Dividend policy and firm performance

MSc Financial Decision Analysis

Does Dividend Policy Matter?

The Impact of Dividend Policy on

Corporate Performance: UK Evidence

Emad Shehadeh

Student ID: UP 516293

Supervised by: Mr. Imad Chbib

December 2012

Portsmouth University Business School

Portsmouth University Business School

MSc Financial Decision Analysis

Title: Does Dividend Policy Matter? The Impact of Dividend Policy on Corporate

Performance: UK Evidence

Author: Emad Shehadeh

Tutor: Mr. Imad Chbib

Year of submission: December 2012

“This project is submitted in partial fulfilment of the requirements for the degree of MSc

Financial Decision Analysis. I, the undersigned, declare that this project report is my own

original work. Where I have taken ideas and or wording from another source, this is

explicitly referenced in the text.

Signed............................................................”

“I give permission that this report may be photocopied and made available for inter-library

loan for the purpose of research.

Signed ...........................................................”

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Acknowledgment

First and above all I want to praise God for providing me this opportunity and granting me

the ability to proceed successfully. I would like to thank my family who gave me the moral as

well as the financial support I required during my studying. It would have been impossible to

write this dissertation without the guidance and endless support of my supervisor Mr Imad

Cbhib. I warmly thank and appreciate my friends and colleagues in MSc Financial Decision

Analysis for their motivation to finish this course. Special thanks to the staff working in the

University of Portsmouth.

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Abstract

The purpose of this paper is to examine the relationship between dividend policy and firm

performance in the UK stock market. The research is based on 283 companies that

maintained their existence in the UK FTSE all shares index between 2005 and 2010. The

study used dividend yield and dividend pay-out ratio as dividend policy indicators and share

price volatility, Tobin Q and return on assets as firm performance measurements. The

Statistical Package for the Social Sciences system (SPSS) was used to run a linear regression

to explore the relations among the variables. The study results suggest different relations

between the variables based on the measures used. It shows that dividend yield have a

significant negative relationship with share price volatility, Tobin Q and a positive

relationship with return on assets. On the other hand, the results indicates a significant

negative relationship between dividend pay-out ratio and share price volatility, a positive

relationship between dividend pay-out ratio and Tobin Q and return on assets.

In addition, it shows the effect of firms’ debt ratio, size, industry and board of directors’ size

on its performance. The results propose a significant negative relationship between firms

share price volatility and its industry, but a positive relationship between firms Tobin Q and

return on assets with its industry. Board of directors’ size have a significant negative

relationship with share price volatility, a negative relationship with Tobin Q and a non-

significant relationship with return on assets. Firm sizes have significant negative relationship

with share price volatility and a positive relationship with Tobin Q and return on assets. Debt

ratio results showed a non-significant relationship with share price volatility and return on

assets, but a positive relationship with Tobin Q. The study examined as well the effect of the

financial credit crisis on firms’ dividend policy and performance. It suggests that dividend

pay-out ratio and debt ratio were strongly affected by the financial crisis. The paper supports

the fact that firms’ dividend policy affects its performance and future value in sample of

firms listed in the UK market.

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Table of Contents Chapter One ............................................................................................................................... 1

1.0 Introduction ...................................................................................................................... 1

1.1 Background ...................................................................................................................... 1

1.2 Firm’s performance .......................................................................................................... 2

1.3 Aims and Objectives ........................................................................................................ 3

1.4 Research Questions .......................................................................................................... 4

1.5 Research Methodology .................................................................................................... 4

1.6 Research Lay-out ............................................................................................................. 4

Chapter Two............................................................................................................................... 5

2.0 Literature Review............................................................................................................. 5

2.1 Introduction ...................................................................................................................... 5

2.1 Efficient Market Hypothesis and Stock price’s volatility ................................................ 6

2.2 Dividend policy and Firm performance ........................................................................... 6

2.3 Dividend policy changes and share price volatility. ........................................................ 7

2.4 Theories of Dividend policy ............................................................................................ 8

2.4.1 Dividend Irrelevance Theory .................................................................................... 8

2.4.2 Agency Cost theory................................................................................................... 9

2.4.3 Signalling and Free cash flow theory...................................................................... 10

2.4.4 Bird in the hand theory ........................................................................................... 11

2.4.5 Cliental effects theory ............................................................................................. 11

2.5 Debt Ratio effect on firms’ dividend policy and performance. ..................................... 12

2.6 Board directors’ size effect on firms’ dividend policy and performance. ..................... 13

2.7 Industry type effect on firms’ dividend policy and performance. ................................. 14

2.8 Firm size effect on firms’ dividend policy and performance. ........................................ 14

2.9 Historical Pay-out Ratio effect on firms’ dividend policy and performance. ................ 15

2.10 Summary ...................................................................................................................... 15

Chapter Three........................................................................................................................... 17

3.0 Methodology .................................................................................................................. 17

3.1 Introduction .................................................................................................................... 17

3.2 Techniques and sources of data collection..................................................................... 17

3.3 Dividend policy measures .............................................................................................. 17

3.4 Firm performance measures ........................................................................................... 18

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3.5 Research control variables. ............................................................................................ 19

3.6 Research equations......................................................................................................... 19

3.7 Definition of research variables ..................................................................................... 21

3.7.1 Debt ratio ................................................................................................................ 21

3.7.2 Firm size.................................................................................................................. 21

3.7.3 Board of directors’ size ........................................................................................... 21

3.7.5 Pay-out ratio ............................................................................................................ 21

3.7.6 Industry type ........................................................................................................... 21

3.7.7 Dividend yield ......................................................................................................... 22

3.7.8 Share price volatility ............................................................................................... 22

3.7.9 Tobin’s Q ................................................................................................................ 22

3.8 Research Hypothesis ...................................................................................................... 22

Chapter Four ............................................................................................................................ 24

4.0 Introduction .................................................................................................................... 24

4.1 Data Descriptive Analysis .............................................................................................. 24

4.2 Regression results .......................................................................................................... 29

4.3 Summary ........................................................................................................................ 46

Chapter Five ............................................................................................................................. 48

5.1 Conclusion ..................................................................................................................... 48

5.2 Limitation ....................................................................................................................... 50

References ................................................................................................................................ 52

Appendices ............................................................................................................................... 58

Appendix (1): Variables descriptive analysis ...................................................................... 58

Appendix (2): Linear regression results from the SPSS model for the relationship between

dividend yield and dividend pay-out ratio with share price volatility. ................................ 61


dividend yield and dividend pay-out ratio with Tobin Q. .................................................... 64


dividend yield and dividend pay-out ratio with ROA .......................................................... 67


dividend yield, dividend pay-out ratio and debt ratio with share price volatility. ............... 70


dividend yield, dividend pay-out ratio and debt ratio with Tobin Q. .................................. 73


dividend yield, dividend pay-out ratio and debt ratio with ROA. ....................................... 76

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dividend yield, dividend pay-out ratio and board of directors’ size with share price

volatility. .............................................................................................................................. 79


dividend yield, dividend pay-out ratio and board of directors’ size with Tobin Q. ............. 82


dividend yield, dividend pay-out ratio and board of directors’ size with ROA. .................. 85


dividend yield, dividend pay-out ratio and market capitalisation with share price volatility.

.............................................................................................................................................. 88


dividend yield, dividend pay-out ratio and market capitalisation with Tobin Q. ................ 91


dividend yield, dividend pay-out ratio and market capitalisation with ROA. ..................... 94


dividend yield, dividend pay-out ratio and industry type with share price volatility. ......... 97


dividend yield, dividend pay-out ratio and industry type with Tobin Q. ........................... 100


dividend yield, dividend pay-out ratio and industry type with ROA. ................................ 103


dividend yield, dividend pay-out ratio, industry type, board of directors’ size, market

capitalisation and debt ratio with share price volatility. .................................................... 106



capitalisation and debt ratio with Tobin Q. ........................................................................ 109



capitalisation and debt ratio with ROA. ............................................................................. 112

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Chapter One

1.0 Introduction

The dividend policy over decades remains a misleading and unresolved problem for

investors’ and managers’, the factors affecting the managers’ decisions on whether to pay or

re-invest the retained earnings and the consequences of these decisions on the performance of

the firms’. This research will examine some of the factors affecting dividend policy and the

performance of firms’ listed in the UK market.

1.1 Background

Defining dividend policy and factors affecting it has been a research topic for decades, but

yet it is considered one of the most challenging subjects in corporate finance. Black (1976)

described the dividend policy as a puzzle that is difficult to understand and also to solve.

Brealey & Myers listed dividend policy as one of ten major unsolved problems facing

financial analysts in the 21st century (Bhattacharyya, 2007). Dividend policy was defined by

Arnold (2008) as the percentage of profit paid to shareholders, usually periodically.

Although, firms can re-invest the retained earnings in projects that improve overall

performance which eventually maximise shareholders wealth in the long term, the question at

this point is why managers pay dividends? Especially that dividend is taxed at a higher rate

than capital gains. Based on the first theory in dividends established in (1961) by Miller &

Modigliani, a firm’s dividend policy is irrelevant to its value and shareholders wealth. Since

the irrelevant theory was established, many researchers and investors doubted the efficiency

of the assumptions used by Miller & Modigliani to establish the theory where they considered

that all investors act rationally, investors have perfect information about the firm’s strategies,

markets are perfect; no brokerage fees, no taxes or any other fees and managers act in the best

of shareholders interest.

However, in the real world the markets are not perfect, investors pay taxes and brokerage

fees, they do not have perfect information about the firm’s strategy or financial situation and

managers might make decisions in their own interest, but if dividend policy does not affect

firm value and it is taxable at a higher rate than capital gains then why do managers pay

dividends?. Following the Miller & Modigliani theory, researchers argued the factors

affecting managers’ decisions in paying dividend. D’Souza and Saxena (1999) argued that

sometimes managers keep secret information about the firm from the shareholders so they

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can use them for their personal interests and in other to create a balance, they pay dividends.

Fairchild (2010) asserted that managers pay dividends to send good and positive signals to

investors. Al-Malkawi (2007) postulated that managers pay dividends to attract investors who

prefer to reduce uncertain future risk by preferring dividend gain rather than capital gain.

Fama & French (2001) in their study on the US market concluded that firm’s profitability,

investment opportunities and size are the main effects on firm’s dividend policy. Al-Najjar &

Hussainey (2009) argued that firm’s capital structure have a big impact on managers

decisions on paying dividends. Bokpin (2011) suggested that the size of the board of directors

is directly related to the agency theory, and it will influence a manager’s decision to pay

dividends. Frankfurt & Wood (2002) argued that different industries have different

government regulations and competitiveness among them, which will affect the dividend

policy for firms within such industry. Baker et al (2001) in their study stressed that previous

pay-out ratios are the main effect on manager’s decision to decide the upcoming pay-out

ratio. Modigliani (1982) argued that inflation has a huge impact on stock returns and as such

recommended that inflation rates should be considered by managers to determine the firm’s

dividend policy. Bhattacharya (2007) in his model presented the effect of dividend

announcement on investors’ behaviour; he argued that since investors don’t have enough

access to information related to firm’s future strategy, they believe that dividend ratio reflects

the financial situation of the firm

1.2 Firm’s performance

Many researchers have attempted to study firm’s performance using different indicators,

some using accounting measures and others arguing that market values reflects more accurate

results. Wolfe & Sauaia (2003) discussed different types of total enterprise (TE) business

games which were developed to study firm’s performance. TE games focus on the

management decisions related to the main functions in firms; marketing, finance and

production. The Multinational Management Game was developed in 1997 by Keys while

Wells proposed that return on sales and debts to total assets are main indicators in measuring

firms’ performance. The Business Strategy and policy game were developed by Eldridge &

Bates in 1984. They found out that selling price, labours amount of generated hours and their

salaries affected firm’s earning per share, and share price. Damodaran (2002) described

market based value as indicators to firm’s performance. Total shareholders return considers

the change in stock price plus the dividend paid in specific period reflects how well the firm

performed in that period.

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Another indicator was Market Value Added, which deduct the amount of capital provided by

shareholders from the market value of shares in specific period. The change of market value

in a long period of time will be considered an evidence of firm’s performance. An additional

measure that was developed to deal with the limitations of total shareholders return and

market value added was the Excess return, which takes into consideration the time value of

money. Excess return is measured by deducting the expected future wealth in present value

from the actual wealth in present value. Arnold (2008) mentioned that financial ratios are

good source of information to analyse firm’s performance. He discussed that analysis can use

liquidity, assets turnover, financial leverage and profitability ratios to estimate the change in

firm’s performance. Other measures have been recommended to use. Fama (1991)

recommended the use of Tobin Q value as a market measurement because it is based on the

basis of efficient market hypothesis. He argued that it Tobin Q value is more reliable than

using accounting measures which have been questionable for its limitation. The Q value can

be calculated by adding the dividends to the market value of shares and divide them by total

assets. Chung & Pruitt (1994) claimed that Tobin Q can explain the phenomena of

diversification on investment decisions. Bharadwaj et al. (1991) suggested that the use of

Tobin Q over accounting measures because it’s a reliable indicator of firm’s intangible value,

while accounting measures rely on historical data that doesn’t reflect the current market

situation.

1.3 Aims and Objectives

The broad objective of this study is to clearly define and analyse the relationship between

firms’ dividend policy and their performance in the long-term using different accounting and

market measures; pay-out ratio and dividend yield as dividend policy measurements and

ROA, Tobin Q’s and share price volatility as firm performance measurement. To define the

relationship in the long term, the study aims to accomplish the following tasks;

Examine the relationship between dividend yield and ROA, Tobin Q’s and Share

price volatility and considering the impacts of the financial credit crisis on dividend

yield.

Examine the relationship between pay-out ratio and ROA, Tobin Q’s and share price

volatility as well as the impact of the financial credit crisis on dividend pay-out ratio.

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Identify the strongest factors affecting managers’ decisions on dividend policy and its

impact on the performance of the firm.

1.4 Research Questions

The research was guided to answer the following questions;

What is the relationship between firms’ dividend policy and its performance?

Did the financial credit crisis affect the relationship between firms’ dividend policy

and its performance?

What are the factors affecting the managers’ decision when setting firms’ dividend

policy?

1.5 Research Methodology

For the purpose of statistical analysis, the relationship between dividend policy and firm

performance and to cover this task, SPSS software will be used and more than twenty

regressions will be run and multiple linear regression is used no analyse the results. The

results will be based on the UK non-financial companies listed between 2005 and 2010. The

data will be collected using Bloomberg software and firms’ financial reports.

1.6 Research Lay-out

The research is divided into introduction, literature review, methodology, results and

conclusion. Chapter 2 covers the literature review which will discuss previous researches

which have analysed the relationship between dividend policy and firm performance using

different measurements. Chapter 3 will discuss the methodology used in this research which

include the variables used, the equations applied in the regression, the established hypothesis

and the descriptive analysis for the variables. Chapter 4 displays the results obtained from

SPSS software and the analysis using linear regression and the hypothesis testing. The next

and final chapter is the conclusions of the model will which provide a summary of the

analysis and hypothesis results.

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Chapter Two

2.0 Literature Review

This chapter will discuss previous theories and studies by various researchers on dividend

policy and firm performance and the factors affecting them.

2.1 Introduction

Dividend policy is a strategic decision made by the management of a firm with regards to the

use of earnings; either pay them as dividends to the shareholders versus reinvest the earnings

in the firm (Hussainy et al, 2011). While the first theoretical definition of dividend was

developed by Lintner (1956), the model by Miller & Modigliani in 1961 is considered the

classical research which proposed the irrelevance theory which assured that dividend policy

is irrelevant to firms’ value. Miller & Modigliani model results based on specific

consideration where investors won’t pay taxes or transaction cost, they can borrow and lend

at the same interest rate, and have access to all information about the firm’s future growth,

and where shareholders will be paid high dividends, and the firm can cover any paid out

earnings by issuing new shares (Arnold, 2008).

However, Black (1976) came up with the puzzle theory and no one argued it because in our

world, transaction cost and taxes exist, and firm’s dividend policy is affected by many

factors; sensitivity of earnings, cliental effect, government regulation, debt level, firm size

and many other factors (Al-Shabibi & Ramesh, 2011). On the other hand it has different

effects, while it sends mixed signals to investors, an increase in pay-out ratio is not necessary

good news, and a decrease in pay-out ratio might benefit the firm in the long-term. Dividend

policy is affected as well by the firm strategy, if the firm is in growth stage, low dividend is

expected. But even a firm in its maturity stage might prefer not to pay dividends and

managers will re-invest the earnings in the research and development department to gain a

competitive advantage or to invest in a positive net present value projects which either ways

will maximise shareholders wealth in the long-term (Grullon et al, 2002).

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2.1 Efficient Market Hypothesis and Stock price’s volatility

The main issue in corporate finance is the efficiency of the market. Several researches proved

the efficiency of the markets, and others argued that markets are inefficient. Fama (1970)

defined an efficient market as that which reflects all past information and reflects new

information immediately. He went further to prove this by dividing market efficiency into

weak, semi-strong and strong based on the effect of information on share price. Weak

efficiency market is where stock prices reflect all the past information, and will reflect any

new information directly. Semi-strong efficiency market is where stock prices reflect all the

available information, but some investors will take advantage of inside information. Strong

efficiency market states that stock prices reflect all the information weather its public or

inside information. Malkiel (2003) described the correlation between efficient market

hypothesis and the random walk idea. They both agree that stock prices reflect new

information immediately, for that tomorrow’s changes in stock prices will be based on today

news, it will be affected by tomorrow’s news.

On the contrary, Jensen & Meckling (1976) and Hussainy et al (2011) argued that markets are

inefficient due to the agency problem, where managers typically have more information than

shareholders which might affect the stock price in the short and long run. Further studies

were conducted to analyse the volatility of stock prices on daily basis. In 1981, Banz

questioned the validity of efficient market hypothesis when he observed an abnormal increase

in return for stocks in the US market in January of each year (Chatterjee and Maniam, 2011).

Other unusual volatility in stock prices was observed in the beginning of each month, after

holiday’s and after weekends which implies that stock prices get affected by news from

previous days (Thaler, 1987). But even if these anomalies exist, Malkiel (2003) believes that

it will lose its value as soon it is discovered by other investors, and the return that investors

will make is very small after deducting the transaction cost.

2.2 Dividend policy and Firm performance

Estimating an accurate measurement for firm’s performance that can be applied in different

sectors has been a difficult mission for analyst. In 1991, Wheatley, Amin, Maddox &

VanderLinde examined the Carnegie Tech Management Game, and they conclude that the

main indicator to firm performance is the volatility of return on assets (Wolfe & Sauaia,

2003). However, Fama (1991) argued that Tobin’s Q is the most reliable measurement for

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firm performance. Baker et al. (2001) used stock price as an indicator to firm performance.

They argued that managers’ pays close attention to the choice of dividend policy and pay-out

ratio in their firm. Their main concern is if they changed the dividend policy that will affect

the stock price, which will affect the firm value, and in return will affect the firm

performance. The effect of dividend policy in firms performance varies based on the

measure’s used as indicators for performance. Baskin (1989) model found a negative

relationship between dividend yield and dividend pay-out ratio and share price volatility.

Hussainey et al (2011) analysis ha similar result to Baskin’s model, they argued that dividend

pay-out ratio have a negative relationship with share price volatility. Allen and Rachim

(1996) results were found a significant negative relationship between dividend pay-out ratios

with share price volatility. DeAngelo et al. (2006) used return on assets as a firm performance

indicator and found a positive relationship between firms’ dividend policy and its

performance. Amidu (2007) studied the relationship between dividend policy and firm

performance using different measures. He found a significant positive relationship between

firm’s dividend policy and firm performance using return on assets as a measurement but the

relationship became negative when he used Tobin Q as a performance indicator. Murekefu

and Ouma (2012) model had similar results to Amidu and found a significant positive

relationship between dividend policy and firm performance.

2.3 Dividend policy changes and share price volatility.

At the beginning of corporate finance, dividend policy was the choice of firms to pay

earnings as cash dividend to its shareholders or reinvest retained earnings in the firm. The

major concern for managers is how much to pay as Dividend, should it be paid annually,

semi-annually or quarterly (Arnold, 2008).

With the progress of corporate finance over the years, dividend policy became a complex

issue; it has to deal with the type of dividend, should it be cash, or scrip dividends, or by

share buy-backs. Other than that, dealing with investor attitude toward risk, and to balance

between investors whom prefers capital gain, and investors whom prefers dividend earnings

(Arnold, 2008).

Lintner (1956) raised questions about the investors that managers should consider; should the

amount of dividend be reduced or increased? Or would they prefer a fixed rate dividends

being decided based on the earnings? The changes in stock prices will be used to analyse how

risky is the stock. The volatility of stock has to do with the historical closing and the amount

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of change in the prices. The higher the volatility the higher the changes in the stock price in

the short-run, which will make it difficult to predict the future stock price.

Investors react differently to the available or new information, they react based on their own

analysis, and this will have an impact on the stock market prices. Forsythe, Palfrey, & Plott

(1982) defined four hypothesis related to the share price with an assumption that investors

have a clear idea about their return in the future. The first hypothesis is the naïve hypothesis,

which emphasize that asset prices are irrelevant to the future pay-out. The second hypothesis

is the speculative equilibrium hypothesis, which relates the investor’s decision to their

expectation of other investor’s behaviour, without considering the actual payoff provided

from the asset. The third hypothesis is that assets prices are steadily related to the future pay-

out, it states that prices will be determine based on each individual expectation of the future

pay-out without considering the resale value for a third party. The fourth hypothesis is the

rational expectation hypothesis, which forecasts the prices based on the future pay-out plus

the resale price for the third party.

2.4 Theories of Dividend policy

Several studies have been developed discussing theories related to dividend policy such as,

Lintner (1956), Miller & Modigliani (1961), Black (1976), Bhattacharya (2007), Fama&

French (2001), Al-Malkawi (2007) and Al-Najjar & Hussainey (2009). These theories and

others related are discussed below;

2.4.1 Dividend Irrelevance Theory

Many past studies focused on the causes that affects managers to pay dividends, and if there

is a pay-out ratio that will maximise the shareholders wealth. Miller & Modigliani (1961)

argued that the dividend policy of a company will not affect the future firm value, and firms

are valued based on future cash flows generated from under taken investments. They assumed

in their argument that all investors have access to all the available information, they are not

obligated to pay a brokerage fees, and they do not pay taxes or any other additional costs.

Other assumptions that investors act rationally, they don’t differentiate between dividend and

capital gain to increase their wealth, and they all have enough information about the firms’

objectives and future growth.

Furthermore, Al Shabibi & Ramesh (2011) conducted that dividend policy is an important

decision which affects the firm’s in the long term, and it is affected by the firm cash flow

stability, the firm size, profitability, and the industry it performs in. Fama & French (2001)

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argued that the percentage of firm’s paying dividends clearly declined after 1978. They stated

that firm’s that pays dividend regularly will have a competitive disadvantage because their

high cost of equity compared to firms that do not pay dividends.

2.4.2 Agency Cost theory

According to Miller & Modigliani (1961) irrelevance theory, managers make their decisions

in order to maximise shareholders wealth. The assumption that managers work for the best of

shareholders have been questionable by new studies. Jensen & Meckling (1976) defined the

shareholders and managers relationship as a contract between them, where managers will be

responsible to take decisions that will achieve shareholders objectives. But shareholders

might question the manager’s decisions, and make sure that they do not act for their interest.

Agency cost will be the price that shareholders will pay if they have any conflict in interest

with the managers. Hussainy et al (2011) stated another possibility for agency cost, which is

the conflict between shareholders and bondholders, while shareholders seeks for higher

dividend payments, bondholders prefer lower dividend pay-out, to ensure a cash stability in

the firm to repay their debt.

Ross et al. (2008) argued that managers can eliminate the conflict between bondholders and

shareholders by paying dividend in stocks instead of regular cash payment which will keep

the excess cash in the firm. Easterbrook (1984) divided the agency cost to the cost of

monitoring the management, and the cost of risk on the management part. Monitoring

managers by hiring external auditors or increase the number of meetings between

shareholders and managers to try to reduce information asymmetry is consider additional cost

that should not be added. D’Souza and Saxena (1999) studied the relationship between

dividend policy and the agency cost, and found that there is a statistical significant negative

relation between them, and argued that firm should pay dividend in a regular basis to reduce

the agency cost. Al-Malkawi (2007) and Arnold (2008) agreed with D’Souza and Saxena

results and found that dividend is the best solution to reduce agency cost. Al-Najjar &

Hussainey (2009) in their model on UK firms suggested that paying dividend is a substitute

for firms with weak corporate governance.

In their working paper, Jiprapon et al. (2008) studied the effect of corporate governance on

dividend pay-out considering sixty two aspect of corporate governance. They found a

positive relationship between corporate governance and dividend pay-out. The better the

corporate governance in the firm, the higher the dividend pay-out. Fairchild (2010) in his

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model identified agency problems related to dividend policy. First if the manager reduced the

dividend amount to invest in a negative net present value investment to gain personal profit.

Second if the manager refuses to reduce dividend to invest in a positive net present value

investment, as a concern of sending bad signals about the firm income.

2.4.3 Signalling and Free cash flow theory

Signalling theory was a result of the asymmetric information between the management and

investors. It states that in an asymmetric environment, the dividend pay-out ratio will be an

important tool for investors to analyse the firm financial stability (Fairchild, 2010). The free

cash flow theory argues that agency cost will be reduced, if the management decided to pay

dividends instead of investing in new projects, because the investor main concern that

managers might invest in a negative present value projects for their own interest (Yoon &

Starks, 1995). The use of the available cash flow by the management sends direct signals to

the investors.

Michael and Mougoue (1991) model anticipated that firms will use cash dividend when they

make small pay out. For intermediate pay outs firms will use open market repurchase, where

they buy-back shareholders shares based on market value. For large pay outs firms will use

fixed price tender, where they offer to buy specific number of shares on specific price.

Although Miller & Modigliani (1961) assumed that management and investors have perfect

information about the firm, but previous researches showed that management will always

have more information more than the investors, even if it is for a short period of time. Petit

(1972) argued that dividend pay-out always carry great information to the investors. If

dividends pay-out ratio increase that will have a positive effect on the share price and vice

versa. Bhattacharyya (2007) stated that dividend announcements for companies are

considered important signals for investors and lot of analyses base their expectations on the

increase/decrease of the pay-out ratios, which raise questions on the irrelevance theory. Ross

et al. (2008) argues that manager’s decisions to increase pay-out ratio is a signal to investors

about the financial stability in the firm. Goddard et al (2006) analysis on the UK market

informed evidence supporting signalling theory, but in the same time they argued that the

relationship between dividend policy and share price volatility is too complicated and cannot

be explained by the signalling theory itself. Fairchild (2010) signalling model used the

dividend as a sign of the firm yearly income, and it affected the management decisions in

taking new projects. Dividend policy sends mixed and complicated signals to investors. If the

management decided to increase their dividend pay-out, investors might analyse that as a bad

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sign for future growth, although the reason might be the lack of opportunities to grow or an

increase in last year earnings. If the management decided to decrease their dividends pay-out

to invest in a positive net present value projects, investors might respond negatively, and

question the management decision if it is based on a personal profit, or for the sack of the

firm (Arnold, 2008).

2.4.4 Bird in the hand theory

Investors use different strategies to analyse the available information, and based on them they

react in different ways based on the level of risk. Bird in hand theory asserts that investors

prefer stocks that pay high dividends to reduce risk, “A bird in hand (dividend) is worth more

than two in the bush (capital gains)” (Al-Malkawi, 2007). Investors are divided based on the

level of risk they are willing to take to risk adverse, risk neutral, and risk takers. Most

investor are identified as a risk averse, and for that Al-Malkawi’s theory was supported by

Lintner (1962) with the assumptions that investors are not provided with all the information

about the firm profitability, the dividends gain are taxed in a higher level than capital gain,

and dividends are used as a signal for the firm profitability. Arnold (2008) stated that

investors attitude toward risk encourage them to invest in firms with high dividend pay-out

ratio. Although dividends gain have a tax disadvantage but yet managers keep paying it to

send positive signals to investors who fear the future uncertainty (Hussaine et al. 2011) With

the investors nature to be risk adverse Ross et al. (2008) recommended firms that pays high

dividends to use share repurchase as a dividend policy instead of cash to reduce the amount

of tax on investors gain. On the other hand Easterbrook (1984) against the bird in the hand

theory. His argument was based on the ability of investors’ to sell the shares at any time

instead of waiting for dividends and that will reduce the amount of tax paid as well.

2.4.5 Cliental effects theory

Investors have different strategies in maximising their profits by using specific stocks. Each

investor will prefer stocks that satisfy his needs. Some investors apply bird in hand theory,

and they prefer stocks that pays high dividend, other investors might prefer stocks that do not

pay dividends for taxes reasons. Al-Malkawi (2007) proposed that firms in their growth stage

will pay low dividend to finance their projects, on the other hand, firms in their maturity stage

will pay high dividend. Miller & Modigliani (1961) stated that any investor is as good as

another, so if investors wish to minimise their income taxes they should invest in companies

with low dividends, and investor’s with a dividend gain preference should invest in firms that

pay high dividends, which make dividend policy irrelevance to the firm value. But

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Bhattacharyya (2007) argued that Miller and Modigliani model failed to explain why

companies and investors are affected by dividend announcements. Bhattacharyya believes

that dividend announcement have some interested information that Miller and Modigliani

model failed to notice it because of the distraction in their assumptions. Goddard et al (2006)

have argued that firm’s dividend policy decisions considers the needs of specific groups of

investors, and firms will assure that their dividend policy will suit these investors. Al-

Malkawi (2007) categorised cliental effects into two groups, first group are investors who are

driven by taxes, and the second group are investors who are driven by transaction cost. The

group who’s affected by taxes can invest in low dividend companies, and the group who’s

affected by transaction cost are usually small investors who prefer companies with high

dividend pay-out, to minimise transaction cost. Miller & Scholes (1982) reduced the effect of

taxes on investors. They argued that investors can reduce the deducted taxes on their dividend

earnings, by increasing the debt ratio in the portfolio, which will lead to an increase in the

interest paid, that will reduce the earnings before taxes, and therefore reduce the amount of

tax paid.

2.5 Debt Ratio effect on firms’ dividend policy and performance.

Debt ratio is the percentage of external funds to shareholders funds (Arnold, 2008). The

determination of capital structure in UK was considered by Niu (2008) who argued that large

firms with high tangible assets or high taxable rate tend to have high leverage. But firms with

growth opportunities, or firms with high liquidity, or with volatile earnings tend to have low

leverage. Although Miller & Modigliani (1961) theory proposed that the percentage of debt

and equity in the capital structure is irrelevant to firms value, researches argued that debt

level have an impact on dividend policy. Baker and Powell (2000) argued that firm’s capital

structure is affected by the type of industry. Their results showed that utility sectors maintain

different capital structure than firms in the retail sector. Arnold (2008) recommended firms to

have a high debt in their capital structure. His assumption was based on the lower cost of debt

compared to the cost of equity. He assumed that a firm with high debt have a trade-off

between interest expenses and the amount of tax paid, which will increase shareholders

wealth. On the other hand Al-Najjar & Hussainey (2009) argued that one of the main

conflicts between shareholders and managers is the debt ratio, because firms with high debt

have a higher risk of facing difficulties in meeting their future obligation, which will send

negative signals to investors. Their study showed a negative relationship between debt ratio

and dividend policy, the lower the debt ratio, the higher the dividend pay-out. Al-Shabibi &

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Ramesh (2011) study on the UK market argued that debt level and dividend policy are not

correlated. Al- Hussainey et al. (2011) studied the effect of debt level on share prices. There

results showed that the higher the debt level, the higher the volatility in stock prices. Allen

and Rachim (1996) argued that debt ratio have a significant positive relationship with share

price volatility. Saeedi and Mahmoodi (2011) found a negative relationship between debt

ratio and ROA but a positive relationship between debt ratio and Tobin Q.

2.6 Board directors’ size effect on firms’ dividend policy and performance.

Board size represents the number of members, executive and none executive in the firm. The

relationship between board of directors’ and dividend policy has been examined by limited

studies. Would the size of board affect the management decisions to pay dividend or is it

irrelevant. Bathala & Rao (1995) in their study on 261 US firms in 1981 found a negative

relationship between the size of board directors’ and dividend policy. They considered the

dividend pay-out is not related to the size of board as much as it is an efficient way to reduce

agency cost. Another study by Borokhovich el al. (2005) examined the relation between

dividend policy and board directors’ size on 192 US firms. Their results were similar to

Bathala & Rao (1995) findings. They suggested that firms with high number of directors’ in

board tend to pay low dividends. Al-Shabibi & Ramesh 2011 study on the UK market found

a non-significant relationship between board size and firms’ dividend policy. On the other

hand Schellengeret al. (1989) found a positive correlation between board size and dividend

policy. Their results were based on a sample on 525 US firms in 1986. They conclude that a

firm board directors’ structure effects dividend policy. In addition a study of 160 US by

Kapalan and Reishus (1990) had the same results. They argued that managers’ decisions in

dividend policy are affected by the number of board directors’. (Belden, Fister and Knapp,

2005), (Al-Najjar & Hussainey (2009) and Bokpin (2011) had similar results; they suggested

a positive relationship between the size of board directors’ and dividend policy. On the other

hand Barnhart and Rosenstein (1998) found a negative relationship between board of

directors’ size and the firm performance. Guest (2009) study on the companies listed in the

UK market found a negative relationship between board of directors’ size and Tobin Q.

Topak (2011) findings from the Turkish market suggested a non-significant relationship

between board of directors’ size and firm performance.

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2.7 Industry type effect on firms’ dividend policy and performance.

This identifies the sector where the company operate. Different sectors have different

competitive level, different environmental changes, and different government regulations.

Fama (1974) found that companies in different industries follow different government

regulations which affect their investment decision. Baker and Powell (2000) studied the

relationship between dividend policy and industry type using a survey in 1997 for NYSE

listed US firms. They found a strong relationship between the type of industry and dividend

policy. Based on Baker & Powell results they argue that utility sector tend to pay more

dividend than manufacturing and retail sector. Frankfurter & Wood (2002) had similar

results, they stated that the competitive level is different among the industries, and it affects

the management decision toward dividend policy. Van Caneghem & Aerts (2011) supported

Baker & Powell results. In their study of a large sample on US firms, they found a significant

relationship between dividend policy and industry type. Their argument was based on the

volatility of mean return for the industry, which affects firm’s dividend policy. But Al-

Shabibi & Ramesh analysis on the UK market argues that firm’s dividend policy is not

affected by their industry type. Hussainey et al. (2011) results suggested a non-significant

relationship between industry type and share price volatility.

2.8 Firm size effect on firms’ dividend policy and performance.

Firms can be categorised based on their size. Market capitalization, total assets, profitability

and other measures can be indicators to firm size. The effect of firm size on dividend policy

is associated with the agency cost, and free cash flow theory. Al-Najjar & Al-hussainey

(2009) model found a positive relation between dividend policy and firms size. Holder et al.

(1998) had the same results. They argued that firms in their maturity stage have easier access

to capital market, which will make them able to pay high dividend. Ho (2003) study on

Australian and Japanese market found a positive relation between firm size and dividend

policy. On the other hand Smith and Watts (1992) stated that the theoretical foundation for

the relationship between firm size and dividend policy is not strong. He suggested a negative

relationship between dividend policy and firm size. Keim (1985) had close results to Smith &

Watts. He argued that dividend policy have a significant negative relationship with the firm

size. Recent studies on the UK market by Al-Shabibi & Ramesh (2011) and Al-Najjar and

Hussainey (2009). Hussainey et al. (2011) studied the relationship between firm size and its

performance using share price volatility as an indicator of performance. There results showed

a significant negative relationship between firm size and share price volatility. Allen and

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Rachim (1996) argued that small firms are subject to greater share price volatility since it is

expected to be less diversified than large firms’. Saeedi and Mahmoodi (2011) found a

positive relationship between firm size and firm performance when using earning per share as

an indicator, but the relationship became negative when they used Tobin Q as a performance

indicator.

2.9 Historical Pay-out Ratio effect on firms’ dividend policy and performance.

Firm’s pay-out ratio is the amount of earnings paid to shareholders as dividends. Baker et al.

(2001) study on U.S companies found that one of the most factors affecting firm’s dividend

policy is the volatility of historical payments. Al-Shabibi & Rmesh (2011) found a significant

positive relationship between dividend policy and historical pay-out ratio. They argued that

reducing pay-out ratio will send bad signals to investors even if the firm is planning to use the

cash to take a positive net present value projects. Hussainey et al. (2011) analysis on the UK

market found a positive correlation between pay-out ratio and firm’s performance. Pay-out

ratio is a sensitive issue for managers, because changing it will have a big impact on the firm.

It has been mention earlier in the literature review the sensitivity of pay-out ratio to the

company’s future, and satisfying investor’s needs. Easterbrook (1984) argued that a stable

dividend policy will affect the share price positively.

2.10 Summary

The aim of this chapter was discussing previous researches and findings about the

relationship between firms’ dividend policy and its performance. The findings of previous

researches were based on the measures used as indicators form dividend policy and firm

performance. Murekefu & Ouma (2012) model showed a positive relationship between firms’

dividend policy and its performance. DeAngelo et al. (2006) and Amidu (2007) used return

on assets as a performance indicator and found a positive relationship between dividend

policy and firm performance. On the other hand Hussainey et al. (2011) and Allen and

Rachim (1996) models used share price volatility as a performance indicator, they found a

significant negative relationship between dividend pay-out ratio and share price volatility. For

dividend yield, Rachim Hussainey et al. (2011) study showed a positive relationship between

dividend yield and share price volatility. Baskin (1989) and Amidu (2007) models showed a

negative relationship between firms’ dividend policy and its performance using share price

volatility and Tobin Q respectively as a performance indicator.

The control variables’ recommended by Baskin (1989) had different effects on firms’

dividend policy and its performance based on the measurement used. Al-Najjar and

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Hussainey (2009) found a positive relationship between firms’ dividend policy and their debt

ratio. Al-Shabibi and Ramesh (2011) results were inconsistent to Al-Najjar and Hussainey

findings, they found that debt ratio have a non-significant relationship with firms’ dividend

policy. Saeedi and Mahmoodi (2011) measured the effect of debt ratio on firm performance

using different indicators. They found a positive relationship between debt ratio and firm

performance using ROA as an indicator, but a negative relationship when using Tobin Q as a

performance measurement.

The board of directors’ size have a positive relationship with dividend policy based on Al-

Najjar and Hussainey (2009) and Bokpin (2011). On the other hand Borokhovich el al. (2005)

analysis showed a negative relationship between board size and dividend policy. Guest

(2009) study found a negative relationship between board of directors’ size and Tobin Q. But

Topak (2011) suggested a non-significant relationship between board of directors’ size and

firm performance on his study.

The firm size was suggested to have a positive relationship with dividend policy based on Al

Shabibi & Ramesh (2011). Hussainey et al. (2011) study showed a significant negative

relationship between firm size and its performance using share price volatility as an indicator.

Saeedi and Mahmoodi (2011) results suggested a negative relationship between firm size and

Tobin Q.

Baker and Powell (2000) found a significant effect of firms’ industry on its dividend policy.

Al-Shabibi and Ramesh (2011) had inconsistent result to Baker and Powell findings. They

suggested a non-significant relationship between firms’ dividend policy and the industry they

follow. Hussainey et al. (2011) results suggested a positive relationship between dividend

yield and share price volatility.

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Chapter Three

3.0 Methodology

3.1 Introduction

This chapter provide a description of the applied methodology to achieve the objectives of

this research. The chapter presents the target population and the data collection, the variables

measures, research equations, variables definition, research hypothesis and data analysis.

3.2 Techniques and sources of data collection

The primary aim of this study is to examine the link between dividend policy and firm

performance in the UK market. The relationship between dividend policy and firm

performance has been examined using Statistical Package for Social Sciences (SPSS) on non-

financial companies that maintained its presence in FTSE 250 for six years consecutively

between 2005 and 2010. However, only 89 out of 250 companies maintained their existence

in the market within this period, this might be considered not adequate to present the whole

companies listed in FTSE 250. To avoid this limitation, the criteria were adjusted to include

more companies. The matching companies listed in FTSE all shares UK index from 2005 to

2010 were included. This criterion provided 283 companies to be tested using SPSS and

multiple least square regressions to analyse the data over the six year period. The financial

companies were excluded because of the different rules and regulations applied in financial

sectors which affect its capital structure.

3.3 Dividend policy measures

The elect of measurement used for dividend policy and firm performance were based on the

recommendation and the usage of them by previous researchers in different models. Dividend

policy can be measured by; changes in historical pay-out ratio, dividend per share, and

dividend yield. Hussainey, Chijoke-Mgbame & Magbame (2011) in their model analysed the

relationship between dividend policy and firm performance in the UK market using dividend

yield and pay-out ratio as dividend policy measurement. Also, Allen and Rachim (1996) in

their model measured firm’s dividend policy in Australian market using dividend yield. In

their model in 2009, Al-Najjar and Hussainey measured dividend policy by using dividend

yield as well. Dobbins and Witt (1993), Lintner (1956) and Jensen (1986) recommended

Page | 18

dividend yield and pay-out ratio as accurate measures to firm’s dividend policy as they reveal

the percentage change in dividend and they consider the changes in share prices. For these

recommendations both dividend yield and pay-out ratio are used as dependent variables to

measure firm’s dividend policy in the model.

3.4 Firm performance measures

Different measurements can be used as indicators to firm’s performance. Forbes (2002)

argued that firm’s performance can be measured by the changes in net income, sales, market

capitalisation and assets. Firm’s performance can vary based on the value sources, if it is

based on book values or market values. Accounting ratios; profit, sales, return on equity,

return on assets and other ratios available in firm’s annual reports can be used to measure

firm’s performance. Measures which considers market and book values; market value added,

economic value added, Tobin’s Q and others which could be calculated can be considered

more reliable than accounting ratios. Other measure, volatility in share price which is

considered a market value indicator can be used as well. But with the limitation of accounting

measures mentioned by Arnold (2008) and Bowhill (2008) which assumes that accounting

measures are not reliable because they reflect past performance and does not consider the

future, they need to be adjusted to market values and it ignores the effect on intangible assets

on firm’s performance, Tobin’s Q and share price volatility are used in this model with the

return on assets as independent variables to reflect firm’s performance.

Baskin (1989), Hussainey, Chijoke-Mgbame & Magbame (2011) and Allen andRachim

(2010) models used share price volatility as firm’s performance. They argued that share price

reflects the financial and non-financial information’s, the company’s future strategy is

reflected on share price and it is consider a key performance to investor’s. Feltham & Xie

(1994) and Paul (1992) recommended the use of share price as a firm performance indicator

as it provides more accurate results than other methods. For these reasons share price

volatility was considered a firm performance indicators in the model. The third dependent

variable Tobin’s Q was used based on the agreement of previous researches as it is one of the

main measures of firm’s performance. Fama (1991) argued that Tobin’s Q perfectly

addresses accounting measures limitations and it is based on the foundation of the efficient

market hypothesis. Hall (1993) stated that the efficiency of Tobin’s Q comes from the

consideration of firms tangible and intangible assets. Chung and Pruitt (1994) preference of

Page | 19

Tobin’s Q over other measurements was because it employ the relationship between equity

ownership and firm value.

3.5 Research control variables.

Taking Baskin (1989) recommendation of analysing other factors affecting dividend policy or

firm performance, other control variables were added to the model; debt ratio, firm size, pay-

out ratio, board of directors’ size and industry type. The source of data in this research is

purely secondary data collected from Bloomberg, firm’s annual reports and London Stock

Exchange website. The independent variable dividend policy was measured using pay-out

ratio and dividend yield. The dependent variable firm performance was measure using

Tobin’s Q, return on assets and share price volatility.

3.6 Research equations

In this model the three dependent variables (stock price volatility, Tobin’s Q and ROA) are

regressed to the two independent variables (dividend yield and pay-out ratio), the differences

in results are discussed in the analysis.

Each dependent variable will be regressed to the independent variables with the following

regression equations;

𝑆ℎ𝑎𝑟𝑒 𝑃𝑟𝑖𝑐𝑒 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦 = 𝐶 + 𝑎1 + 𝑎2 (1)

𝑇𝑜𝑏𝑖𝑛’𝑠 𝑄 = 𝐶 + 𝑎1 + 𝑎2 (2)

𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑛 𝑎𝑠𝑠𝑒𝑡𝑠 = 𝐶 + 𝑎1 + 𝑎2 (3)

Where,

“C” represents the intercept.

“a1” represents pay-out ratio.

“a2” represents dividend yield.

The results represent a simple test to the relationship between firm performance and dividend

policy using different indicators.

With all the factors affecting dividend yield and dividend pay-out ratio the results of the

equations above may not be accurate. For that the control variables mentioned earlier were

added as independent variables. Control variables have been added separately to each

equation to analyse its effect on dividend policy and firm performance, then all the control

variables were added together to consider its effect on dividend policy and firm performance.

𝑆𝑡𝑜𝑐𝑘 𝑝𝑟𝑖𝑐𝑒 𝑣𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦 =

Page | 20

𝐶 + 𝑎1 + 𝑎2 + 𝑎3 + 𝑎4 + 𝑎5 + 𝑎6 + 𝑎7 + 𝑒 (4)

𝑇𝑜𝑏𝑖𝑛’𝑠 𝑄 = 𝐶 + 𝑎1 + 𝑎2 + 𝑎3 + 𝑎4 + 𝑎5 + 𝑎6 + 𝑎7 + 𝑒 (5)

𝑅𝑒𝑡𝑢𝑟𝑛 𝑜𝑛 𝑎𝑠𝑠𝑒𝑡𝑠 =

𝐶 + 𝑎1 + 𝑎2 + 𝑎3 + 𝑎4 + 𝑎5 + 𝑎6 + 𝑎7 + 𝑒 (6)

Where,

“a3” represents Debt ratio.

“a4” represents Firm size.

“a5” represent Board directors’ size.

“a6” represents Historical pay-out ratio.

“a7” represents Industry type.

‘’e’’ represent the error.

The analysis of the equations (4), (5) and (6) will represent more accurate understanding

about the relationship between dividend policy and firm performance. The equations above

were applied on the 283 firms and the results discussed the effect of dividend policy on firm’s

performance each year separately, and the variations of the results are analysed later on this

chapter. The regression model has been used to analyse the results. Where,

R squared (R2); will be a measure of the accuracy of the model predictions. It determines how

well the model fits the data. A value of 1 means that the predictions are fully accurate (The

deviations of independent variables are explained). A value of 0 will indicate that the results

are not reliable and the independent variables should be overlooked. R square efficiency has

been questioned when the number of independent variables is high and for not considering

the sampling errors. Since the adjusted R square is covers these issues it has been used in this

model.

T-statistic; will be an indicator for the relationship between the dependent and independent

variable. It is calculated by dividing the coefficient value from the standard error. A high

value of T-statistic indicates a strong correlation between the independent and dependent

variables vice versa. The T-statistic can be statistically significant at 10%, 5% or 1%.

Beta; it is used to as a weight indicator for the independent variables. The independent

variable with the highest beta value is considered the most affective variable on the

dependent.

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3.7 Definition of research variables

3.7.1 Debt ratio

Debt ratio is the proportion of debt to equity is calculated by dividing total debt to total

equity, following Al-Najjar & Hussainey, (2009). The figures were directly obtained from

Bloomberg, and firm’s annual reports.

3.7.2 Firm size

Firm size can be measured by total assets, market capitalisation and number of employees. In

this model market capitalisation was used for the preference of using a market value

measurement and following Hussainey at el. (2011). The figures of closing prices and

number of shares outstanding represent the last day of trading at the end of the firm financial

year. The figures were directly obtained from Bloomberg, and firm’s annual reports.

3.7.3 Board of directors’ size

Board sizes represent the number of directors’ in the boards of each firm, following Bathala

& Rao, (1995). The figures were directly obtained from firm’s annual reports and Bloomberg.

3.7.5 Pay-out ratio

The ratio used is the dividend per share divided by earning per share. Following Hussainey et

al (2011). The figures were directly obtained from Bloomberg, and firm’s annual reports.

3.7.6 Industry type

Firms were divided according to their sectors. Following Al-Shabibi and Ramesh (2011).

Bloomberg Industry Classification (BICS) were used which classify the companies into nine

groups; Utilities, Technology, Industrial, Energy, Diversified, Consumer non-cyclical,

Consumer cyclical, Communications and Basic materials.

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3.7.7 Dividend yield

Dividend yield is expressed as the dividend per share divided by earning per share. Following

Malkawi & Al-Najjar (2010).The figures were directly obtained from Bloomberg, and firm’s

annual reports.

3.7.8 Share price volatility

It measures the volatility of changes in stock prices. Following Allen and Rachim (1996) and

Hussainey et al (2011). 360 days price volatility measures the daily changes on share prices

over a year. The figures were obtained directly from Bloomberg.

3.7.9 Tobin’s Q

It was recommended by Fama (2001) as the most accurate measure for firm performance.

The following equation was used to calculate Tobin’s Q values;

(MVS + D) / TA. Where: MVS is the market value of shares based on the last trading day at

the end of the financial year to each firm, TA is the firms’ total assets and D is the firm’s total

debt. It is calculated by deducting the accounting value of the firm’s current liabilities form

the accounting value of the firm’s current assets and then adding the accounting value of the

firm’s long term debt. The figures were directly obtained from Bloomberg.

3.7.10 Return on assets

It is calculated by dividing firm’s Net Income from its Total Assets. Following Wolf,

(2003).The figures were directly obtained from Bloomberg and firm’s annual reports.

3.8 Research Hypothesis

Hypothesis One;

H0 (Null Hypothesis): There is a negative relationship between dividend yield and firms’

share price volatility.

H1 (Alternative Hypothesis): There is a positive relationship between dividend yield and

firms’ share price volatility.

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Hypothesis Two;

H0 (Null Hypothesis): There is a negative relationship between dividend pay-out ratio and


H1 (Alternative Hypothesis): There is a positive relationship between dividend pay-out and


Hypothesis Three;

H0 (Null Hypothesis): There is a negative relationship between dividend yield and firms

Tobin Q.


firms Tobin Q.

Hypothesis Four;


firms Tobin Q.


firms Tobin Q.

Hypothesis Five;

H0 (Null Hypothesis): There is a negative relationship between dividend yield and firms ROA


firms ROA

Hypothesis Six;


firms ROA


firms ROA

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Chapter Four

4.0 Introduction

This chapter will describe the summary statistics of the variables used in the model and

analyse the regression results from SPSS software. It shows the changes in the statistical

mean and standard deviation for each variable in every yea followed by the regression and

hypothesis results.

4.1 Data Descriptive Analysis

Chart (1) shows the changes in the Mean and Standard Deviation for debt ratio. It shows that

in 2006 the Mean for debt ratio increased by 16% comparing to 2005, see table (1) in

appendix (1). The debt ratio continued to increase in 2007 before it decreased slightly in 2008

and it increased again in 2009 to its peek before it decreased in 2010. Fosberg (2012) stated

that the increase in debt ratio in firm’s capital structure between 2006 and 2010 was a result

from the financial crisis. He argued that many firm’s used external debt to save them from

bankruptcy.

The Standard Deviation for this sample is considered to be high, which indicate that most of

the firm’s debt ratio are spread around the mean of the index, but it is normal for the debt

ratio variable to have a high standard deviation, since firm’s have different preferences about

the amount of debt in their capital structure.

Chart (1): Debt ratio descriptive analysis

0

100

200

300

400

500

600

DebtRatio 05

DebtRatio 06

DebtRatio 07

DebtRatio 08

DebtRatio 09

DebtRatio 10

Mean

Std. Deviation

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Chart (2) shows the changes in the Mean and Standard Deviation for firm's dividend yield.

Between the periods of 2005 to 2010, dividend yield Mean moved in a similar pattern. But it

increased significantly in 2008 by 54% comparing to 2007, see table (2) in appendix (1). In

2008 the financial crisis effect reached the peek and firms preferred to pay dividends rather

than re-investing the retained earnings. In this sample the Standard Deviation is low, which

indicates that firms dividend yield ratio is close to the mean of the index.

Chart (2): Dividend yield descriptive analysis

Chart (3) shows the changes in the Mean and Standard Deviation for firm’s market

capitalisation. The mean shows a 7.2% increase in 2006 comparing to 2005 and a 13.9%

increase in 2007. In 2008 firm’s market capitalisation was affected by the financial crisis and

decreased by 20%, see table (3) in appendix (1). Fosberg (2012) related this reduction to

firm’s strategy in facing the crisis by increasing their debts and decreasing the amount of

shares outstanding. Standard Deviation figures are relatively high but stable. Which indicate

that firms’ market capitalisation vary between companies and it is spread around the index

mean.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

DividendYield 05

DividendYield 06

DividendYield 07

DividendYield 08

DividendYield 09

DividendYield 10

Mean

Std. Deviation

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Chart (3): Market Capitalisation descriptive analysis

Chart (4) shows the changes in the Mean and Standard Deviation for firm’s Return on Assets.

The table shows an increase in the Mean for ROA between 2006 and 2007. In 2008 and 2009

the effect of financial crisis decreased firm’s ROA before it recovers and increased again in

2010. The standard deviation for the period is considered to be low and stable, which

indicates that firm’s ROA are close to the industry mean and the decrease in the mean during

the financial crisis affected the entire firms. See table (4) in appendix (1).

Chart (4): Return on assets descriptive analysis

0

2000

4000

6000

8000

10000

12000

14000

16000

MarketCap. 05

MarketCap. 06

MarketCap. 07

MarketCap. 08

MarketCap. 09

MarketCap. 10

Mean

Std. Deviation

0

2

4

6

8

10

12

ROA 05 ROA 06 ROA 07 ROA 08 ROA 09 ROA 10

Mean

Std. Deviation

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Chart (5) shows the changes in the Mean and Standard Deviation for firm’s Tobin Q’s. It

shows that the Mean of firm’s performance increased by 8% in 2006 but it was affected by

the financial crisis in 2007 to 2009 and had significantly decreased before it recovers in 2010.

The Standard Deviation for Tobin Q’s was low in that period as well and was affected by the

changes in the Mean, which indicates that firm’s performance was strongly affected by the

financial crisis. See table (5) in appendix (1).

Chart (5): Tobin Q’s descriptive analysis

Chart (6) shows the changes in the Mean and Standard Deviation for firm’s pay-out ratio. The

volatility of the Mean can be regressed to the changes in pay-out strategy of the firms. In

2006 the mean increased by 51% before it decrease by 31% in 2007 as a reaction of the

financial crisis. When the financial crisis was at its peak in 2008, firm’s decided to increase

their pay-out ratios, which lead the Mean to increase by 67% comparing to 2007, see table (6)

in appendix (1). When the market started to recover from the financial crisis, firm’s decreased

the pay-out ratio and that is shown in the table, where the Mean decreased in 2009 and 2010.

The Standard Deviation in this sample is high and volatile, which indicates that firm’s pay-

out ratios are spread around the Mean and the firm’s had different strategies in paying out to

face the financial crisis.

0

0.5

1

1.5

2

2.5

Tobin Q’s 05

Tobin Q’s 06

Tobin Q’s 07

Tobin Q’s 08

Tobin Q’s 09

Tobin Q’s 10

Mean

Std. Deviation

Page | 28

Chart (6): Pay-out ratio descriptive analysis

Chart (7) shows the changes in the Mean and Standard Deviation for the stocks volatility.

The changes in the Mean were stable in 2005 to 2007 until it had a significant increase by

55% in 2008 and 25% in 2009 due to the financial crisis, before it decline in 2010 by 29%,

see table (7) in appendix (1). The Standard Deviation in this sample considered to be low in

the first three years before it increases by 79% in 2008 and 25% in 2009 due to the effect of

financial crisis on the stock prices, which lead them to be diffused around the mean.

Chart (7): 360 days share price volatility

0

100

200

300

400

500

600

700

800

Pay-OutRatio 05

Pay-OutRatio 06

Pay-OutRatio 07

Pay-OutRatio 08

Pay-OutRatio 09

Pay-OutRatio 10

Mean

Std. Deviation

0

10

20

30

40

50

60

70

Volatility05

Volatility06

Volatility07

Volatility08

Volatility09

Volatility10

Mean

Std. Deviation

Page | 29

4.2 Regression results

This part will analyse the regression results for the six equations to test the hypothesis

mentioned in chapter 3. If the t-static values are positive, the hypothesis will remain as

specified. But if the t-statistic values are negative the null hypothesis (N0) will be rejected

and the alternative hypothesis (N1) will be accepted. Tables 1-18 show the output of the

linear regression which was run using SPSS software.

Table (1) shows the result of the first equation. Figures are obtained from appendix (2). It

indicates that dividend yield have a significant negative relationship with share price

volatility before and after the financial credit crises. This is consistent with Baskin (1989) and

inconsistent with Hussainey et al. (2011) findings. Including the crisis period in this model

could be the reason for the inconsistent in the model results with Hussainey et al. findings.

On the other hand Pay-out ratio had no significant relationship with share price volatility

between 2005 and 2007. But between 2008 and 2010 and on an average between 2005 to

2010 it shows that pay-out ratio have a negative relationship with share price volatility. This

is inconsistent with Hussainey et al. (2011). Including the crisis period in this model could be

the reason for the inconsistent in the model results with Hussainey et al. findings.

Beta figures shows that the negative effect of dividend yield is higher than the positive effect

of pay-out ratio on share price volatility. Adjusted R square shows that dividend yield and

pay-out ratio effect had declined by about 40%.On average between 2005 and 2010, dividend

yield and pay-out ratio affected share price volatility by about 7%.

Beta t-statistic Sig.

Dividend Yield Avg. 05-07 -0.391 -6.853 0

Pay-Out Ratio Avg. 05-07 0.023 0.379 0.692

Dividend Yield Avg. 08-10 -0.135 -2.154 0.032

Pay-Out Ratio Avg. 08-10 -0.086 -1.379 0.169


Pay-Out Ratio Avg. 05-10 0.088 -1.432 0.153

2005-2007 2008-2010 2005-2010

Adjusted R Square 0.0413 0.026 0.069

Table 1: The association between share price volatility, dividend yield and pay-out ratio.

Page | 30

Table (2) shows the results of the second equation. Figures are obtained from appendix (3). It

shows that dividend yield have a significant negative relationship with Tobin Q prior and

after the crisis and in the long-term. Pay-out ratios have a positive relationship with Tobin

Q’s in the short term (before and after the crisis) and a significant positive relationship with

Tobin Q’s at 10% in the long term between 2005 and 2010. This is contrary to Amidu (2007)

model findings that suggested a negative relationship between firms’ dividend policy and its

Tobin Q ratio. Amidu findings were based on the Ghana market, which is considered an

emerging market comparing to the UK and this could be an explanation of the differences in

the findings.

Beta figures shows that the negative effect of dividend yield is higher than the positive effect

of pay-out ratio on share price volatility. Adjusted R shows that pay-out ratio and dividend

yield effect on Tobin Q values increased by 1% after the financial crisis. On average between

2005 and 2010, dividend yield and pay-out ratio affected ROA by about 6%.



Pay-Out Ratio Avg. 05-07 0.041 0.67 0.503


Pay-Out Ratio Avg. 08-10 0.053 0.853 0.395


Pay-Out Ratio Avg. 05-10 0.1 1.622 0.106

2005-2007 2008-2010 2005-2010


Table 2: The association between Tobin Q’s, dividend yield and dividend pay-out ratio.

Table (3) shows the results of the third equation. Figures are obtained from appendix (4). It

indicates that dividend yield had a significant positive relationship with ROA in the short

term and insignificant positive relationship in the long term. On the other hand pay-out ratio

had a non-significant relationship with ROA before the crisis, after the crisis the relationship

became insignificantly negative. But in the long term it has an insignificant positive

relationship with ROA. This is consistent with DeAngelo et al. (2006) and Amidu (2007)

findings.

Page | 31

Beta values show that dividend yield had more effect on ROA than pay-out ratio. Adjusted R

figures show that dividend yield and pay-out ratio effect on ROA declined by more than 50%.

On average between 2005 and 2010 dividend yield and pay-out ratio affected ROA by 1%.


Dividend Yield Avg. 05-07 0.151 2.47 0.014

Pay-Out Ratio Avg. 05-07 0.005 -0.083 0.934


Pay-Out Ratio Avg. 08-10 -0.036 -0.571 0.569


Pay-Out Ratio Avg. 05-10 0.049 0.775 0.439

2005-2007 2008-2010 2005-2010


Table 3: The association between ROA, dividend yield and dividend pay-out ratio.

Table (4) shows the results for the first equation after adding the debt ratio as control variable

and holding others constant. Figures are obtained from appendix (5). Dividend yield results

were not affected by debt ratio and continue to shows a significant negative relationship with


Pay-out ratio results were affected by debt ratio only before the crisis and show a positive

relationship with share price volatility after it was non-significant. But there was no effect of

debt ratio on the results after the crisis and in the long term, it continues to show a negative

relationship with share price volatility after the financial crisis and on an average between

2005 and 2010.

The control variable debt ratio had more effect on share price volatility before the financial

crisis with a negative relationship, after the financial crisis debt ratio appears to have a non-

significant relationship with price volatility. In the long term, debt ratio has an insignificant

negative relationship with price volatility.

Beta values shows that all the variables have negative effect on share price volatility, the

strongest effect is from dividend yield, then pay-out ratio and then debt ratio. Adjusted R

shows that the effect of the variables on price volatility decreased after the financial crisis by

more than 100%. On average the variables influenced price volatility between 2005 and 2010

by about 7%.

Page | 32



Pay-Out Ratio Avg. 05-07 0.062 0.896 0.371

Debt Ratio Avg. 05-07 -0.06 -1.031 0.303


Pay-Out Ratio Avg. 08-10 -0.084 -1.324 0.187

Debt Ratio Avg. 08-10 0.005 0.078 0.938


Pay-Out Ratio Avg. 05-10 -0.083 -1.353 0.177

Debt Ratio Avg. 05-10 -0.05 -0.854 0.394

2005-2007 2008-2010 2005-2010


Table 4: The association between share price volatility, dividend yield, pay-out ratio and debt ratio.

Table (5) shows the results for the second equation after adding the debt ratio as control

variable holding others constant. Figures are obtained from appendix (6). Dividend yield

results did not vary after adding debt ratio and shows a significant negative relationship with

Tobin Q.

On the other hand pay-out ratio results before the crisis and in the long term were affected by

debt ratio, it shows a non-significant relationship with Tobin Q before the crisis while it

showed an insignificant positive relationship in table (2) and the relationship in the long term

became insignificant though it was significant. After the crisis pay-out ratio continues to

show a positive insignificant relationship with Tobin Q.

Debt ratio had a positive significant relationship with Tobin Q at 10% after the financial

crisis and in the long term, debt ratio seems to have an insignificant positive relationship with

Tobin Q.

Beta figures shows that prior to the credit crisis debt ratio had the biggest impact on the

Tobin Q, but after the financial crisis and in the long term, pay-out ratio have the biggest

impact on Tobin Q then debt ratio and then dividend yield. Adjusted R shows that the

independent variables used affected the Tobin Q’by about 6%.



Page | 33

Pay-Out Ratio Avg. 05-07 -0.033 -0.45 0.653

Debt Ratio Avg. 05-07 0.129 1.826 0.069


Pay-Out Ratio Avg. 08-10 0.061 0.98 0.328

Debt Ratio Avg. 08-10 0.011 0.18 0.857


Pay-Out Ratio Avg. 05-10 0.094 1.515 0.131

Debt Ratio Avg. 05-10 0.058 0.991 0.322

2005-2007 2008-2010 2005-2010


Table 5: The association between Tobin Q’s, dividend yield, pay-out ratio and debt ratio.

Table (6) shows the results for the third equation after adding debt ratio as control variable

holding others constant. Figures are obtained from appendix (7). Dividend yield results were

not affected by the control variable, it shows that in the short-term dividend yield has a

positive significant relationship with ROA and in the long-run the relationship is positive but

insignificant.

Pay-out ratio figures show that it was affected by debt ratio variable prior the crisis. After

showing a non-significant relationship with ROA, the relationship between pay-out ratio and

ROA became negative before the crisis when adding debt ratio as a control variable. The

relationship after the crisis and in the long-term did not vary, it continues to show a negative

relationship between 2008-2010 and a positive relationship in the long-term.

Debt ratio figures show a significant positive relationship with ROA at 5%, but after the

financial crisis the relationship became insignificantly negative. In the long term debt ratio

have a non-significant relationship with ROA.

Beta shows that in the long run dividend yield has the biggest impact on ROA then pay-out

ratio and then debt ratio. Adjusted R shows that in the short term the variables impact on

ROA before financial crisis was greater than after it. In the long term the variables impacted

the ROA by 6%.



Pay-Out Ratio Avg. 05-07 -0.084 -1.139 0.256

Page | 34

Debt Ratio Avg. 05-07 1.37 1.902 0.058


Pay-Out Ratio Avg. 08-10 -0.035 -0.539 0.59

Debt Ratio Avg. 08-10 -0.044 -7.32 0.464


Pay-Out Ratio Avg. 05-10 0.047 0.734 0.463

Debt Ratio Avg. 05-10 0.021 0.355 0.723

2005-2007 2008-2010 2005-2010


Table 6: The association between ROA, dividend yield, pay-out ratio and debt ratio

Table (7) shows the results of the first equation after adding the board directors’ size as

control variable and holding others constant. Figures are obtained from appendix (8).

Dividend yield results were not affected by the control variable and continue to shows the

negative significant relationship with share price volatility.

Pay-out ratio results did not vary before the crisis, it shows a non-significant relationship with

share price volatility. After the financial crisis and in the long term the results were affected

by the board size, it shows that the relationship between pay-out ratio and share price

volatility became significantly negative.

Board size results show a significant negative relationship with share price volatility before

and after the financial crisis and in the long term.

Beta figures show that all the variables affected negatively, Board size had the highest effect

with -0.26, then dividend yield with -0.25 and then pay-out ratio with -0.12. Adjusted R

shows that after the financial crisis, the variables effect declined by 46%. In the long term the

variables impact on share price volatility is about 15%.



Pay-Out Ratio Avg. 05-07 0.009 0.156 0.876

Board Avg. size 05-07 -0.198 -3.455 0.001


Pay-Out Ratio Avg. 08-10 -0.153 -2.426 0.016

Board Avg. size 08-10 -0.219 -3.693 0


Page | 35

Pay-Out Ratio Avg. 05-10 -0.12 -1.967 0.05

Board Avg. size 05-10 -0.257 -4.461 0

2005-2007 2008-2010 2005-2010


Table 7: The association between share price volatility, dividend yield, pay-out ratio and board size.

Table (8) shows the results of the second equation after adding the board directors’ size as


Dividend yield results continue to show the significant negative relationship with Tobin Q’s

in the short and long term.

Pay-out ratio results were not affected by the control variable as well. It shows an

insignificant positive relationship with Tobin Q’s before and after the crisis and a

significantly positive relationship in the long term.

Board size had a negative relationship with Tobin Q’s before the credit crisis. But the

relationship became non-significant after the crisis and in the long term.

Beta figures shows that in the long term Tobin Q’s get affected by dividend yield more than

the other variables. Before the credit crisis, board size had a bigger impact on Tobin Q’s than

pay-out ratio, but after the crisis and in the long-term the results shows that pay-out ratio

effect is more than the board of directors’ size. Adjusted R figures shows that in the long term

the dividend yield, pay-out ratio and board size influence Tobin Q’s by about 6%.



Pay-Out Ratio Avg. 05-07 0.03 0.465 0.642

Board Avg. size 05-07 -0.16 -2.59 0.796


Pay-Out Ratio Avg. 08-10 0.063 0.99 0.323

Board Avg. size 08-10 0.004 0.06 0.953


Pay-Out Ratio Avg. 05-10 0.104 1.626 0.105

Board Avg. size 05-10 -0.002 -0.036 0.971

2005-2007 2008-2010 2005-2010


Table 8: The association between Tobin Q’s, dividend yield, pay-out ratio and board size

Page | 36

Table (9) shows the results of the third equation after adding the board directors’ size as


The results show that dividend yield were not affected by the control variable prior the crisis

and in the long term, it continues to show a significant positive relationship with ROA prior

the crisis and insignificant positive relationship in the long term. After the crisis the result

was affected by the control variable and became insignificantly positive after it was

significant.

Pay-out ratios continue to show a non-significant relationship with ROA before the financial

crisis and an insignificant positive relationship in the long-term. But the results after the crisis

became non-significantly after it was insignificantly negative.

Board sizes have an insignificant positive relationship with ROA in the short and long term.

Adjusted R shows that the variables effect on ROA decreased by about 80%. In the long run

the variables have a 0.6% impact on ROA.



Pay-Out Ratio Avg. 05-07 0.001 0.01 0.992

Board Avg. size 05-07 0.073 1.16 0.247


Pay-Out Ratio Avg. 08-10 0.011 0.163 0.87

Board Avg. size 08-10 0.046 0.734 0.463


Pay-Out Ratio Avg. 05-10 0.062 0.942 0.347

Board Avg. size 05-10 0.074 1.183 0.238

2005-2007 2008-2010 2005-2010


Table 9: The association between ROA, dividend yield, pay-out ratio and board size

Table (10) shows the results of the first equation after adding the market capitalisation as


Dividend yield figures show the constant significant negative relationship with share price

volatility.

Page | 37

Pay-out ratio figures did not vary from the previous results as well. It shows the non-

significant relationship before the financial crisis and insignificant negative relationship after

the crisis and in the long term.

Market capitalisation as expected have a significant negative relationship with price volatility

in the short and long term. Beta figures shows that in the long term market capitalisation have

the biggest effect on share price volatility with (-2), then dividend yield with (-0.224) and

then pay-out ratio with (-0.096). Adjusted R shows that the variables effect on share price

volatility declined by 71% from 0.174 to 0.05. In the long term the variables affected price

volatility by about 11%.



Pay-Out Ratio Avg. 05-07 0.013 0.24 0.811

Market Avg. Cap 05-07 -0.183 -3.375 0.001


Pay-Out Ratio Avg. 08-10 -0.09 -1.458 0.146

Market Avg. Cap 08-10 -0.163 -2.794 0.006


Pay-Out Ratio Avg. 05-10 -0.096 -1.607 0.11

Market Avg. Cap 05-10 -2 -3.551 0

2005-2007 2008-2010 2005-2010


Table 10: The association between share price volatility, dividend yield, pay-out ratio and market cap.

Table (11) shows the results of the second equation after adding the market capitalisation as


Dividend yield results were not affected by the control variable and continue to shows a

significant negative relationship with Tobin Q’s in short and long term.

Pay-out ratio results did not vary as well. It shows the insignificant positive relationship in

the short term with Tobin Q’s and a significant positive relationship in the long term.

Market capitalisation figures shows an in significant positive relationship with Tobin Q’s

before the financial crisis and a positive significant relationship after the crisis and in the long

term.

Page | 38

Beta figures shows that Dividend yield have the strongest effect on Tobin Q’s with (-0.27)

then pay-out ratio with (0.104) then market capitalisation with (0.099). Adjusted R shows that

the variables affect Tobin Q’s by 6.2% in the long term.

Table 11: The association between Tobin Q’s, dividend yield, pay-out ratio and market cap.

Table (12) shows the results of the third equation after adding the market capitalisation as


Dividend yield results did not vary, it shows the significant positive relationship with ROA in

the short term and insignificant positive relationship in the long term.

Pay-out ratio results were not affected by the control variable as well and continue to shows a

non-significant relationship with ROA before the credit crisis, which became negatively

insignificant after the crisis and in the long term, pay-out ratios have insignificant positive

relationship with ROA.

Market capitalisation figures show the significant positive relationship with ROA in the short

and long term.

Beta figures in the long term shows that market capitalisation have the biggest impact on

ROA with (0.162) then dividend yield with (0.094) and then pay-out ratio with (0.056).

Adjusted R in the long term shows that the independent variables affect ROA by 3.2%.





Pay-Out Ratio Avg. 05-07 0.045 0.747 0.456

Market Avg. Cap 05-07 0.92 1.564 0.119


Pay-Out Ratio Avg. 08-10 0.055 0.9 0.369

Market Avg. Cap 08-10 0.113 1.95 0.052


Pay-Out Ratio Avg. 05-10 0.104 1.697 0.091

Market Avg. Cap 05-10 0.099 1.71 0.088

2005-2007 2008-2010 2005-2010


Page | 39

Pay-Out Ratio Avg. 05-07 0.001 0.02 0.984

Market Avg. Cap 05-07 0.126 2.136 0.034


Pay-Out Ratio Avg. 08-10 -0.033 -5.21 0.603

Market Avg. Cap 08-10 0.142 2.403 0.017


Pay-Out Ratio Avg. 05-10 0.056 0.899 0.37

Market Avg. Cap 05-10 0.162 2.764 0.006

2005-2007 2008-2010 2005-2010


Table 12: The association between ROA, dividend yield, pay-out ratio and market cap

Table (13) shows the results for the first equation after adding the industry type as a control

variable and holding others constant. Figures are obtained from appendix (14).

Dividend yield figures were affected by the control variable, it continues to show a

significant negative relationship with share price volatility before the credit crisis, but after

the crisis and in the long term it shows an insignificant negative relationship with share price

volatility, while it was significant in table (1).

Pay-out ratio figures were affected as well by the control variable. It continues to show the

non-significant relationship with share price volatility before the financial crisis, but after the

crisis and in the long term the relationship became significantly negative, while it was

insignificant.

Industry type shows figures show an insignificant negative relationship with share price

volatility prior the crisis and a significant negative relationship after the crisis and in the long

term.

Beta results show that dividend yield and industry type effect on share price decreased by

75%, 35% respectively, pay-out ratio effect increased by 500%. In the long term pay-out ratio

have the strongest effect on share price volatility, then industry type and then dividend yield.

Adjusted R square shows that in the long term the independent variables impacted share price

volatility by 9.2%.



Pay-Out Ratio Avg. 05-07 0.024 0.416 0.678

Page | 40

Industry type 05-07 -0.32 -0.569 0.57


Pay-Out Ratio Avg. 08-10 -0.115 -1.878 0.062

Industry type 08-10 -0.209 -3.606 0


Pay-Out Ratio Avg. 05-10 -0.223 -3.683 0

Industry type 05-10 -0.162 -2.844 0.005

2005-2007 2008-2010 2005-2010


Table 13: The association between share price volatility, dividend yield, pay-out ratio and Industry type.

Table (14) shows the results of the second equation after adding industry type as control


Dividend yield and pay-out ratio results were not affected by the control variable. Dividend

yield continues to show its significant negative relationship in the short and long term with

Tobin Q.

Pay-out ratio remains to have an insignificant positive relationship with Tobin Q in the short

term and a significant positive relationship in the long term.

Industry type results show an insignificant positive relationship with Tobin Q before the

crisis, after the crisis the relationship became non-significant and positively insignificant in

the long-term.

Beta figures show that in the long term dividend yield has the strongest effect on Tobin Q,

then pay-out ratio and then industry type. Adjusted R square shows that the independent

variables affect the Tobin Q’s by about 6% in the long term.



Pay-Out Ratio Avg. 05-07 0.038 0.624 0.533

Industry type 05-07 0.077 1.311 0.191


Pay-Out Ratio Avg. 08-10 0.054 0.878 0.381

Industry type 08-10 0.025 0.433 0.665


Page | 41

Pay-Out Ratio Avg. 05-10 0.102 1.663 0.097

Industry type 05-10 0.074 1.284 0.2

2005-2007 2008-2010 2005-2010


Table 14: The association between Tobin Q’s, dividend yield, pay-out ratio and Industry type.

Table (15) shows the results of the third equation after adding industry type as control


Dividend yield results were not affected by the industry type; it shows a significant positive

relationship with ROA in the short term and an insignificant positive relationship in the long

term.

Pay-out ratio results were only affected after the crisis. It continues to show a non-significant

relationship with ROA before the crisis and an insignificant positive relationship in the long

term. After the crisis the relationship became non-significant after it was negative before

adding the control variable.

Industry type results show a non-significant relationship with Tobin Q’s before the crisis and

an insignificant positive relationship after the crisis and in the long term.

Betas figures show that dividend yield have the strongest effect on ROA, then pay-out ratio

and then industry type. Adjusted R shows that in the long term the independent variables

affected ROA by 0.7%.



Pay-Out Ratio Avg. 05-07 -0.004 -0.07 0.944

Industry type 05-07 -0.021 -0.348 0.728


Pay-Out Ratio Avg. 08-10 -0.029 -0.455 0.65

Industry type 08-10 0.095 1.589 0.113


Pay-Out Ratio Avg. 05-10 0.05 0.794 0.428

Industry type 05-10 0.034 0.578 0.564

2005-2007 2008-2010 2005-2010


Page | 42

Table 15: The association between ROA, dividend yield, pay-out ratio and industry type.

Table (16) shows the result of the fourth equation. Figures are obtained from appendix (17).

It shows that the effect of the independent variables varied after the financial crisis.

After adding all the control variables dividend yield continued to show a significant negative

relationship with share price volatility, which lead to accept the null hypothesis (H0) from

hypothesis one and rejecting the alternative hypothesis (H1). This is consistent with Baskin

(1989) findings.

Dividend pay-out ratio results varied after adding all the control variables to the equation.

Before the crisis it continued to show a non-significant relationship with price volatility, but

while it showed an insignificant negative relationship after the crisis and in the long-term, the

relationship became significantly negative. For that the null hypothesis (H0) from the second

hypothesis were accepted and the alternative hypothesis (H1) were rejected. This is consistent

with Bakin (1989), Allen and Rachim (1996) and Hussainey et al. (2011) findings.

On the other hand the control variables had different effects on share price volatility. Industry

type showed an insignificant negative relationship with share price volatility before the crisis

and a significant negative relationship after the crisis and in the long term. This is

inconsistent to Hussainey et al. (2011) findings, which suggested a non-significant

relationship between industry type and price volatility. Hussainey et al. (2011) model

classified companies to two groups, services and industrial, while in this model nine groups

were used to classify the companies and that might resulted the differences in findings.

Board size results showed a significant negative relationship with share price volatility at

10% before the crisis and 1% after the crisis and in the long term. This is consistent with

Barnhart and Rosenstein (1998) findings. Market capitalisation results showed a significant

negative relationship with share price volatility at 10% before the crisis and in the long term.

But after the crisis the relationship were negatively insignificant. This is consistent with

Hussainey et al. (2011) findings.

Beta figures shows that the effect of dividend yield, board size and debt ratio decreased after

the crisis and the effect of pay-out ratio, industry type and board of directors’ size increased

after the crisis. In the long term dividend yield have the highest effect on price volatility with

(-0.235), then board size with (-0.218), then industry type with (-0.209), then pay-out ratio

with (-0.125), then market capitalisation with (-0.11) and then debt ratio with (-0.021).

Page | 43

Adjusted R square figures show that the independent variables affect price volatility by about

19% in the long term.



Pay-Out Ratio Avg. 05-07 0.027 0.369 0.712

Industry type 05-07 -0.072 -1.24 0.216

Board Avg. size 05-07 -0.129 -1.859 0.064

Market Cap. Avg. 05-07 -0.128 -1.863 0.064

Debt Ratio Avg. 05-07 -0.03 -0.427 0.67


Pay-Out Ratio Avg. 08-10 -0.16 -2.59 0.01

Industry type 08-10 -0.246 -4.211 0

Board Avg. size 08-10 -0.182 -2.677 0.008

Market Cap. Avg. 08-10 -0.098 -1.453 0.148

Debt Ratio Avg. 08-10 0.007 0.111 0.912


Pay-Out Ratio Avg. 05-10 -0.125 -2.077 0.039

Industry type 05-10 -0.209 -3.685 0

Board Avg. size 05-10 -0.218 -3.202 0.002

Market Cap. Avg. 05-10 -0.11 -1.641 0.102

Debt Ratio Avg. 08510 -0.021 -0.369 0.713

2005-2007 2008-2010 2005-2010


Table 16: The association between share price volatility, dividend yield, pay-out ratio, Industry type, board size, market cap.

And debt ratio.

Table (17) shows the result of the fifth equation. Figures are obtained from appendix (18).

Dividend yield results were not affected by the control variables and shows a significant

negative relationship with Tobin Q’s in short and long term. For that the null hypothesis (H0)

from the third hypothesis is accepted and the alternative hypothesis (H1) is rejected. This is

consistent with Gordon growth model (Damodaran, 2002).

Pay-out ratio results were affected by the control variables. It shows a non-significant

relationship with Tobin Q before the crisis, while it showed a positive relation in table (2).

Page | 44

After the crisis and in the long term the relationship became positive. For that we accept the

alternative hypothesis (H1) from the fourth hypothesis and we reject the null hypothesis (H0).

This is consistent with Murekefu and Ouma (2012) findings.

The control variables result shows a positive relationship between industry type and Tobin Q.

On the other hand board of directors’ size have a negative relationship with Tobin Q. This is

consistent with Guest (2009) results. Market capitalisation results showed a significant

positive relationship with Tobin Q. Debt ratio had a significant positive relationship with

Tobin Q before the crisis, non-significant relationship after the crisis and an insignificant

positive relationship with Tobin Q in the long-term. This is consistent with Saeedi and

Mahmoodi (2011) findings.

Beta figures shows that the independent variables effect on Tobin Q’s did not vary after the

financial crisis, expect the debt ratio effect which declined by 80% after the crisis. In the long

term dividend yield have the strongest effect on Tobin Q’s with (-0.29), then market

capitalisation with (0.145), then pay-out ratio with (0.098), then board of directors’ size with

(-0.084), then industry type with (0.08) and then debt ratio with (0.076). Adjusted R square

figures shows that in the long term, the independent variables affect Tobin Q’s by 7%.



Pay-Out Ratio Avg. 05-07 -0.053 -0.689 0.491

Industry type 05-07 0.071 1.14 0.256

Board Avg. size 05-07 -0.105 -1.404 0.162

Market Cap. Avg. 05-07 0.145 1.968 0.05

Debt Ratio Avg. 05-07 0.145 1.918 0.056


Pay-Out Ratio Avg. 08-10 0.089 1.366 0.173

Industry type 08-10 0.048 0.777 0.438

Board Avg. size 08-10 -0.063 -0.878 0.381

Market Cap. Avg. 08-10 0.148 2.082 0.038

Debt Ratio Avg. 08-10 0.028 0.456 0.649


Pay-Out Ratio Avg. 05-10 0.098 1.522 0.129

Industry type 05-10 0.08 1.313 0.191

Page | 45

Board Avg. size 05-10 -0.084 -1.151 0.251

Market Cap. Avg. 05-10 0.145 20.024 0.044

Debt Ratio Avg. 08510 0.076 1.217 0.225

2005-2007 2008-2010 2005-2010


Table 17: The association between Tobin Q’s, dividend yield, pay-out ratio, Industry type, board size, market capitalisation and

debt ratio.

Table (18) shows the results of the sixth equation. Figures are obtained from appendix (19).

Dividend yield results continue to shows a significant positive relationship before the crisis

and an insignificant positive relationship in the long-term. A0fter crisis results were affected

by the control variables, it shows a non-significant relationship with ROA, while it showed a

significant positive relationship in table (3). For that the alternative hypothesis (H1) from

hypothesis five is accepted and the null hypothesis (H0) is rejected. This is consistent with

Amidu (2007).

On the other hand pay-out ratio results were affected by the control variable in the short term,

while it showed a non-significant relation with ROA before the crisis, the relationship

became positive after adding the control variables. After the crisis the relationship became

non-significant after it was negative before. In the long term the results did not vary and it

continues to show a positive relationship between pay-out ratio and ROA. Therefore the

alternative hypothesis (H1) from the sixth hypothesis is accepted and the null hypothesis is

rejected (H0). These results are consistent with DeAngelo et al. (2006) and Amidu (2007).

The control variables result shows a non-significant relationship between industry type and

ROA in the short term (before and after the crisis) and a positive relationship with ROA in

the long term. Board size results show a non-significant relationship with ROA. This is

consistent with Topak (2011) findings. Firm size results shows a significant positive

relationship with ROA at 10% before the crisis and significant at 5% after the crisis and in

the long term. This is consistent with Saeedi and Mahmoodi (2011) suggestions. Debt ratio

had a significant positive relationship with ROA at 10%. But the relationship became non-

significant after the crisis and in the long-term.

Beta figures show that the variables effect on ROA did not vary after the financial except

industry type and debt ratio. In the long-run market capitalisation has the highest effect on

ROA with (0.172), then dividend yield with (0.066), then pay-out ratio with (0.061), then

Page | 46

industry type with (0.052), then debt ratio with (0.026) and then board size with (-0.017).

Adjusted R square figures show that the independent variables affect the ROA by 1.7%.



Pay-Out Ratio Avg. 05-07 -0.075 -0.954 0.341

Industry type 05-07 -0.004 -0.065 0.948

Board Avg. size 05-07 -0.015 -0.196 0.845

Market Cap. Avg. 05-07 0.129 1.712 0.088

Debt Ratio Avg. 05-07 0.133 1.709 0.089


Pay-Out Ratio Avg. 08-10 0.02 0.302 0.763

Industry type 08-10 0.102 1.619 0.107

Board Avg. size 08-10 -0.021 -0.286 0.775

Market Cap. Avg. 08-10 0.162 2.209 0.028

Debt Ratio Avg. 08-10 -0.024 -0.378 0.706


Pay-Out Ratio Avg. 05-10 0.061 0.923 0.357

Industry type 05-10 0.052 0.827 0.409

Board Avg. size 05-10 -0.017 -0.225 0.822

Market Cap. Avg. 05-10 0.172 2.338 0.02

Debt Ratio Avg. 08510 0.026 0.399 0.69

2005-2007 2008-2010 2005-2010


Table 18: The association between ROA, dividend yield, pay-out ratio, Industry type, board size, market capitalisation and debt

ratio.

4.3 Summary

This chapter described the changes in the mean and standard deviation for the research

variables, analysed the regression results and stating the results of the hypothesis tests.

The regressions results suggested different relations between dividend yield and firm

performance before and after adding the control variables and based on the measurements

used.

Page | 47

Before adding the control variables dividend yield had a significant negative relationship with

share price volatility and Tobin Q. But it showed a significant positive relationship with ROA

in the short term and a positive relationship in the long-term.

But after adding the control variables the relationship with share price volatility and Tobin Q

did not vary. It showed the same results with ROA before the crisis and in the long-term but

after the crisis the relationship became non-significant.

On the other hand before adding the control variables, dividend pay-out ratio results showed

a non-significant relationship with share price volatility before the crisis and a negative

relationship after the crisis and in the long-term. It showed a positive relationship with Tobin

Q in the short term and a significant positive relationship in the long term. With ROA it

showed a non-significant relationship before the crisis, negative relationship after the crisis

and a positive relationship in the long term.

After adding the control variables, pay-out ratio continued to show a non-significant

relationship with share price volatility before the crisis but the relationship after the crisis and

in the long term became significantly negative. The relationship with Tobin Q became non-

significant after the crisis and positive before the crisis and in the long term. It showed a

positive relationship with ROA before the crisis and in the long term and a non-significant

relationship after the crisis.

The control variables results showed that industry type have a negative relationship with

share price volatility before the crisis and a significant negative relationship after the crisis

and in the long-term. The relationship between industry type and firm performance became

positive when Tobin Q is used as an indicator. When ROA is used, industry type results

showed a non-significant relationship with firm performance in the short term and positive

relationship in the long-term.

Board of directors’ size results showed a significant negative relationship with share price

volatility, a negative relationship with Tobin Q and a non-significant relationship with ROA.

Market capitalisation results showed a significant negative relationship with share price

volatility before the crisis and in the long term but an insignificant negative relationship after

the crisis. On the other hand market capitalisation has a significant positive relationship with

Tobin Q and ROA.

Debt ratio results showed a non-significant relationship with share price. It shows a

significant positive relationship with Tobin Q before the crisis which became non-significant

relationship after the crisis and a positive relationship in the long-term with Tobin Q.

Page | 48

Chapter Five

5.1 Conclusion

The purpose of this research was to observe the relationship between dividend policy

(dividend yield and pay-out ratio) with firm performance (ROA, Tobin Q’s and share price

volatility). It also considered some factors affecting the dividend policy (industry type, board

of directors’ size, market capitalisation and debt ratio) and its relationship with the firm

performance measurements. The relationship between the variables was examined using

linear regression for the purpose of analysis. The study was based on 283 firms’ which

maintained its existence in the UK stock market between the period 2005 and 2010 after

excluding the financial firms. The model results showed different relations between dividend

yield and firm performance based on the indicators used.

When using share price volatility as a performance indicator and regress it with the variables,

the results suggested a significant negative relationship with dividend yield and a non-

significant relationship with pay-out ratio before the financial crisis, but a significant negative

relationship after the crisis and on the long term. Dividend yield result is consistent with

Baskin (1989) findings. Pay-out ratio suggestion is consistent with Baskin (1989), Allen and

Rachim (1996) and Hussainey et al. (2011) results. The results suggest that the higher the

firms’ dividend yield and pay-out ratio the volatility of its stock price will be lower. On the

other hand the control variables had a negative relationship with share price volatility except

the debt ratio that showed a non-significant relationship with price volatility. Type of industry

showed a negative relationship with share price volatility before the financial crisis, but the

relationship became significantly negative after the crisis and on the long term. This result is

inconsistent to Hussainey et al. (2011) due to the different classifications used for companies.

Board of directors’ size showed a significant negative relationship with share price volatility

at 10% before the crisis and at 1% after the crisis and on the long term. This is consistent with

Page | 49

Barnhart and Rosenstein (1998). Firm size showed a significant negative relationship with

share price volatility at 10% before the crisis and in the long term, but insignificant negative

relationship after the crisis. This is consistent with Hussainey et al. (2011) findings. The

result shows that dividend yield have the highest effect on share price volatility.

On the other hand when using Tobin Q as a performance indicator the results highly varied.

Dividend yield result shows a significant negative relationship with Tobin Q. This is

consistent with Gordon growth model (Damodaran, 2002). While the relationship between

pay-out ratio and firm performance was significantly negative when share price volatility was

used as an indicator, the relationship became non-significant before the crisis and positive

after the crisis an in the long term with share price volatility when using Tobin Q as an

indicator. This is consistent with Murekefu and Ouma (2012) findings. The results suggest

that a firm with a high dividend yield will have a low Tobin Q and a firm with high pay-out

ratio will have a high Tobin Q. The control variables results showed a positive relationship

between industry type and firm performance using Tobin Q. Board of directors’ size

continues to show a negative relationship with firm performance after using Tobin Q as an

indicator. This is consistent with Guest (2009) findings. Firm size fissures suggest a

significant positive relationship with Tobin Q. Debt ratio result shows a significant positive

relationship with Tobin Q before the crisis, but after the crisis the relationship became non-

significant and in the long term the relationship is positively insignificant. This is consistent

with Saeedi and Mahmoodi (2011) findings. The results suggested that dividend yield have

the highest impact on Tobin Q results.

When using a book value measurement (ROA) as a firm performance indicator the results

suggest different relations. Although dividend yield had a significant negative relationship

with firm performance when share price volatility and Tobin Q were used, the results showed

a significant positive relationship before the crisis, non-significant relationship after the crisis

and an insignificant positive relationship in the long term between dividend yield and firm

performance when ROA is used as an indicator. This is consistent with Amidu (2007). Pay-

out ratio figures suggests a positive relationship with ROA before the crisis and on the long

term and a non-significant relationship with ROA after the crisis. This is consistent with

DeAngelo et al. (2006) and Amidu (2007). This means that a firm with high dividend yield

and pay-out ratio will have a high ROA. The control variables results suggested a non-

significant relationship between industry type and ROA before and after the crisis, but a

Page | 50

positive relationship in the long term. Board of directors’ size have no effect on firm

performance when using ROA as an indicator. This is consistent with Topak (2011) results.

Firm size figures show a significant positive relationship with ROA. This is consistent with

Saeedi and Mahmoodi (2011) findings. Debt ratio figures show a significant positive

relationship with ROA before the crisis, but after the crisis and on the long term there is no

effect of debt ratio on ROA. The results suggest that market capitalisation have the highest

effect on ROA.

The results above suggest that the relationship between dividend policy and firm performance

depend on the measurements used to identify them. It shows that using market data will

provide different results than using book value figures. For that investors’ and managers will

have different results and suggestions about the relationship between dividend and

performance based on the measures used for dividend policy and firm performance and the

control variables used.

5.2 Limitation

Although the research fulfilled its aims and objectives, but that does not mean there were no

limitations in the study. First the use of firm performance measures, while considering the use

of different measures by using market and book value data. Stock price might not reflect the

real financial situation of the firm and its investment opportunities that have. It does not

consider the firms’ future earnings and it is affected by the external factors that affect the

financial markets (Bernard and Thomas, 1990). On the other hand using ROA as a financial

ratio for firm performance measure might provide un-reliable results since ROA represents

the historical economic values and not the current economic one and it is analysed using

accounting data which can be manipulated by the firm (Bowhill, 2008). Second, it is

important to study the relationship between dividend policy and firm performance excluding

year 2008, which had the peak of the financial credit crisis. Replacing year 2008 with a

dummy variable might provide different results. This dissertation failed to study that

relationship because of the time limit. Third, the control variables used were not enough to

reflect all the factors affecting the firms’ dividend policy and its performance. For that more

control variables should be added to indicate the main factors affecting the firms’ dividend

policy and its performance. To understand the effect of dividend policy on firms’

performance it is recommended to study each industry separately, since each industry is

affected by different variables and it has its own government regulations.

Page | 51

Page | 52

References

Al Shabibi, B. K. & Ramesh, G. (2011). An Empirical Study on the Determinants of

Dividend Policy in the UK. International Research Journal of Finance and Economics, 80,

106-120.

Allen, D. E. & Rachim, V. S. (1996). Dividend policy and stock price volatility: Australian

evidence. Applied Financial Economics, 6(2), 175-188.

Al-Malkawi, N. H. (2007). Determinants of Corporate Dividend Policy in Jordan: An

application of the Tobit Model. Journal of Economic & Administrative Sciences, 23(2), 44-

70.

Al-Najjar, B. & Hussainye, K. (2009). The Association between Dividend Payout and

Outside Directorships. Journal of Applied Accounting Research, 10, 4-19.

Amidu, M. (2007). How does dividend policy affect performance of the firm on Ghana stock

exchange?. Investment Management and Financial Innovations,4(2), 103-112.

Arnold, G. (2008) Corporate Finance Management (4th Ed.). England: Person education

limited.

Baker, H. K. & Powell, G. E (2000). Determinants of corporate dividend policy: a survey of

NYSE firms. Financial Practice and education, 9, 29-40.

Barnhart, S. W. & Roseinstein, S. (1998). Board Composition, Managerial Ownership, and

Firm Performance: An Empirical Analysis. The Financial Review, 33, 1-16.

Baskin, J. (1989). Dividend policy and the volatility of common stock. Journal of Portfolio

Management, 15, 19-25.

Bathala, C. & Rao, R. (1995). The Determinants of Board Composition: An Agency Theory

Perspective. Managerial and Decision Economics, 16(1), 59-69.

Bernard, V. L., & Thomas, J. K. (1990). Evidence That Stock Prices Do Not Fully

Reflect The Implications Of Current Earnings For Future Earnings. Journal of Accounting

and Economics, 13, 305-340.

Bharadwaj, A. S., Bharadwaj, S. G. & Konsynski, B. R. (1991). Information Technology

Effects on Firm Performance as Measured by Tobin's q. Management Science, 45(7), 1008-

1024.

Bhattacharyya, N. (2007). Dividend policy: a review. Managerial Finance, 33(1), 4-13.

Black, F. (1976). The dividend puzzle. Journal of Portfolio Management, 2, 5-8.

Bleden, S., Fister, T. & Knapp, B. (2005). Dividends and Directors: Do Outsiders Reduce

Page | 53

Agency Costs?. Business and Society Review, 110(2), 171-180.

Bokpin, G. A. (2011). Ownership structure, corporate governance and dividend performance

on the Ghana Stock Exchange. Journal of Applied Accounting Research, 12(1), 61-73.

Bond, M. T. & Mougoue, M. (1991). Corporate dividend policy and the partial adjustment

model. Journal of Economics and Business, 43(2), 165-178.

Borokhovich, K., Brunarski, K., Harman, Y. & Kehr, J. (2005). Dividends, Corporate

Monitors and Agency Costs. The Financial Review, 40, 37-65.

Bowhill B., (2008). Business planning and control: Integrating accounting, strategy and

people. England: John Wiley & Sons.

Chatterjee, A. & Maniam, B. (2011). Market Anomalies Revisited. Journal of Applied

Business Research. 13(4), 47-56.

Chung, K. H. & Pruitt, S. W. (1994). A simple approximation of Tobin's q. Financial

Management, 23(3), 70-74.

Damodaran, A. (2002). Investment valuation. New York: Wiley.

DeAngelo, H., DeAngelo, L. & Stulz, R. M. (2006). Dividend policy and the earned/

contributed capital mix: a test of the life-cycle theory. Journal of Financial Economics, 81,

227–254.

Dobbins R. & Witt, S. F. (1993). How Much Should A Firm Pay in Dividends?. Managerial

Finance, 8(1), 23-27.

D'Souza, J. & Saxena, A. K. (1999). Agency cost, market risk, investment opportunities and

dividend policy - an international perspective. Managerial Finance, 25(6), 35-43.

Easterbrook, F. (1984). Two agency cost explanations of dividends. American Economic

Review, 74, 650-659.

Fairchild, R. (2010) Dividend policy, signalling and free cash flow: an integrated approach.

Managerial Finance, 36(5), 394-413.

Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work.

Journal of Finance, 25, 383-41.

Fama, E. F. (1991). Efficient Capital Markets: II. The Journal of Finance, 46(5), 1575-1617.

Fama, E. F. & French, K. R. (2001). Disappearing dividends: changing firm characteristics or

lower propensity to pay?. Journal of Financial Economics, 60, 3-43.

Page | 54

Feltham, G., & Xie, J. (1994). Performance Measure Congruity and Diversity in Multi-Task

Principal/Agent Relations. Accounting Review, 69, 429-453.

Forbes, K. J. (2002). How Do Large Depreciations Affect Firm Performance?. International

Monetary Fund, 49, 214-238.

Forsythe, R., Palfrey, T. R. & Plott, C. R. (1984). Futures Markets and Informational

Efficiency: A Laboratory Examination. Journal of Finance, 39, 955-981.

Frankfurter, G.M. & Wood, B.G. (2002). Dividend policy theories and their empirical tests.

International Review of Financial Analysis, 11, 111-38.

Goddard, J., McMillan, D. G. & Wilson, J. O. S. (2006). Dividend smoothing vs dividend

signalling: evidence from UK firms. Managerial Finance, 32(6), 493-504.

Grullon, G., Michaely, R. & Swaminathan, B. (2002). Are Dividend Changes a Sign of Firm

Maturity?. The Journal of Business, 75, 387-424.

Guest, P. M. (2009). The Impact of Board Size on Firm Performance: Evidence from the UK.

The European Journal of Finance, 15(4), 385-404.

Hall, B. H. (1993). The stock market's valuation of R&D investment during the 1980's. AEA

Papers and Proceedings, 70(2), 259-264.

Ho, H. (2003). Dividend policies in Australia and Japan. International Advances in

Economic Research, 9(2), 91-100.

Holder, M. E., Langrehr, F. W. & Hexter, J. L. (1998). Dividend policy determinants: an

Investigation of the influences of stakeholder theory. Financial Management 27(3), 73-82.

Hussainey, K., Mgbame, C. O. & Chijoke-Mgbame, A. M. (2011). Dividend policy and share

price volatility: UK evidence. The Journal of Risk Finance, 12(1), 57-68.

Jensen, M. C. & Meckling, W. H. (1976). Theory of the Firm: Managerial Behaviour,

Agency Costs and Ownership Structure. Journal of Financial Economics, 3(4), 305-360.

Jiraporn, P., Kim, S. & Mathur, I. (2008). Does corporate diversification exacerbate or

mitigate earnings management?: an empirical analysis. International Review of

Financial Analysis, 17, 1087-1109.

Kaplan, S. & Reishus, D. (1990). Outside directorships and corporate performance. Journal

of Financial Economics, 27(2), 389-410.

Keim, D. B., (1985). Dividend Yields and Stock Returns: Implications of Abnormal January

Returns. Journal of Financial Economics, 14, 473-489.

Page | 55

Lintner, J. (1965). Distribution of incomes of corporations among dividends, retained

earnings and taxes. The American Economic Review, 46(2), 97-113.

Malkiel B. G. (2003). The Efficient Market Hypothesis and Its Critics. Journal of Economic

Perspectives, 17(1), 59-82.

Miller, M. H, & Modigliani, F. (1961). Dividend policy, growth and the valuation of shares.

The Journal of Business, 34(4), 411-433.

Miller, M. & Scholes, M. (1982). Dividends and Taxes: Some Empirical Evidence. Journal

of Political Economy, 90(6), 1118-1141

Modigliani, F. (1982). Debt, Dividend Policy, Taxes, Inflation and Market Valuation.

Journal of Finance, 37(2), 255-273.

Murekefu, T. M. & Ouma, O. P. (2012). The relationship between dividend pay-out and firm

performance: a study of listed companies in Kenya. European Scientific Journal, 8(9), 199-

215.

Niu, X. (2008). Theoretical and practical review of capital structure and its

determinants. International Journal of Business and Management, 3 (3), 133-139.

Pettit, R. R. (1972) Dividend Announcements, Security Performance and Capital Market

Efficiency. Journal of Finance, 27, 993-1007.

Ross, S. A., Westerfield, R. W., Jaffe, J. and Jordan, B. D. (2008), Modern Financial

Management (8th ed). New York: McGraw-Hill.

Saeedi, A. & Mahmoodi, I. (2011). Capital Structure and Firm Performance:Evidence from

Iranian Companies. International Research Journal of Finance and Economics, 70, 21-29.

Schellenger, M., Wood, D. & Tashakori, A. (1989). Board of Director Composition,

Shareholder Wealth, and Dividend Policy. Journal of Management, 15 (3), 457-467.

Smith, C. W. & Watts, R. L. (1992). The Investment Opportunity Set and Corporate

Financing, Dividend, and Compensation Policies. Journal of Financial Economics, 32, 263-

292.

Thaler, R. H. (1987). Anomalies: The January Effect. The Journal of Economic Perspective,

1(1), 197-201.

Topak, M. S. (2011). The Effect of Board Size on Firm Performance: Evidence from Turkey.

Middle Eastern Finance and Economics, (14), 120-126.

Van Caneghem, T. & Aerts, W. (2011). Intra-industry conformity in dividend policy.

Managerial Finance, 37(6), 492 – 516.

Page | 56

Wolf, J. & Sauaia, A. C. A. (2003). The Tobin q as a company performance indicator.

Developments in Business Simulation and Experiential Learning, 30, 155-159.

Yoon, P. S. & Starks, L. T. (1995). Signalling, Investment Opportunities and Dividend

Announcements. Review of Financial Studies, 8(4), 995-1018.

.

Page | 57

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Appendices

Appendix (1): Variables descriptive analysis

Table 1: Debt ratio descriptive analysis

N Minimum Maximum Mean Std. Deviation

Debt Ratio 2005 270 0 1157 89.34 137.631

Debt Ratio 2006 268 0 3027 103.35 247.941

Debt Ratio 2007 271 0 4319 117.75 350.453

Debt Ratio 2008 271 0 1596 106.39 184.032

Debt Ratio 2009 268 0 8229 133.91 522.598

Debt Ratio 2010 265 0 5330 112.83 394.618

Valid N (listwise) 246

Table 2: Dividend yield descriptive analysis


Dividend Yield 2005 282 0 27 2.66 2.124

Dividend Yield 2006 283 0 7 2.47 1.498

Dividend Yield 2007 283 0 11 2.78 1.835

Dividend Yield 2008 282 0 30 4.29 3.467

Dividend Yield 2009 283 0 15 3.24 2.716

Dividend Yield 2010 274 0 12 2.72 2.054


Table 3: Market capitalisation descriptive analysis


Market Cap. 2005 283 62 127864 3670.61 12145.047

Market Cap. 2006 283 60 111715 3934.46 11484.914

Market Cap. 2007 283 36 116372 4481.00 12975.104

Market Cap. 2008 283 11 112869 3602.64 12102.824

Market Cap. 2009 283 15 112584 4017.82 12734.583

Market Cap. 2010 275 10 110281 4817.82 13946.901


Page | 59

Table 4: Return on assets descriptive analysis


ROA 2005 280 -36 35 6.90 8.615

ROA 2006 281 -42 38 6.94 9.516

ROA 2007 281 -32 72 8.36 9.503

ROA 2008 280 -57 52 5.75 9.816

ROA 2009 280 -37 70 3.39 8.890

ROA 2010 274 -49 33 5.17 7.767


Table 5: Tobin Q’s descriptive analysis


Tobin Q’s 2005 281 1 6 1.89 .980

Tobin Q’s 2006 281 1 8 2.04 1.040

Tobin Q’s 2007 281 1 7 1.93 .970

Tobin Q’s 2008 280 0 5 1.40 .712

Tobin Q’s 2009 282 0 4 1.42 .693

Tobin Q’s 2010 273 1 8 1.59 .903


Table 6: Tobin Q’s Statistical Analysis.

Table 6: Pay-out ratio descriptive analysis


Pay-Out Ratio 2005 274 0 1200 60.55 110.380

Pay-Out Ratio 2006 268 0 9268 91.28 570.175

Pay-Out Ratio 2007 272 0 4022 62.52 245.857

Pay-Out Ratio 2008 253 0 10500 104.38 671.611

Pay-Out Ratio 2009 240 0 2514 84.52 226.593

Pay-Out Ratio 2010 261 0 1318 58.29 126.566


Page | 60

Table 8: Board of directors’ size descriptive analysis


Board size 2005 240 4 17 8.92 2.309

Board size 2006 242 4 17 8.95 2.431

Board size 2007 252 4 19 8.93 2.417

Board size 2008 259 4 19 8.90 2.369

Board size 2009 255 5 17 8.73 2.270

Board size 2010 251 4 17 8.75 2.330


.

Table 7: 360 days volatility descriptive analysis


Volatility 2005 280 10 97 26.08 10.784

Volatility 2006 283 14 84 28.57 9.439

Volatility 2007 283 13 115 31.04 9.899

Volatility 2008 283 20 136 48.19 17.699

Volatility 2009 283 28 156 60.43 22.172

Volatility 2010 275 18 179 42.87 18.943


Page | 61

Appendix (2): Linear regression results from the SPSS model for the

relationship between dividend yield and dividend pay-out ratio with share price

volatility.

Average 2005-2007.

Model Summary

Model R R Square Adjusted R

Square

Std. Error of

the Estimate

1 .386a .149 .143 7.901

a. Predictors: (Constant), Pay-Out Ratio Avg. 05-07, Dividend

Yield Avg. 05-07

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 3045.925 2 1522.962 24.397 .000b

Residual 17415.990 279 62.423

Total 20461.915 281

a. Dependent Variable: 360 Volatility Avg. 05-07

b. Predictors: (Constant), Pay-Out Ratio Avg. 05-07, Dividend Yield Avg. 05-07

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 34.385 .961 35.770 .000

Dividend Yield Avg. 05-07 -2.275 .332 -.391 -6.853 .000

Pay-Out Ratio Avg. 05-07 .002 .005 .023 .397 .692


Page | 62

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .183a .033 .026 15.991

a. Predictors: (Constant), Pay-Out Ratio Avg. 08-10, Dividend Yield

Avg. 08-10

ANOVAa


1

Regression 2455.828 2 1227.914 4.802 .009b

Residual 71084.421 278 255.699

Total 73540.249 280



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 55.040 1.820 30.236 .000


Pay-Out Ratio Avg. 08-10 -.017 .012 -.086 -1.379 .169


Page | 63

Average 2005-2010.

Model Summary


Square

Std. Error of

the Estimate

1 .275a .076 .069 10.291


Yield Avg. 05-10

ANOVAa


1

Regression 2421.982 2 1210.991 11.435 .000b

Residual 29652.124 280 105.900

Total 32074.106 282



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 44.836 1.274 35.186 .000


Pay-Out Ratio Avg. 05-10 -.014 .010 -.088 -1.432 .153


Page | 64


relationship between dividend yield and dividend pay-out ratio with Tobin Q.

Average 2005-2007.

Model Summary


Square

Std. Error of

the Estimate

1 .217a .047 .040 .917


Yield Avg. 05-07

ANOVAa


1

Regression 11.496 2 5.748 6.836 .001b

Residual 232.901 277 .841

Total 244.396 279

a. Dependent Variable: Tobin Q's Avg. 05-07


Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.306 .113 20.362 .000

Dividend Yield Avg. 05-07 -.144 .039 -.223 -3.690 .000

Pay-Out Ratio Avg. 05-07 .000 .001 .041 .670 .503


Page | 65

Average 2008-2010.

Model Summary


Square

Std. Error of

the Estimate

1 .239a .057 .050 .704


Yield Avg. 08-10

ANOVAa


1

Regression 8.348 2 4.174 8.431 .000b

Residual 137.644 278 .495

Total 145.993 280



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.734 .080 21.648 .000


Pay-Out Ratio Avg. 08-10 .000 .001 .053 .853 .395


Page | 66

Average 2005-2010.

Model Summary


Square

Std. Error of

the Estimate

1 .250a .063 .056 .812


Yield Avg. 05-10

ANOVAa


1

Regression 12.337 2 6.169 9.353 .000b

Residual 184.673 280 .660

Total 197.011 282



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.013 .101 20.013 .000


Pay-Out Ratio Avg. 05-10 .001 .001 .100 1.622 .106


Page | 67


relationship between dividend yield and dividend pay-out ratio with ROA

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .150a .023 .015 7.479

a. Predictors: (Constant), Pay-Out Ratio Avg. 05-07, Dividend Yield Avg.

05-07

.

ANOVAa


1

Regression 357.441 2 178.720 3.195 .042b

Residual 15493.930 277 55.935

Total 15851.371 279

a. Dependent Variable: ROA Avg. 05-07


Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 5.345 .924 5.786 .000

Dividend Yield Avg. 05-07 .784 .317 .151 2.470 .014

Pay-Out Ratio Avg. 05-07 .000 .005 -.005 -.083 .934


Page | 68

Average 2008-2010.

Model Summary


Square

Std. Error of

the Estimate

1 .119a .014 .007 7.011

a. Predictors: (Constant), Pay-Out Ratio Avg. 08-10, Dividend Yield

Avg. 08-10

ANOVAa


1

Regression 195.259 2 97.629 1.986 .139b

Residual 13614.652 277 49.150

Total 13809.911 279



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 3.522 .801 4.398 .000


Pay-Out Ratio Avg. 08-10 -.003 .005 -.036 -.571 .569


Page | 69

Average 2005-2010

Model Summary

Model R R Square Adjusted R Square Std. Error of the

Estimate

1 .126a .016 .009 6.291

a. Predictors: (Constant), Pay-Out Ratio Avg. 05-10, Dividend Yield Avg. 05-10

ANOVAa


1

Regression 179.143 2 89.572 2.263 .106b

Residual 11041.708 279 39.576

Total 11220.851 281



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.634 .784 5.907 .000


Pay-Out Ratio Avg. 05-10 .005 .006 .049 .775 .439


Page | 70


relationship between dividend yield, dividend pay-out ratio and debt ratio with


Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .390a .152 .142 7.848

a. Predictors: (Constant), Debt Ratio Avg. 05-07, Dividend Yield Avg. 05-

07, Pay-Out Ratio Avg. 05-07

ANOVAa


1

Regression 2997.582 3 999.194 16.223 .000b

Residual 16753.056 272 61.592

Total 19750.638 275


b. Predictors: (Constant), Debt Ratio Avg. 05-07, Dividend Yield Avg. 05-07, Pay-Out Ratio Avg.

05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 34.457 .981 35.111 .000


Pay-Out Ratio Avg. 05-07 .005 .006 .062 .896 .371

Debt Ratio Avg. 05-07 -.002 .002 -.069 -1.031 .303


Page | 71

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .186a .035 .024 16.070

a. Predictors: (Constant), Debt Ratio Avg. 08-10, Pay-Out Ratio Avg.

08-10, Dividend Yield Avg. 08-10

ANOVAa


1

Regression 2527.100 3 842.367 3.262 .022b

Residual 70501.391 273 258.247

Total 73028.491 276


b. Predictors: (Constant), Debt Ratio Avg. 08-10, Pay-Out Ratio Avg. 08-10, Dividend Yield Avg.

08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 55.141 1.864 29.586 .000


Pay-Out Ratio Avg. 08-10 -.016 .012 -.084 -1.324 .187

Debt Ratio Avg. 08-10 .000 .003 .005 .078 .938


Page | 72

Average 2005-2010.

Model Summary


Square

Std. Error of

the Estimate

1 .280a .078 .068 10.300

a. Predictors: (Constant), Debt Ratio Avg. 05-10, Dividend

Yield Avg. 05-10, Pay-Out Ratio Avg. 05-10

ANOVAa


1

Regression 2506.736 3 835.579 7.876 .000b

Residual 29494.048 278 106.094

Total 32000.784 281



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 45.024 1.288 34.943 .000


Pay-Out Ratio Avg. 05-10 -.013 .010 -.083 -1.353 .177

Debt Ratio Avg. 05-10 -.002 .002 -.050 -.854 .394


Page | 73



Tobin Q.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .244a .059 .049 .919

a. Predictors: (Constant), Debt Ratio Avg. 05-07, Dividend Yield Avg.

05-07, Pay-Out Ratio Avg. 05-07

ANOVAa


1

Regression 14.519 3 4.840 5.727 .001b

Residual 229.868 272 .845

Total 244.388 275



05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.296 .115 19.975 .000


Pay-Out Ratio Avg. 05-07 .000 .001 -.033 -.450 .653

Debt Ratio Avg. 05-07 .000 .000 .129 1.826 .069


Page | 74

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .248a .061 .051 .701



ANOVAa


1

Regression 8.759 3 2.920 5.947 .001b

Residual 134.014 273 .491

Total 142.773 276



08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.730 .081 21.287 .000


Pay-Out Ratio Avg. 08-10 .001 .001 .061 .980 .328

Debt Ratio Avg. 08-10 2.179E-005 .000 .011 .180 .857


Page | 75

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .257a .066 .056 .813

a. Predictors: (Constant), Debt Ratio Avg. 05-10, Dividend Yield Avg. 05-

10, Pay-Out Ratio Avg. 05-10

ANOVAa


1

Regression 13.008 3 4.336 6.554 .000b

Residual 183.904 278 .662

Total 196.911 281



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.997 .102 19.629 .000


Pay-Out Ratio Avg. 05-10 .001 .001 .094 1.515 .131

Debt Ratio Avg. 05-10 .000 .000 .058 .991 .322


Page | 76



ROA.

Average 2005-2007

Model Summary


Square

Std. Error of the

Estimate

1 .185a .034 .024 7.480



ANOVAa


1

Regression 541.490 3 180.497 3.226 .023b

Residual 15219.423 272 55.954

Total 15760.913 275



05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 5.287 .935 5.652 .000


Pay-Out Ratio Avg. 05-07 -.006 .006 -.084 -1.139 .256

Debt Ratio Avg. 05-07 .004 .002 .137 1.902 .058


Page | 77

Average 2008-2010

Model Summary


Square

Std. Error of the

Estimate

1 .114a .013 .002 7.026



ANOVAa


1

Regression 177.192 3 59.064 1.196 .312b

Residual 13427.968 272 49.368

Total 13605.159 275



08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 3.722 .818 4.551 .000


Pay-Out Ratio Avg. 08-10 -.003 .005 -.035 -.539 .590

Debt Ratio Avg. 08-10 -.001 .001 -.044 -.732 .464


Page | 78

Average 2005-2010

Model Summary


Square

Std. Error of the

Estimate

1 .128a .016 .006 6.312



ANOVAa


1

Regression 184.457 3 61.486 1.543 .204b

Residual 11035.515 277 39.839

Total 11219.972 280



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.590 .795 5.773 .000


Pay-Out Ratio Avg. 05-10 .004 .006 .047 .734 .463

Debt Ratio Avg. 05-10 .001 .002 .021 .355 .723


Page | 79


relationship between dividend yield, dividend pay-out ratio and board of

directors’ size with share price volatility.

Average 2005-2007.

ANOVAa


1

Regression 3417.706 3 1139.235 19.448 .000b

Residual 14527.258 248 58.578

Total 17944.964 251


b. Predictors: (Constant), Board Size Avg. 05-07, Dividend Yield Avg. 05-07, Pay-Out Ratio Avg.

05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 40.543 2.078 19.515 .000


Pay-Out Ratio Avg. 05-07 .001 .005 .009 .156 .876

Board Size Avg. 05-07 -.703 .204 -.198 -3.455 .001


Model Summary


Square

Std. Error of

the Estimate

1 .436a .190 .181 7.654

a. Predictors: (Constant), Board Size Avg. 05-07, Dividend Yield

Avg. 05-07, Pay-Out Ratio Avg. 05-07

Page | 80

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .329a .108 .098 14.720

a. Predictors: (Constant), Board Size Avg. 08-10, Pay-Out Ratio Avg.


ANOVAa


1

Regression 6664.836 3 2221.612 10.253 .000b

Residual 54817.725 253 216.671

Total 61482.560 256


b. Predictors: (Constant), Board Size Avg. 08-10, Pay-Out Ratio Avg. 08-10, Dividend Yield Avg.

08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 68.955 4.101 16.813 .000


Pay-Out Ratio Avg. 08-10 -.029 .012 -.153 -2.426 .016

Board Size Avg. 08-10 -1.526 .413 -.219 -3.693 .000


Page | 81

Average 2005-2010

Model Summary


Square

Std. Error of the

Estimate

1 .394a .155 .145 9.585

a. Predictors: (Constant), Board Size Avg. 05-10, Dividend Yield Avg.


ANOVAa


1

Regression 4313.420 3 1437.807 15.650 .000b

Residual 23519.545 256 91.873

Total 27832.965 259



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 55.663 2.736 20.344 .000


Pay-Out Ratio Avg. 05-10 -.018 .009 -.120 -1.967 .050

Board Size Avg. 05-10 -1.204 .270 -.257 -4.461 .000


Page | 82



directors’ size with Tobin Q.

Average 2005-2007

Model Summary


Square

Std. Error of the

Estimate

1 .231a .053 .042 .941



ANOVAa


1

Regression 12.292 3 4.097 4.628 .004b

Residual 218.672 247 .885

Total 230.964 250



05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.441 .256 9.549 .000


Pay-Out Ratio Avg. 05-07 .000 .001 .030 .465 .642

Board Size Avg. 05-07 -.006 .025 -.016 -.259 .796


Page | 83

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .246a .060 .049 .722



ANOVAa


1

Regression 8.459 3 2.820 5.413 .001b

Residual 131.790 253 .521

Total 140.249 256



08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.774 .201 8.822 .000


Pay-Out Ratio Avg. 08-10 .001 .001 .076 1.176 .241

Board Size Avg. 08-10 .001 .020 .002 .029 .977


Page | 84

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .261a .068 .057 .829



ANOVAa


1

Regression 12.836 3 4.279 6.220 .000b

Residual 176.102 256 .688

Total 188.938 259



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.083 .237 8.799 .000


Pay-Out Ratio Avg. 05-10 .001 .001 .104 1.626 .105

Board Size Avg. 05-10 -.001 .023 -.002 -.036 .971


Page | 85



directors’ size with ROA.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .145a .021 .009 7.563



ANOVAa


1

Regression 302.547 3 100.849 1.763 .155b

Residual 14127.612 247 57.197

Total 14430.159 250



05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 3.792 2.054 1.846 .066


Pay-Out Ratio Avg. 05-07 4.904E-005 .005 .001 .010 .992

Board Size Avg. 05-07 .234 .201 .073 1.160 .247


Page | 86

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .116a .014 .002 7.039



ANOVAa


1

Regression 171.415 3 57.138 1.153 .328b

Residual 12487.319 252 49.553

Total 12658.734 255



08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.508 1.963 1.278 .203


Pay-Out Ratio Avg. 08-10 .001 .006 .011 .163 .870

Board Size Avg. 08-10 .146 .198 .046 .734 .463


Page | 87

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .132a .017 .006 6.324



ANOVAa


1

Regression 180.943 3 60.314 1.508 .213b

Residual 10199.813 255 39.999

Total 10380.757 258



05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 3.196 1.805 1.771 .078


Pay-Out Ratio Avg. 05-10 .006 .006 .062 .942 .347

Board Size Avg. 05-10 .211 .178 .074 1.183 .238


Page | 88


relationship between dividend yield, dividend pay-out ratio and market

capitalisation with share price volatility.

Average 2005-2007

Model Summary


Square

Std. Error of the

Estimate

1 .427a .182 .174 7.758

a. Predictors: (Constant), Market Cap. Avg. 05-07, Pay-Out Ratio Avg.


ANOVAa


1

Regression 3731.537 3 1243.846 20.668 .000b

Residual 16730.378 278 60.181

Total 20461.915 281


b. Predictors: (Constant), Market Cap. Avg. 05-07, Pay-Out Ratio Avg. 05-07, Dividend Yield

Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 34.796 .952 36.563 .000


Pay-Out Ratio Avg. 05-07 .001 .005 .013 .240 .811

Market Cap. Avg. 05-07 .000 .000 -.183 -3.375 .001


Page | 89

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .245a .060 .050 15.798



ANOVAa


1

Regression 4404.327 3 1468.109 5.882 .001b

Residual 69135.922 277 249.588

Total 73540.249 280



Avg. 08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 55.779 1.818 30.684 .000


Pay-Out Ratio Avg. 08-10 -.018 .012 -.090 -1.458 .146

Market Cap. Avg. 08-10 .000 .000 -.163 -2.794 .006


Page | 90

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .340a .115 .106 10.084

a. Predictors: (Constant), Market Cap. Avg. 05-10, Dividend Yield Avg.


ANOVAa


1

Regression 3703.905 3 1234.635 12.142 .000b

Residual 28370.201 279 101.685

Total 32074.106 282


b. Predictors: (Constant), Market Cap. Avg. 05-10, Dividend Yield Avg. 05-10, Pay-Out Ratio

Avg. 05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 45.476 1.262 36.047 .000


Pay-Out Ratio Avg. 05-10 -.015 .010 -.096 -1.607 .110

Market Cap. Avg. 05-10 .000 .000 -.200 -3.551 .000


Page | 91



capitalisation with Tobin Q.

Average 2005-2007

Model Summary


Square

Std. Error of the

Estimate

1 .235a .055 .045 .915



ANOVAa


1

Regression 13.542 3 4.514 5.397 .001b

Residual 230.854 276 .836

Total 244.396 279



Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.284 .114 20.063 .000


Pay-Out Ratio Avg. 05-07 .000 .001 .045 .747 .456

Market Cap. Avg. 05-07 7.086E-006 .000 .092 1.564 .119


Page | 92

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .264a .070 .060 .700



ANOVAa


1

Regression 10.212 3 3.404 6.944 .000b

Residual 135.781 277 .490

Total 145.993 280



Avg. 08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.711 .081 21.241 .000


Pay-Out Ratio Avg. 08-10 .000 .001 .055 .900 .369

Market Cap. Avg. 08-10 6.438E-006 .000 .113 1.950 .052


Page | 93

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .269a .072 .062 .809



ANOVAa


1

Regression 14.253 3 4.751 7.253 .000b

Residual 182.758 279 .655

Total 197.011 282



Avg. 05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.988 .101 19.631 .000


Pay-Out Ratio Avg. 05-10 .001 .001 .104 1.697 .091

Market Cap. Avg. 05-10 6.740E-006 .000 .099 1.710 .088


Page | 94



capitalisation with ROA.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .196a .038 .028 7.431



ANOVAa


1

Regression 609.355 3 203.118 3.678 .013b

Residual 15242.016 276 55.225

Total 15851.371 279



Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 5.100 .925 5.513 .000


Pay-Out Ratio Avg. 05-07 9.418E-005 .005 .001 .020 .984

Market Cap. Avg. 05-07 7.861E-005 .000 .126 2.136 .034


Page | 95

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .185a .034 .024 6.951



ANOVAa


1

Regression 474.222 3 158.074 3.272 .022b

Residual 13335.688 276 48.318

Total 13809.911 279



Avg. 08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 3.243 .802 4.042 .000


Pay-Out Ratio Avg. 08-10 -.003 .005 -.033 -.521 .603

Market Cap. Avg. 08-10 7.878E-005 .000 .142 2.403 .017


Page | 96

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .206a .042 .032 6.217



ANOVAa


1

Regression 474.387 3 158.129 4.091 .007b

Residual 10746.464 278 38.656

Total 11220.851 281



Avg. 05-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.329 .783 5.528 .000


Pay-Out Ratio Avg. 05-10 .005 .006 .056 .899 .370

Market Cap. Avg. 05-10 8.367E-005 .000 .162 2.764 .006


Page | 97


relationship between dividend yield, dividend pay-out ratio and industry type

with share price volatility.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .387a .150 .141 7.910

a. Predictors: (Constant), Industries , Pay-Out Ratio Avg. 05-07,

Dividend Yield Avg. 05-07

ANOVAa


1

Regression 3066.149 3 1022.050 16.333 .000b

Residual 17395.766 278 62.575

Total 20461.915 281


b. Predictors: (Constant), Industries , Pay-Out Ratio Avg. 05-07, Dividend Yield Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 35.032 1.491 23.492 .000


Pay-Out Ratio Avg. 05-07 .002 .005 .024 .416 .678

Industries -.147 .258 -.032 -.569 .570


Page | 98

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .277a .077 .067 15.656

a. Predictors: (Constant), Pay-Out Ratio Avg. 08-10, Industries ,


ANOVAa


1

Regression 5643.182 3 1881.061 7.674 .000b

Residual 67897.067 277 245.116

Total 73540.249 280


b. Predictors: (Constant), Pay-Out Ratio Avg. 08-10, Industries , Dividend Yield Avg. 08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 62.557 2.743 22.809 .000

Industries -1.847 .512 -.209 -3.606 .000


Pay-Out Ratio Avg. 08-10 -.020 .012 -.101 -1.640 .102


Page | 99

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .319a .102 .092 10.163



ANOVAa


1

Regression 3257.445 3 1085.815 10.513 .000b

Residual 28816.661 279 103.286

Total 32074.106 282



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 48.712 1.855 26.259 .000

Industries -.941 .331 -.162 -2.844 .005


Pay-Out Ratio Avg. 05-10 -.015 .010 -.093 -1.537 .125


Page | 100



with Tobin Q.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .230a .053 .043 .916

a. Predictors: (Constant), Industries , Pay-Out Ratio Avg. 05-07,


ANOVAa


1

Regression 12.937 3 4.312 5.142 .002b

Residual 231.460 276 .839

Total 244.396 279


b. Predictors: (Constant), Industries , Pay-Out Ratio Avg. 05-07, Dividend Yield Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.133 .174 12.275 .000


Pay-Out Ratio Avg. 05-07 .000 .001 .038 .624 .533

Industries .039 .030 .077 1.311 .191


Page | 101

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .240a .058 .048 .705



ANOVAa


1

Regression 8.442 3 2.814 5.666 .001b

Residual 137.551 277 .497

Total 145.993 280



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.693 .123 13.718 .000

Industries .010 .023 .025 .433 .665


Pay-Out Ratio Avg. 08-10 .000 .001 .054 .878 .381


Page | 102

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .261a .068 .058 .811



ANOVAa


1

Regression 13.422 3 4.474 6.799 .000b

Residual 183.589 279 .658

Total 197.011 282



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.873 .148 12.648 .000

Industries .034 .026 .074 1.284 .200


Pay-Out Ratio Avg. 05-10 .001 .001 .102 1.663 .097


Page | 103



with ROA.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .152a .023 .012 7.491



ANOVAa


1

Regression 364.220 3 121.407 2.164 .093b

Residual 15487.151 276 56.113

Total 15851.371 279



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 5.720 1.421 4.024 .000

Industries -.086 .246 -.021 -.348 .728


Pay-Out Ratio Avg. 05-07 .000 .005 -.004 -.070 .944


Page | 104

Average 2008-2010

Model Summary


Square

Std. Error of the

Estimate

1 .152a .023 .012 6.992



ANOVAa


1

Regression 318.611 3 106.204 2.173 .091b

Residual 13491.300 276 48.882

Total 13809.911 279



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.044 1.226 1.667 .097

Industries .367 .231 .095 1.589 .113


Pay-Out Ratio Avg. 08-10 -.002 .005 -.029 -.455 .650


Page | 105

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .131a .017 .007 6.298



ANOVAa


1

Regression 192.393 3 64.131 1.617 .186b

Residual 11028.458 278 39.671

Total 11220.851 281



Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.148 1.150 3.608 .000

Industries .119 .207 .034 .578 .564


Pay-Out Ratio Avg. 05-10 .005 .006 .050 .794 .428


Page | 106


relationship between dividend yield, dividend pay-out ratio, industry type, board

of directors’ size, market capitalisation and debt ratio with share price volatility.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .450a .203 .183 7.565

a. Predictors: (Constant), Dividend Yield Avg. 05-07, Board Size Avg.

05-07, Industries , Debt Ratio Avg. 05-07, Market Cap. Avg. 05-07,

Pay-Out Ratio Avg. 05-07

ANOVAa


1

Regression 3488.878 6 581.480 10.160 .000b

Residual 13736.401 240 57.235

Total 17225.279 246


b. Predictors: (Constant), Dividend Yield Avg. 05-07, Board Size Avg. 05-07, Industries , Debt

Ratio Avg. 05-07, Market Cap. Avg. 05-07, Pay-Out Ratio Avg. 05-07

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 39.954 2.662 15.012 .000

Pay-Out Ratio Avg. 05-07 .002 .006 .027 .369 .712

Industries -.328 .265 -.072 -1.240 .216

Market Cap. Avg. 05-07 -8.347E-005 .000 -.128 -1.863 .064

Board Size Avg. 05-07 -.451 .243 -.129 -1.859 .064

Debt Ratio Avg. 05-07 -.001 .002 -.030 -.427 .670



Page | 107

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .415a .172 .152 14.303


08-10, Industries , Debt Ratio Avg. 08-10, Pay-Out Ratio Avg. 08-10,

Market Cap. Avg. 08-10

ANOVAa


1

Regression 10487.654 6 1747.942 8.545 .000b

Residual 50528.366 247 204.568

Total 61016.020 253



Ratio Avg. 08-10, Pay-Out Ratio Avg. 08-10, Market Cap. Avg. 08-10

Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 75.676 4.873 15.529 .000

Industries -2.065 .490 -.246 -4.211 .000

Board Size Avg. 08-10 -1.263 .472 -.182 -2.677 .008

Pay-Out Ratio Avg. 08-10 -.030 .012 -.160 -2.590 .010

Market Cap. Avg. 08-10 .000 .000 -.098 -1.453 .148

Debt Ratio Avg. 08-10 .000 .003 .007 .111 .912



Page | 108

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .453a .205 .186 9.358




ANOVAa


1

Regression 5697.588 6 949.598 10.843 .000b

Residual 22069.702 252 87.578

Total 27767.290 258




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 59.326 3.326 17.839 .000

Industries -1.172 .318 -.209 -3.685 .000

Board Size Avg. 05-10 -1.018 .318 -.218 -3.202 .002

Pay-Out Ratio Avg. 05-10 -.019 .009 -.125 -2.077 .039

Market Cap. Avg. 05-10 -8.947E-005 .000 -.110 -1.641 .102

Debt Ratio Avg. 05-10 -.001 .002 -.021 -.369 .713



Page | 109



of directors’ size, market capitalisation and debt ratio with Tobin Q.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .292a .085 .063 .938




ANOVAa


1

Regression 19.720 6 3.287 3.734 .001b

Residual 211.243 240 .880

Total 230.964 246




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.551 .330 7.730 .000

Industries .037 .033 .071 1.140 .256

Market Cap. Avg. 05-07 1.094E-005 .000 .145 1.968 .050

Board Size Avg. 05-07 -.042 .030 -.105 -1.404 .162

Pay-Out Ratio Avg. 05-07 .000 .001 -.053 -.689 .491

Debt Ratio Avg. 05-07 .000 .000 .145 1.918 .056



Page | 110

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .291a .084 .062 .714




ANOVAa


1

Regression 11.606 6 1.934 3.796 .001b

Residual 125.858 247 .510

Total 137.465 253




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.854 .243 7.622 .000

Industries .019 .024 .048 .777 .438

Board Size Avg. 08-10 -.021 .024 -.063 -.878 .381

Pay-Out Ratio Avg. 08-10 .001 .001 .089 1.366 .173

Market Cap. Avg. 08-10 8.238E-006 .000 .148 2.082 .038

Debt Ratio Avg. 08-10 5.829E-005 .000 .028 .456 .649



Page | 111

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .302a .091 .070 .825




ANOVAa


1

Regression 17.231 6 2.872 4.217 .000b

Residual 171.626 252 .681

Total 188.857 258




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.156 .293 7.350 .000

Industries .037 .028 .080 1.313 .191

Board Size Avg. 05-10 -.032 .028 -.084 -1.151 .251

Pay-Out Ratio Avg. 05-10 .001 .001 .098 1.522 .129

Market Cap. Avg. 05-10 9.734E-006 .000 .145 2.024 .044

Debt Ratio Avg. 05-10 .000 .000 .076 1.217 .225



Page | 112



of directors’ size, market capitalisation and debt ratio with ROA.

Average 2005-2007.

Model Summary


Square

Std. Error of the

Estimate

1 .203a .041 .017 7.567




ANOVAa


1

Regression 592.530 6 98.755 1.725 .116b

Residual 13741.527 240 57.256

Total 14334.057 246




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 6.082 2.662 2.285 .023

Industries -.017 .265 -.004 -.065 .948

Market Cap. Avg. 05-07 7.671E-005 .000 .129 1.712 .088

Board Size Avg. 05-07 -.048 .243 -.015 -.196 .845

Pay-Out Ratio Avg. 05-07 -.006 .006 -.075 -.954 .341

Debt Ratio Avg. 05-07 .003 .002 .133 1.709 .089



Page | 113

Average 2008-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .202a .041 .017 6.997




ANOVAa


1

Regression 511.891 6 85.315 1.743 .112b

Residual 12042.789 246 48.954

Total 12554.680 252




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.541 2.399 1.059 .290

Industries .392 .242 .102 1.619 .107

Market Cap. Avg. 08-10 8.571E-005 .000 .162 2.209 .028

Board Size Avg. 08-10 -.066 .232 -.021 -.286 .775

Pay-Out Ratio Avg. 08-10 .002 .006 .020 .302 .763

Debt Ratio Avg. 08-10 .000 .001 -.024 -.378 .706



Page | 114

Average 2005-2010.

Model Summary


Square

Std. Error of the

Estimate

1 .200a .040 .017 6.300




ANOVAa


1

Regression 416.860 6 69.477 1.750 .110b

Residual 9963.439 251 39.695

Total 10380.298 257




Coefficientsa


Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.402 2.244 1.961 .051

Industries .179 .216 .052 .827 .409

Market Cap. Avg. 05-10 8.584E-005 .000 .172 2.338 .020

Board Size Avg. 05-10 -.048 .215 -.017 -.225 .822

Pay-Out Ratio Avg. 05-10 .006 .006 .061 .923 .357

Debt Ratio Avg. 05-10 .001 .002 .026 .399 .690

Dividend Yield Avg. 05-10 .257 .258 .066 .997 .320


Page | 115

Documents

Dividend policy and firm performance