. SAOG, Muscat, Oman. Sawicki, J., 2002. An investigation into the dividend of firms in East Asia. Working

Paper, Nanyang Technological University. Saxena, A., 1999. Determinants of dividend payout policy: Regulated versus

unregulated firms. Working Paper, State University of West Georgia. Schooley, D., and L. Barney, 1994. Using dividend policy and managerial

ownership to reduce agency costs. Journal of Financial Research 17, 363-373.

Schwartz, E., and J. Aronson, 1967. Some surrogate evidence in support of the

concept of optimal capital structure. Journal of Finance 22, 10-18. Scott, J., 1976. A theory of optimal capital structure. Bell Journal of Economics 7,

33-54. Seiler, M., 2000. The efficacy of event-study methodologies: Measuring EREIT

abnormal performance under conditions of induced variance. Journal of Financial and Strategic Decisions 13, 101-112.

Share-Holding Guide of MSM Listed Companies. Muscat Securites Market, 1989 –

2005, Muscat, Oman. Sharpe, I., and G. Pooley, 1991. Asymmetric information, adjustment costs and

capital structure of Australian finance companies. Pacific Accounting Review 3, 93-125.

339

Shaw, W., 1991. An examination of ex-dividend day stock price movements: The case of nontaxable master limited partnership distributions. Journal of Finance 46, 755-771.

Shenoy, C., and P. Koch, 1996. The firm's leverage-cash flow relationship. Journal

of Empirical Finance 2, 307-331. Shevlin, T., 1982. Australian corporate dividend policy: Empirical analysis.

Accounting and Finance 22, 1-22. Shleifer, A., and R.Vishny, 1989. Management entrenchment: The case of manager-

specific investments. Journal of Financial Economics 25, 123-140.

Short, H., 1994. Ownership, control, financial structure and the performance of firms. Journal of Economic Surveys 8, 203-249.

Short, H., H. Zhang, and K. Keasey, 2002. The link between dividend policy and

institutional ownership. Journal of Corporate Finance 8,105-122. Shyam-Sunder, L., and S. Myers, 1999. Testing static tradeoff against pecking order

models of capital structure. Journal of Financial Economics 51, 219-244. Sibilkov, V., 2005. Asset liquidity and capital structure. Working Paper, Purdue

University. Siddiqi, M., 1995. An indirect test for dividend relevance. Journal of Financial

Research 18, 89-101. Singh, A., 1995. Corporate financial patterns in industrialising economies: A

comparative study. IFC Technical Paper No. 2, Washington D.C., International Finance Corporation.

Singh, A., and J. Hamid, 1992. Corporate financial structures in developing

countries. IFC Technical Paper No. 1, Washington D.C., International Finance Corporation.

Smith, C., and J. Warner, 1979. On financial contracting: An analysis of bond

covenants. Journal of Financial Economics 7, 117-161. Smith, C., and R. Watts, 1992. The investment opportunity set and corporate

financing, dividend, and compensation policies. Journal of Financial Economics 32, 263-292.

Song, J., and G. Philippatos, 2004. Have we resolved some critical issues related to

international capital structure? Empirical evidence from the 30 OECD countries. Working Paper, University of Tennessee.

340

Spiess, D., and J. Affleck-Graves, 1995. Underperformance in long-run stock

returns following seasoned equity offerings. Journal of Financial Economics 38, 243-267.

Sponholtz, C., 2004. Separating the stock market’s reaction to dividend and

earnings announcements: The case of simultaneous announcements in Denmark. Working Paper, University of Aarhus.

Stacescu, B., 2004. Dividend policy in Switzerland. Working Paper, Swiss Banking

Institute. Stohs, M., and D. Mauer, 1996. The determinants of corporate debt maturity

structure. Journal of Business 69, 279-312. Stonehill, A., and T. Stitzel, 1969. Financial structure and multinational corporation.

California Management Review 12, 91-96. Strebulaev, I., 2006. Do tests of capital structure theory mean what they say?

Journal of Finance, forthcoming. Stulz, R., 1990. Managerial discretion and optimal financing policies. Journal of

Financial Economics 26, 3-28. Taggart, R., 1977. A model of corporate financing decisions. Journal of Finance 32,

1467-1484. Thies, C., and M. Klock, 1992. Determinants of capital structure. Review of

Financial Economics 1, 40-52. Thomson, L., and R. Watson, 1989. Historic cost earnings, current cost earnings and

the dividend decision. Journal of Business Finance and Accounting 16, 1-24.

Titman, S., and S. Tsyplakov, 2005. A dynamic model of optimal capital structure. Working Paper, University of Texas at Austin.

Titman, S., and R. Wessels, 1988. The determinants of capital structure choice.

Journal of Finance 43, 1-19 Tong, G., and C. Green, 2005. Pecking order or trade-off hypothesis? Evidence on

the capital structure of Chinese companies. Applied Economics 37, 2179-2189.

Toy, N., A. Stonehill, L. Remmers, R. Wright, and T. Beekhuisen, 1974. A

comparative international study of growth, profitability and risk as

341

determinants of corporate debt ratios in manufacturing sector. Journal of Financial and Quantitative Analysis 9, 875-886.

Travlos, N., L. Trigeorgis, and N. Vafeas, 2001. Shareholder wealth effects of

dividend policy changes in an emerging stock market: The case of Cyprus. Multinational Finance Journal 5, 87-112.

Trojanowski, G., 2004. Ownership structure and payout policy in the UK. Working

Paper, Tilburg University. Trojanowski, G., and L. Renneboog, 2005. Patterns in payout policy and payout

channel choice of UK firms in the 1990s. Working Paper, Tilburg University.

Uddin, M., 2003. Effect of dividend announcements on shareholders’ value:

Evidence from Dhaka Stock Exchange. Working Paper, University of Dhaka.

Van Eaton, R.D., 1999. Stock price adjustment to the information in dividend

changes. Review of Quantitative Finance and Accounting 12, 113-33. Venkatesh, P., and R. Chiang, 1986. Information asymmetry and the deal bid-ask

spread: A case study of earnings and dividend announcements. Journal of Finance 41, 1089-03.

Viswanath, P., 1993. Strategic considerations, the pecking order hypothesis, and

market reactions to equity financing. Journal of Financial and Quantitative analysis 28, 213-234.

Vogt, S., 1994. The cash flow/investment relationship: Evidence from U.S.

manufacturing firms. Financial Management 23, 3-20. Wald, J., 1999. How firm characteristics affect capital structure: An international

comparison. Journal of Financial Research 22, 161-187.

Walsh, E., and J. Ryan, 1997. Agency and tax explanations of security issuance decisions. Journal of Business Finance & Accounting 24, 943-961.

Walter, J., 1963. Dividend policy: Its influence on the value of the enterprise.

Journal of Finance 18, 280-291. Wang, Y., 2005. The effect of dividend initiations on stock returns: A propensity

score matching approach. Working Paper, University of Toronto. Warner, J., 1977. Bankruptcy, absolute priority, and the pricing of risky debt claims.


342

Watts, R., 1973. The information content of dividends. Journal of Business 46, 191-

211. Welch, I., 2004. Capital structure and stock returns. Journal of Political Economy

112, 106-131. Welch, I., and G. Hoberg, 2002. What do book values of equity mean? Working

Paper, Yale University. Wei, G., W. Zhang, and J. Xiao, 2003. Dividend policy and ownership structure in

China. Working Paper, Cardiff University. Wei, J., and J. Xiao, 2005. Shareholder preferences and dividend payment in China.

Working Paper, Cardiff University. White, H., 1980. A heteroscedasticity-consistent covariance matrix estimator and a

direct test for heteroscedasticity. Econometrica 48, 817-838. Whitworth, J., and R. Rao, 2006. Ex-dividend stock price behaviour: Evidence from

a century of tax law changes. Working Paper, Oklahoma State University. Williamson, O., 1988. Corporate finance and corporate governance. Journal of

Finance 43, 567-591. Woolridge, J., 1982. The information content of dividend changes. Journal of

Financial Research 5, 237-247. Woolridge, J., 1983. Dividend changes and security prices. Journal of Finance 38,

1607-1615. Xu, Z., 2006. Do firms adjust toward a target leverage level? Working Paper,

University of Toronto. Yoon, P., and L. Starks, 1995. Signaling, investment opportunities, and dividend

announcements. Review of Financial Studies 8, 995-1018. Zeckhauser, R., and J. Pound, 1990. Are large shareholders effective monitors? An

investigation of share ownership and corporate performance. In R.G. Hubbard (ed.), Asymmetric Information, Corporate Finance, and Investment. University of Chicago Press, Chicago.

Zeng, T., 2003. What determines dividend policy: A comprehensive test. Journal of

American Academy of Business 2, 304-309.

343

Zhang, R., 2005. The effects of firm-and country-level governance mechanisms on dividend policy, cash holdings, and firm value: A cross-country study. Working Paper, Georgia Southern University.

Zwiebel, J., 1996. Dynamic capital structure under managerial entrenchment.

American Economic Review 86, 1197-1215.

capital structure and dividend policy in a personal tax free environment

Documents