a research paper on impact of dividend payout on ...viz, investment decisions, financing decisions,...

A Research Paper on Impact of Dividend

Payout on Shareholders Wealth in Indian

Industries1P.G. Thirumagal and

2S. Vasantha

1School of Management Studies,

Vels Institute of Science, Technology and Advanced Studies,

Chennai, India.

[email protected]

2School of Management Studies,

Vels Institute of Science, Technology and Advanced Studies,

Chennai, India.

[email protected]

Abstract This research paper analysed the impact of dividend payout on

shareholders wealth for five important industries in India viz, Automobile,

Infrastructure & Construction, Energy, Information Technology and

Pharmaceutical industry as well the effect of dividend announcement on

share price using 15 years data from 2001 to 2015. Panel data regression

and Paired t test was used. It was found that dividend payout had

significant negative impact on shareholders wealth for majority of the

industries. There was significant difference in share price between pre and

post dividend announcement.

Key Words:Dividend, shareholders wealth, dividend announcement,

Panel regression, TOBINSQ.

International Journal of Pure and Applied MathematicsVolume 118 No. 5 2018, 65-97ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

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1. Introduction

Dividend is derived from the Latin word “Dividendum”. This means “that which

is to be distributed”. Earnings distribution to the shareholders according to their

ownership proportion is called as Dividend. All the shareholders of the company

have share in dividend based on their ownership proportion in the company.

Dividend decision or dividend policy is defined as the ratio of retained earnings

to the distributed earnings. Dividend decision is interrelated with other three

decision viz investment decisions, financing decisions and liquidity decisions.

Companies decide the proportion of earning to be distributed as dividend and

proportion of earnings to be retained with the objective of wealth maximization

of shareholders. The companies should find out the optimum dividend payout

with risk return trade off leading to the objective of shareholders wealth

maximization. The firms have to decide the form and timing of dividend

payment.

According to Allen et al (2000), “Although a number of theories have been put

forward in the literature to explain their pervasive presence, dividends remain

one of the horniest puzzles in corporate finance”. Even Frankfurter et al (2002)

concluded that “The dividend puzzle both as a share value enhancing and as a

matter of policy is one of the most challenging topics of modern finance/

financial economics. Forty years of research… has not been able to resolve it”

The scope of financial management and the functions of finance manager have

undergone changes in the last few decades but the goal or objective of the

company remains unchanged. The main objective of the firm is shareholders

wealth maximization. It is represented by the positive net present value of the

financial decisions. According to Azhagaiah & Sabaripriya (2008) Shareholders

think the wealth is created by increase in the firm’s market price of the share.

Even many researchers have proved the same. All the four financial decisions

viz, Investment decisions, financing decisions, Dividend decisions and Liquidity

decisions decide the value of the firm. All the four decisions together contribute

in the wealth creation for shareholders. Dividend decision is one of the

important financial decisions that contribute in shareholders wealth creation.

There are some dividend theories which prove that dividend decision affects the

market value of the firm while others disprove it. Those who proved the

relationship between dividend decision and value of the firm often link dividend

decision with the investment opportunities of the firm.

If there are good and profitable investment opportunities, retention of earnings

would be a better option than dividend distribution. This would increase the

value of the firm. If there are no better investment opportunities, dividend

distribution would be a better choice for the management. Shareholder wealth is

International Journal of Pure and Applied Mathematics Special Issue

66

created if there is increase in the market value of the firm. It is the function of all

the four decisions of the firm. Finance manager should identify optimum

dividend policy that maximizes shareholders wealth by increase in the market

value of the firm. This study would analyse the impact of dividend determinants

on the shareholders wealth

According to Pettit (1972), market price of shares changes to the change in

dividend announcements. Gordon (1959, 1962) and Vickery (1978) found that

there were positive abnormal returns after dividend payment announcements.

Easton and Sinclair (1989) found that there was negative reaction of stock prices

on dividend announcements. Uddin and Chowdhury (2005) analysed and found

that there was no information content of dividend announcement. It was found

that based on the previous literature dividend announcement’s impact on market

price of share had shown a mixed reaction. In this study, the impact of dividend

announcement on the market price of share was analysed through year wise and

market capitalization wise. The main objective of this research is to examine the

impact of dividend payout and its determinants on the Shareholders wealth and

to analyze the effect of dividend announcement on the market price of share.

2. Literature Review

TOBINSQ is a measure of shareholders wealth and firm performance. Pruitt and

Chung (1994) explained the simple approximation of Tobins’q. It was suggested

that there was similarities between approximate q, MVA and EVA.

Approximate was identified as standardized performance measure. Kakani et al

(2001) studied the determinants of financial performance of Indian corporate

sector in the post liberalization era for 566 companies during 1992 to 2000. The

researchers used and suggested TOBINS’Q as measure of shareholders wealth

which is a more appealing measure than accounting returns (Wernerfelt &

Montgomery, 1988). Amidu (2007) used TOBINS’Q as a measure of firm

performance for the firms listed in Ghana Stock Exchange. Ben et al (2013)

analysed the relationship between director remuneration and performance of

firms listed in the Nairobi Securities Exchange. TOBINS’Q was used one of the

firm performance measure. Odongo et al (2014) examined the impact of capital

structure and profitability on Kenyan listed firm performance which was

measured as TOBINS’Q. Sweety and Kaur (2014) examined the impact of firm

specific attributes on shareholders wealth creation of 100 Indian companies

during 1997 to 2009. The researchers used EVA (Economic Value Added), an

accounting based measure, MVA (Market Value Added) and TOBINS’Q, a

market based measure as proxy for shareholder wealth creation. It was found

that the selected attributes explained 34% variation in EVA and 55% variation

on MVA and TOBINS’Q. Mitharshana (2015) analysed the impact of firm

characteristics on firm performance. He used Tobins’q as a measure of firm

performance and found that leverage was positively significant at 1% whereas


67

Asset tangibility was negatively significant at 10% level with Tobins’q.

Liquidity and Firm size were insignificant. Kirubalini (2015) examined the

impact of corporate governance variables and firm size on Tobins’q, a measure

of firm performance. Firm size was insignificant with firm performance. Robert

and Mukras (2015) analysed the financial leverage and performance of listed

firms in a frontier market from Kenya during 2007 to 2011. TOBINS’Q was

used as measure of financial performance and it was found that financial

leverage and ownership concentration were negatively significant and tangibility

was positively significant with TOBINS’Q.

Gitundu et al (2015) examined the influence of change in corporate governance

on financial performance of 55 privatized companies in Kenya during 2007 to

2013. Tobins’Q was used as measure of financial performance. Board

composition was positively significant and board size was negatively significant

with TOBINS’Q. Azhagaiah and Sabari Priya (2008) observed the impact of

dividend policy on shareholders wealth for 28 companies listed in NSE during

1997 to 2006. Dividend per share was used as proxy of dividend policy and

market price per share was used as proxy for shareholders wealth. Dividend

policy was positively significant with shareholders wealth for organic chemical

companies whereas insignificant for inorganic chemical companies. Shahid Ali

et al (2010) analysed the impact of dividend policy on shareholders wealth of 68

companies listed in Karachi Stock Exchange during 2002 to 2008. Annual stock

return was used as measure of shareholders wealth whereas dividend payout

ratio, Size of the firm, Price earnings ratio, Growth and Profitability were used

as independent variables. Through fixed effect model, for companies with the

year ended June, dividend payout ratio was insignificant, profitability and price

earnings ratio were positively significant whereas firm size was negatively

significant with shareholders wealth. Companies with the year ended December,

Growth alone positively significant with shareholders wealth. Sujata Kapoor

(2010) investigated the impact of dividend policy on shareholders wealth of

Indian firms in IT sector, FMCG sector and Service sector. Event study was used

to find out the impact of dividend policy on shareholders wealth. In FMCG

sector and Service sector, cash dividend announcement has an impact on market

value of shares represented as shareholders wealth.

Shaveta Gupta (2011) analysed the management considerations and factors

affecting dividend decisions of Indian Engineering industry, FMCG industry, IT

and Textile industry during 2004 to 2008. Market value to Book value of share

was used as measure of shareholders wealth. For all the years and for all the

industries, dividend pay-out ratio was negatively significant with shareholders

wealth except for Textile industry, dividend payout ratio was negatively

significant only for the year 2006. Gul et al (2012) examined the relationship

between dividend policy and shareholders wealth of 75 companies listed in

Karachi stock exchange during 2005 to 2010. Market price of share was the

proxy of shareholders wealth and dividend per share, lagged price earnings per


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ratio, retained earnings and lagged market price per share was used as

independent variables. The average market value to book value of equity for

dividend paying companies was very high when compared to non-dividend

paying companies. Through multiple regression and Stepwise regression it was

found that dividend per share and lagged market price per share were positively

significant with shareholders wealth whereas retained earnings and lagged price

earnings ratio were negatively insignificant with shareholders wealth. Mistry

(2012) analysed the impact of dividend policy on shareholders wealth of

selected major pharmaceutical units in India during 2001 to 2009. It was found

that five companies have positive significant impact of dividend payout ratio on

shareholders wealth which was measured through Net worth. Bawa and Kaur

(2013) observed the impact of dividend policy on shareholders wealth of Indian

Information Technology sector during 2006 to 2010. Market price per share was

used as proxy for shareholders wealth whereas dividend per share, retained

earnings per share, lagged price earnings ratio and lagged market price per share

was used as independent variables. There was significant difference in the

market to book value of dividend paying companies and dividend non-paying

companies. Fixed effect panel regression has shown that dividend per share,

retained earnings per share and lagged market price per share were positively

significant with shareholders wealth.

Chidinma et al (2013) analysed the impact of dividend policy on shareholders

wealth from 216 public companies in Nigeria during 2000 to 2011. It was

observed that dividend policy impacted the shareholders wealth. Sarwar (2013)

examined the effect of dividend policy on shareholders wealth in 33 listed

companies of sugar industries of Pakistan during 2006 to 2011. Market price per

share was used as measure of shareholders wealth whereas dividend per share,

earnings per share, lagged market price per share, price earnings ratio, lagged

price earnings ratio and retained earnings was used as independent variables.

Through least square regression it was found that dividend per share, earnings

per share and lagged market price per share were positively significant while

lagged price earnings ratio had negatively significant impact on shareholders

wealth. De Wet and Mpinda (2013) found the impact of dividend payments on

shareholders wealth using Vector error correction model for 46 companies listed

on Johannesburg securities exchange during 1995 to 2010. Dividend yield had

significant positive impact on market price of share whereas Earnings per share

was insignificant with shareholders wealth. Kai et al (2014) studied the impact

of dividend policy on shareholders wealth from 59 Malaysia’s listed food

producer sector during 2008 to 2012. Earnings per share was used as proxy for

shareholders wealth whereas dividend payout ratio, earnings volatility, long term

debt ratio, growth in assets, profitability and liquidity were used as independent

variables. Dividend payout ratio and long term debt ratio were negatively

significant whereas earnings volatility and profitability were positively

significant with shareholders wealth. Growth in assets and liquidity were


69

insignificant with shareholders wealth.


70

Iqbal et al (2014) examined the impact of dividend policy on shareholders

wealth of 35 selected manufacturing industries of Pakistan during 2006 to 2011.

OLS presented that dividend per share, growth and size of the firm were

positively significant with shareholders wealth which was measured as market

capitalization. Kumaresan (2014) analysed the impact of dividend policy on

shareholders wealth of top ten listed companies in Hotels and Travels sector of

Sri Lanka during 2008 to 2012. Earnings per share was used as proxy for

shareholders wealth. There was positive relationship between Return on equity,

Dividend per share and Dividend payout ratio were positively significant while

Retention ratio was negatively significant with shareholders wealth. Tahir and

Raja (2014) examined the impact of dividend policy on shareholders wealth of

gas exploration companies of Pakistan during 1999 to 2006. Holding period

yield was used as measure of shareholders wealth whereas dividend payout ratio,

price earnings ratio and book value to market value as independent variables. It

was found that there was insignificant relationship between dependent and

independent variables.

Gejalakshmi and Azhagaiah (2015) examined the impact of dividend policy on

shareholders wealth before and after financial melt down from 13 FMCG sector

in India during 2003 to 2013. 2003 to 2007 period was considered as before

global financial meltdown and 2009 to 2013 period was considered as after

global financial meltdown. Dividend per share was positively significant with

EPS, a measure of shareholders wealth both before and after global financial

meltdown. Retained earnings per share was positively significant with

shareholders wealth before global financial meltdown whereas lagged price

earnings ratio and lagged market price per share were positively significant after

global financial meltdown. Chow test proved that there was positive significant

shift in respect of dividend policy on shareholders wealth. Anushiya & Rubika

(2015) found the impact of dividend policy on shareholders wealth from listed

banks in SriLanka during 2009 to 2013. Market price per share was used as a

proxy for shareholders wealth. It was found that divided policy had an impact on

shareholders wealth. Joseph and Mensah (2015) investigated the dividend policy

and its effect on shareholders wealth from 25 companies of UK retail industries

during 2004 to 2008. Market value to book value of stock price was used as

measure of shareholders wealth. Dividend payout ratio, Cash flow, investment,

profitability, leverage, liquidity and firm size were the independent variables

using panel data regression. Firm size, current dividend payout and current

investment had no impact on shareholders wealth whereas earnings, past

dividend payout, profitability, share price and leverage were positively

significant while investment was negatively significant with shareholders

wealth.

Gejalakshmi and Azhagaiah (2015) studied the impact of financial meltdown on

the relationship between dividend policy and shareholders wealth in basic


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material sector in India. Dividend per share, Earnings per share and Owners fund

were positively significant whereas Leverage was negatively significant with

shareholders wealth. Chow test proved that there was significant difference in

dividend payout ratio before and after financial meltdown. Ojeme et al

(2015)examined the dividend policy and shareholders wealth in 21 Nigerian

quoted banks during 2007 to 2010. Correlation proved that dividend had an

impact on market value of share. Ansar et al (2015) studied the impact of

dividend policy on shareholders wealth for 30 companies from Karachi stock

exchange during 2007 to 2011. Market price per share was used as proxy for

shareholders wealth. Dividend per share, Lagged market price per share,

Retained earnings per share and Return on equity were positively significant

with shareholders wealth. Mbuvi (2015) analysed the effect of dividend policy

on value creation for 59 shareholders of companies listed in the Nairobi

Securities Exchange. Dividend announcement, dividend payout, tax incentives

and cash flows had significant impact on shareholders wealth which was

measured through market price per share.

One of the earliest studies in this direction was done by Pettit (1972) who found

that the market made use of dividend change announcements in pricing

securities. Rozeff and Kinney (1976) explain that, since firms’ release more

information to the public in the month of January, above-normal returns in the

month of January can be attributed to this increased inflow of information by

firms to the market. Ball and Kothari (1991), investigating quarterly earnings

announcements and stock prices in the US from 1980 to 1988, find that

abnormal returns persisted after earning announcements. Gordon (1959, 1962),

Foster and Vickery (1978), and Lee (1995) document evidence that suggests

positive abnormal returns to dividend payment announcements. Contrary to the

above studies, Easton and Sinclair (1989) find negative abnormal returns, i.e., a

negative reaction by stock prices to dividend announcements; this is normally

attributed to the tax effect of dividends for shareholders. Lonie, et al (1996)

investigates the dividend announcements of 620 UK companies from January to

June 1991 using event study and interaction tests. They find that investors

responded to the increase or decrease in dividends. However, their findings also

reveal that, even for companies with no change in dividends, the average

abnormal returns one day prior to the announcements were significantly

different from zero as indicated by the t statistic.

Below and Johnson (1996) also fail to support the semi-strong form of market

efficiency for the US equity market. Adelegan (2003) conducts a study to

analyze the reaction of stock prices to dividend announcements and capital

market efficiency in Nigeria. He uses the standard event study methodology to

test the semi-strong form of market efficiency and finds that the Nigerian stock

market was inefficient in its semi-strong form. Uddin and Chowdhury (2005)

investigate dividend announcements on the Dhaka Stock Exchange and find that

there were no statistically significant abnormal returns and that dividends had no


72

information content for stock returns and prices in the Dhaka Stock Exchange.

Gunasekarage and Power (2006) also find that dividend announcements

influence stock returns at the time of announcements, but that the short-term

influence of dividend announcements had no long-term implications. In the long

run, firms with current reductions in dividends earned excess returns.

Kong and Taghavi (2006) analyze earning announcements for the Chinese

equity markets. They use the M-EGARCH approach to model changes in stock

returns with event study methodology and reject the semi strong form of market

efficiency on the basis of their findings. Acker (1999) investigates the impact of

dividend announcements on stock volatility rather than stock returns and finds

that stock volatility increases around dividend announcements, particularly final

dividend announcement and interim dividend announcements when there is a

dividend cut. Husain (1998, 1999), Chakraborty (2006), and Ali and Akbar

(2009)are a few of the studies that investigate the weak form of market

efficiency in the Pakistani equity market. Ali and Mustafa (2001) examine the

semi strong form of market efficiency in the Karachi Stock Exchange (KSE) by

analyzing public news in two daily newspapers and the changes in trade volume

and stock returns. They conclude that public information did not play an

important role in the determination of stock returns since stock returns appeared

more sensitive to private information. Chitra (2013) in the study impact of

dividend announcements on share price behaviour of select industries in India

found that share price volatility was high during post dividend announcement

period in Banking industry, Construction industry, Power industry, Cement

industry and Tobacco industry. Share price volatility was high during pre and

post dividend announcement period in IT industry. For Steel industry and

Textile industry, share price volatility was high during event date of dividend

announcement and during pre dividend announcement for Telecom industry and

Automobile industry. Paired t test was done for high and low share price during

pre event period, event period and post event period and found that for majority

of pairs, it was not statistically significant.

3. Research Methodology

In this research five industries viz Automobile, Infrastructure & Construction,

Energy, Information technology and Pharmaceutical industry were used. Fifteen

companies have been segregated as five large capitalization, five mid

capitalization and five small capitalization from each industry. Companies with

market capitalization of more than Rs. 20,000 Crores was considered as large

capitalization companies, Rs. 5,000 to Rs. 20,000 Crores was considered as mid-

capitalization companies and less than Rs. 5,000 Crores was considered as small

capitalization companies (Source: www.equitymaster.com).

Fifteen years data (2001 to 2015) were used to examine the impact of dividend

payout on shareholders wealth. Panel regression was to identify the impact of


73

dividend payout on shareholders wealth and Paired t test was used to find the

effect of dividend announcement on market price of share during before and

after financial meltdown. Secondary data were collected from Prowess database

of Centre for Monitoring Indian Economy (CMIE), www.bseindia.com and

www.nseindia.com were the source of data for the research. Based on the

requirement, the Secondary data was compiled from the database. To examine

the impact of dividend payout and its determinants on Shareholders wealth

To examine the impact of dividend payout and its determinants based on

all selected industries together during 2001 to 2015.

To analyse the impact of dividend payout and its determinants based on

all selected industries together before financial meltdown (2001 to 2007)

and after financial meltdown (2009 to 2015).

To analyse the impact of dividend payout and its determinants based on

market capitalization during 2001 to 2015.

To find out the impact of dividend payout and its determinants for all

selected industries separately during 2001 to 2015.

To analyze the effect of dividend announcement on the market price of share.

Monthly market price of the share of all the companies for fifteen year

from 2001 to 2015 have been selected on the pre dividend announcement

month, dividend announcement month and post dividend announcement

month.

Market price of the share on pre – event, event – post and pre – post

dividend announcement has been compared to analyse the effect of

dividend announcement on the share price for all selected industries and

market capitalization separately.

4. Results and Discussions

Impact of Dividend Payout on Shareholders Wealth

Based on the literature review it was found that ASG, AT, DER, ID, ISH,

LAGDPR, LNTA, OD, PER and RONW were the major dividend determinants.

The following common model has been selected to analyse the impact of

dividend payout and its determinants on shareholders wealth.

TOBINS’Q = β1 (DPR) + β2 (ASG) + β3 (DER) + β4 (ID) + β5 (LAGDPR) + β6

(LNTA) + β7 (OD) + β8 (PER) + β9 (RONW) + e

Where, TOBINS’Q = Measure of Shareholders wealth

DPR = Dividend Pay out Ratio

ASG = Annual Sales growth measures the Growth opportunities of the company

DER = Debt Equity Ratio measures the financial leverage of the company

ID = Investment Demand measures the Investment level of the company

LAGDPR = Lagged Dividend pay out ratio measures the past dividend

LNTA = Natural log of Total assets measures the size of the firm

OD = Ownership Dispersion measures the agency cost


74

PER = Price Earnings Ratio measures the risk level of the firm

RONW = Return on Net worth measures the Profitability of the company

Table 1: Panel data Regression–Impact of Dividend on Shareholders Wealth-All Industries

& Market Capitalization

Dependent Variable = TOBINS’Q S.No /

Variables

1

FEM

2

FEM

3

FEM

4

FEM

5

FEM

6

REM

7

FEM

8

FEM

9

REM

10

REM

11

FEM

C 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.861 0.851 0.000*** 0.253 0.006** 0.044**

DPR 0.024** 0.765 0.000*** 0.371 0.000*** 0.008** 0.067* 0.200 0.033** 0.007** 0.000***

ASG 0.067* 0.159 0.593 0.205 0.776 0.284 0.136 0.311 0.244 0.039** 0.294

DER 0.000*** 0.000*** 0.000*** 0.033** 0.000*** 0.000*** 0.000*** 0.557 0.625 0.047** 0.000***

ID 0.420 0.000*** 0.906 0.816 0.051* 0.102 0.021** 0.340 0.110 0.000*** 0.008**

LAGDPR 0.498 0.034** 0.323 0.049** 0.550 0.685 0.130 0.028** 0.018** 0.065* 0.974

LNTA 0.546 0.000*** 0.000*** 0.000*** 0.000*** 0.004*** 0.000*** 0.124 0.867 0.016** 0.026**

OD 0.000*** 0.000*** 0.000*** 0.000*** 0.192 0.000*** 0.000*** 0.069* 0.790 0.000*** 0.339

PER 0.000*** 0.003*** 0.000*** 0.633 0.000*** 0.000*** 0.126 0.001*** 0.000*** 0.000*** 0.000***

RONW 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.075* 0.000*** 0.366

R Sq 0.312 0.850 0.812 0.430 0.543 0.205 0.694 0.516 0.744 0.594 0.504

Adj R Sq 0.298 0.822 0.781 0.392 0.513 0.186 0.659 0.461 0.733 0.577 0.447

F Stat 21.725 30.093 26.807 11.493 18.107 10.474 19.851 9.331 69.427 34.942 8.871

P (F Stat) 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000***

***** 152.555

(0.000***)

42.202

(0.000***

)

116.028

(0.000***

)

21.216

(0.000***

)

78.137

(0.000***

)

32.551(0.000***

)

44.314(0.000***

)

15.381(0.000***

)

82.050(0.000***

)

83.307(0.000***

)

52.748

(0.000***)

******* 92.638(0.000***

)

91.059

(0.000***

)

119.512

(0.000***

)

108.590

(0.000***

)

102.399

(0.000***

)

16.484

(0.057***)

34.805

(0.000***)

71.972

(0.000***)

14.015 (0.122) 14.581(0.103) 41.581(0.000***

)

1.All the selected industries: 2001 – 2015, 2. All the selected industries during

pre-financial meltdown (2001 to 2007), 3. All the selected industries during

post-financial meltdown (2009 to 2015), 4. All the selected industries Large

Capitalization companies during 2001 to 2015, 5. All the selected industries

Mid-Capitalization companies during 2001 to 2015, 6. All the selected

industries Small Capitalization companies during 2001 to 2015, 7. All the

selected companies of Automobile industry during 2001 to 2015, 8. All the

selected companies of Infrastructure & Construction industry during 2001 to

2015, 9. All the selected companies of Energy industry during 2001 to 2015, 10.

All the selected companies of Information Technology industry during 2001 to

2015, 11. All the selected companies of Pharmaceutical industry during 2001 to

2015, ***** Poolability Hypothesis test – F statistic, ******* Hausman Test –

Chi – Sq. Statistic, *** Significant at 1% level ** Significant at 5% level

* Significant at 10%, REM = Random Effect Model, FEM = Fixed Effect

Model, DPR = Dividend payout ratio , ASG = Annual sales growth measuring

growth opportunities, DER = Debt Equity ratio measuring leverage , ID =

Investment demand, LAGDPR = Lagged dividend payout ratio measuring past

dividend, LNTA = Natural log total assets measuring size of the company, OD =

Ownership dispersion measuring agency cost, PER = Price earnings ratio

measuring firm risk, RONW = Return on Networth measuring profitability

Table no. 1 analysed the impact of dividend payout and its determinants on

shareholders wealth. Panel data regression was used for the study with

TOBINS’Q as the measure of shareholders wealth.

Poolability hypothesis test probability was less than 1% significance level which

proved that Hausman test could be done to identify the best model between

Fixed Effect Model (FEM) and Random Effect Model (REM). If the probability


75

of Hausman test was less than 1% level of significance (0.000) Fixed Effect

Model (FEM) was used otherwise Random Effect Model (REM).

Ho1: There is no significant impact of dividend payout on shareholders wealth

among the selected companies of Automobile, Infrastructure & Construction,

Energy, Information Technology and Pharmaceutical industries together during

2001 to 2015.

DPR has probability of less than 5% significance level, hence null hypothesis

was rejected. So, there was significant impact of dividend payout on

shareholders wealth among the selected companies of Automobile,


Pharmaceutical industries together during 2001 to 2015. F statistics was

significant at 1% level of significance indicated that the model could be

generalized for all the companies of all selected industries during 2001 to 2015

and it can be concluded that at least one of the independent variable was

significant in explaining dividend payout ratio.

Ho2: There is no significant impact of dividend payout on shareholders wealth



Pre financial meltdown (2001 to 2007)

DPR has probability of more than 5% significance level, hence null hypothesis

was accepted. So, there was no significant impact of dividend payout on



Pharmaceutical industries together during Pre financial meltdown (2001 to

2007). F statistics was significant at 1% level of significance indicated that the

model could be generalized for all the companies of all selected industries

during pre-financial meltdown (2001 to 2007) and it can be concluded that at

least one of the independent variable was significant in explaining dividend

payout ratio.

H03: There is no significant impact of dividend payout on shareholders wealth



Post financial meltdown (2009 to 2015).





Pharmaceutical industries together during Post financial meltdown (2009 to

2015). F statistics was significant at 1% significance level of significance


76

indicated that the model could be generalized for all the companies of all

selected industries during post financial meltdown (2001 to 2007) and it can be

concluded that at least one of the independent variable was significant in

explaining dividend payout ratio.


in Automobile, Infrastructure & Construction, Energy, Information Technology

and Pharmaceutical industries selected large capitalization companies together

during 2001 to 2015.

DPR has probability of more than 5%, hence null hypothesis H028 was accepted.

So, there was no significant impact of dividend payout on shareholders wealth in

Automobile, Infrastructure & Construction, Energy, Information Technology

and Pharmaceutical industries selected large capitalization companies together

during 2001 to 2015. F statistics was significant at 1% level of significance

indicated that the model could be generalized for all the large capitalization

companies of all selected industries during 2001 to 2015 and it can be concluded

that at least one of the independent variable was significant in explaining

dividend payout ratio.



and Pharmaceutical industries selected mid-capitalization companies together




shareholders wealth in Automobile, Infrastructure & Construction, Energy,

Information Technology and Pharmaceutical industries selected mid-

capitalization companies together during 2001 to 2015. F statistics was


generalized for all the mid-capitalization companies of all selected industries

during 2001 to 2015 and it can be concluded that at least one of the independent

variable was significant in explaining dividend payout ratio.



and Pharmaceutical industries selected Small capitalization companies together




shareholders wealth in Automobile, Infrastructure & Construction, Energy,

Information Technology and Pharmaceutical industries selected Small

capitalization companies together during 2001 to 2015. F statistics was


77


generalized for all the small capitalization companies of all selected industries

during 2001 to 2015 and it can be concluded that at least one of the independent



among all selected companies of Automobile industry during 2001 to 2015.


was rejected. So, there was significant impact of dividend pay significance level

out on shareholders wealth among all selected companies of Automobile

industry during 2001 to 2015. F statistics was significant at 1% level of

significance indicated that the model could be generalized for all the automobile

industry companies during 2001 to 2015 and it can be concluded that at least one

of the independent variable was significant in explaining dividend payout ratio.


among all selected companies of Infrastructure & Construction industry during

2001 to 2015.

DPR has probability of more than 5% significance level, hence null hypothesis

was accepted. So, there was no significant impact of dividend payout on

shareholders wealth among all selected companies of Infrastructure &

Construction industry during 2001 to 2015.

F statistics was significant at 1% level of significance indicated that the model

could be generalized for all the Infrastructure & Construction industry

companies during 2001 to 2015 and it can be concluded that at least one of the

independent variable was significant in explaining dividend payout ratio.


among all selected companies of Energy industry during 2001 to 2015.



shareholders wealth among all selected companies of Energy industry during

2001 to 2015. F statistics was significant at 1% level of significance indicated

that the model could be generalized for all the Energy industry companies during

2001 to 2015 and it can be concluded that at least one of the independent



among all selected companies of Information Technology industry during 2001

to 2015.

DPR has the probability of less than 5% significance level, hence null


78

hypothesis was rejected. So, there was significant impact of dividend payout on

shareholders wealth among all selected companies of Information Technology

industry during 2001 to 2015. F statistics was significant at 1% level of

significance indicated that the model could be generalized for all the Information

technology industry companies during 2001 to 2015 and it can be concluded that

at least one of the independent variable was significant in explaining dividend

payout ratio.


among all selected companies of Pharmaceutical industry during 2001 to 2015.

DPR has the probability of less than 5% significance level, hence null

hypothesis was rejected. So, there was significant impact of dividend payout on

shareholders wealth among all selected companies of Pharmaceutical industry

during 2001 to 2015. F statistics was significant at 1% level of significance

indicated that the model could be generalized for all the Pharmaceutical industry

companies during 2001 to 2015 and it can be concluded that at least one of the

independent variable was significant in explaining dividend payout ratio.

Dividend payout had a negative impact on shareholders wealth for all selected

industries together from 2001 to 2015, all selected industries together from 2009

to 2015 (Post financial meltdown), all selected industries mid-capitalization

companies from 2001 to 2015, all selected companies of energy industry, all

selected companies of information technology industry and for all selected

companies of pharmaceutical industry. Dividend payout ratio was negatively

impacting shareholders wealth which is in consistent with (Shaveta Gupta

(2011), Kai et al (2014), Anushiya & Rubika (2015), Ojeme et al (2015) and

Mbuvi (2015). Dividend payout ratio had significant negative impact on

majority of selected industries and market capitalizations. Payment of more

dividend would reduce the shareholders wealth. According to Hull, 2012,

payment of dividend would reduce the share price on ex-dividend date.

Investors, managers and promoters would also want more investment than

dividend payout. Policy makers should design the optimum payout policy that

should increase the shareholders wealth.

Dividend payout had positive impact on shareholders wealth for all selected

industries small capitalization companies from 2001 to 2015 and all selected

companies of automobile industry from 2001 to 2015 Dividend payout ratio

was positively significant with shareholders wealth which is in lieu with

Azhagaiah & Sabari priya (2008), Gul et al (2012), Mistry (2012), Bawa & Kaur

(2013), Chidinma et al (2013), Sarwar (2013), De wet Mpinda (2013), Iqbal et al

(2014), Kumaresan (2014), Ansar et al (2015), Gejalakshmi & Azhagaiah

(2015), Anushiya & Rubika (2015), Ojeme et al (2015) and Mbuvi (2015) and it

had no impact on shareholders wealth for all selected industries together from

2001 to 2007 (Pre financial meltdown), all selected industries large


79

capitalization companies from 2001 to 2015 and for all selected companies of

infrastructure & construction industry whish is in lieu with (Shahid Ali et al

(2010), Tahir & Raja (2014) and Joseph & Mensah (2015)).


80

Effect of Dividend Announcement on the Market Price of Share

Analysis of mean share price behaviour during pre, event and post announcement of dividend for all selected industries and market capitalization during 2001 to 2015:

Table 2: Mean of Share Prices of All Selected Industries and Market

Capitalization during Pre Event Period, Event Period and Post

Event Period for the Year 2001 to 2015 Year Event Type 1 2 3 4 5 6 7 8

2001

Pre- 392.94 123.42 124.51 764.58 515.37 847.50 209.53 65.51

Event- 372.77 122.30 121.18 788.07 478.40 835.16 196.50 67.95

Post- 342.48 118.76 124.50 841.24 474.71 856.39 183.98 67.80

2002

Pre- 530.01 144.69 143.66 914.26 303.93 867.14 327.76 81.15

Event- 576.44 148.37 140.52 898.92 301.22 885.80 342.52 77.45

Post- 582.16 147.93 142.50 893.70 301.50 891.46 335.50 83.57

2003

Pre- 608.86 204.14 323.66 777.91 319.61 767.86 383.80 184.08

Event- 687.09 238.35 340.05 702.48 353.90 765.43 429.79 201.60

Post- 697.34 293.35 361.79 708.47 391.95 806.60 438.01 223.34

2004

Pre- 1123.55 486.25 526.73 698.04 500.10 1148.87 543.34 214.47

Event- 1099.45 527.72 522.21 743.85 496.80 1172.27 541.88 213.00

Post- 1166.85 526.01 551.76 758.45 508.21 1205.67 560.79 242.12

2005

Pre- 726.17 865.38 470.91 667.61 500.39 909.17 638.56 259.25

Event- 707.41 990.74 495.93 633.57 526.40 949.38 625.95 272.49

Post- 763.59 1071.27 500.41 694.11 555.10 1019.41 671.72 282.73

2006

Pre- 1099.16 1044.64 529.96 728.16 635.77 1138.82 765.05 296.54

Event- 1108.81 1050.21 529.00 724.42 626.10 1129.28 786.14 281.60

Post- 1186.56 1028.34 501.00 712.48 656.89 1143.46 810.38 262.05

2007

Pre- 1365.49 1039.38 831.16 612.52 563.75 1200.37 900.21 430.79

Event- 1594.53 2860.92 872.50 630.28 547.29 2147.53 1062.42 461.58

Post- 1436.52 1056.76 903.10 611.28 543.56 1205.67 946.05 463.25

2008

Pre- 946.59 826.20 952.41 465.53 466.47 936.10 674.13 445.50

Event- 873.91 740.71 906.21 447.11 470.79 891.92 632.99 407.07

Post- 846.91 688.26 850.02 446.91 453.97 872.41 601.61 372.02

2009

Pre- 1186.99 524.74 687.87 359.62 454.47 719.38 827.87 289.99

Event- 1264.98 646.95 719.61 408.37 492.11 782.06 912.78 323.11

Post- 1295.63 688.44 748.47 424.00 531.31 790.08 964.42 359.54

2010

Pre- 1756.91 850.52 900.71 606.06 738.08 1132.65 1246.88 443.07

Event- 1702.94 874.29 890.71 631.94 760.06 1159.64 1233.63 426.97

Post- 1627.00 899.35 944.22 618.44 793.40 1179.14 1195.28 455.97

2011

Pre- 1886.21 609.26 820.87 571.02 610.12 1207.04 918.85 441.96

Event- 1922.19 596.41 782.92 566.25 599.48 1192.47 929.88 427.27

Post- 1944.91 612.56 776.12 560.91 619.63 1220.37 931.80 417.23

2012

Pre- 2205.39 355.55 650.89 555.82 638.08 920.21 1217.22 389.63

Event- 2205.70 350.51 605.78 555.35 625.92 911.38 1215.00 362.79

Post- 2393.96 368.82 609.68 548.36 634.88 940.67 1274.52 390.37

2013

Pre- 2706.74 370.97 534.83 708.88 742.67 1037.38 1405.92 386.46

Event- 2914.03 354.48 549.99 709.93 745.43 1037.16 1507.57 395.28

Post- 3079.38 347.34 522.97 741.15 741.29 1069.24 1576.00 374.06

2014

Pre- 5365.07 393.62 1247.83 987.70 906.92 1350.78 2750.92 998.96

Event- 5439.66 464.83 1406.83 1005.04 892.60 1393.27 2782.88 1122.86

Post- 5934.35 515.61 1547.33 1024.18 963.11 1473.70 3005.43 1259.55

2015

Pre- 6221.86 676.12 1505.67 909.38 1108.80 1693.65 2591.17 1403.47

Event- 6558.77 669.22 1503.58 895.16 1186.38 1733.84 2741.89 1396.42

Post- 6395.55 676.11 1957.56 930.10 1163.49 1706.46 2699.13 1768.02


81

1 = Automobile industry 2 = Infrastructure & Construction industry 3 = Energy

industry 4 = Information technology industry 5 = Pharmaceutical industry 6 =

Large capitalization companies 7 = Mid capitalization companies 8 = Small

capitalization companies

It was found from Table 2 that the years 2002, 2003, 2004, 2005, 2006, 2009,

2011, 2012, 2013 and 2014, the share price had shown an increase in the post

event period. This implied that during the post event period the share price has

shown a positive impact towards dividend announcement in the above

mentioned years. On the other hand, during the years 2001, 2008 and 2010, the

share price of Automobile industry had shown an increase in the pre event

period. This implied that the share price reacted positively during the pre event

period towards dividend announcement.

Further, during the years 2007 and 2015, the share price had shown an increase

in the event period. Overall, the effect of dividend announcement on share price

of Automobile industry was 67% favourable to post event period, 20%

favourable to pre event period and 13% favourable to event period. It was

concluded that the share price volatility was high during post dividend

announcement period for majority of the selected automobile industry

companies.

The results have shown that during the years 2003, 2005, 2009, 2010, 2011,

2012 and 2014, the share price had shown an increase in the post event period.

This implied that during the post event period the share price has shown a

positive effect towards dividend announcement in the above mentioned years.

On the other hand, during the years 2001, 2008, 2013 and 2015, the share price

of Infrastructure & Construction industry had shown an increase in the pre event


period towards dividend announcement. Further, during the years 2002, 2004,

2006 and 2007, the share price had shown an increase in the event period.

Overall, the effect of dividend announcement on share price of Infrastructure &

Construction industry was 46% favourable to post event period, 27% favourable

to pre event period and 27% favourable to event period. It was concluded that

the share price volatility was high during post dividend announcement period for

majority of the selected Infrastructure & Construction industry companies.


2010, 2014 and 2015, the share price had shown an increase in the post event

period. This implied that during the post event period the share price has shown

a positive effect towards dividend announcement in the above mentioned years.

On the other hand, during the years 2001, 2002, 2006, 2008, 2011 and 2012, the

share price of Energy industry had shown an increase in the pre event period.

This implied that the share price reacted positively during the pre event period

towards dividend announcement. Further, during the year 2013, the share price


82

had shown an increase in the event period. Overall, the effect of dividend

announcement on share price of Energy industry was 53% favourable to post

event period, 40% favourable to pre event period and 7% favourable to event

period. It was concluded that the share price volatility was high during post

dividend announcement period for majority of the selected energy industry

companies.


2014 and 2015, the share price had shown an increase in the post event period.

This implied that during the post event period the share price has shown a

positive impact towards dividend announcement in the above mentioned years.

On the other hand, during the years 2002, 2003, 2006, 2008, 2011 and 2012, the

share price of Information Technology industry had shown an increase in the pre

event period. This implied that the share price reacted positively during the pre

event period towards dividend announcement. Further, during the years 2007

and 2010, the share price had shown an increase in the event period. Overall, the

effect of dividend announcement on share price of Information Technology

industry was 47% favourable to post event period, 40% favourable to pre event

period and 13% favourable to event period. It was concluded that the share price

volatility was high during post dividend announcement period for majority of

the selected information technology companies. The results have shown that

during the years 2003, 2004, 2005, 2006, 2009, 2010, 2011 and 2014, the share

price had shown an increase in the post event period. This implied that during

the post event period the share price has shown a positive impact towards

dividend announcement in the above mentioned years. On the other hand, during

the years 2001, 2002, 2007 and 2012, the share price of Pharmaceutical industry

had shown an increase in the pre event period. This implied that the share price

reacted positively during the pre event period towards dividend announcement.

Further, during the years 2008, 2013 and 2015, the share price had shown an

increase in the event period. Overall, the effect of dividend announcement on

share price of Pharmaceutical industry was 53% favourable to post event period,

27% favourable to pre event period and 20% favourable to event period. It was


announcement period for majority of the selected pharmaceutical companies.


2006, 2009, 2010, 2012, 2013 and 2014, the share price had shown an increase

in the post event period. This implied that during the post event period the share

price has shown a positive impact towards dividend announcement in the above

mentioned years. On the other hand, during the years 2008 and 2011, the share

price of large capitalization companies had shown an increase in the pre event


period towards dividend announcement.


83

Further, during the years 2007 and 2015, the share price had shown an increase

in the event period. Overall, the effect of dividend announcement on share price

of large capitalization companies was 74% favourable to post event period, 13%



announcement period for majority of the selected large capitalization companies.


2011, 2012, 2013 and 2014, the share price had shown an increase in the post

event period. This implied that during the post event period the share price has

shown a positive impact towards dividend announcement in the above


share price of mid capitalization companies had shown an increase in the pre

event period. This implied that the share price reacted positively during the pre

event period towards dividend announcement. Further, during the years 2002,

2007 and 2015, the share price had shown an increase in the event period.

Overall, the effect of dividend announcement on share price of mid

capitalization companies was 60% favourable to post event period, 20%



announcement period for majority of the selected mid capitalization companies.


2009, 2010, 2012, 2014 and 2015, the share price had shown an increase in the

post event period. This implied that during the post event period the share price

has shown a positive impact towards dividend announcement in the above


share price of small capitalization companies had shown an increase in the pre

event period.

This implied that the share price reacted positively during the pre event period

towards dividend announcement. Further, during the years 2001 and 2013, the

share price had shown an increase in the event period. Overall, the effect of

dividend announcement on share price of small capitalization companies was

67% favourable to post event period, 20% favourable to pre event period and

13% favourable to event period. It was concluded that the share price volatility

was high during post dividend announcement period for majority of the selected

small capitalization companies.

It was found that dividend announcement impact on the closing share price of

the companies was more favourable during post event for all selected industries

and market capitalization than the pre event and event.


84

Paired t – test for closing share price all selected industries and market capitalization for dividend announcement during pre event, event and post event period

Table 3: Paired t – test for Closing Share Price of All Selected Industries

and Market Capitalization for Dividend Announcement during Pre Event,

Event and Post Event Period

Industry Pair Event P value S /

NS

Automobile Pair

1

Pre 0.061* S

Event

Pair

2

Event 0.298 NS

Post

Pair

3

Pre 0.037*

*

S

Post

Infrastructure &

Construction

Pair

1

Pre 0.261 NS

Event

Pair

2

Event 0.396 NS

Post

Pair

3

Pre 0.128 NS

Post

Energy Pair

1

Pre 0.488 NS

Event

Pair

2

Event 0.187 NS

Post

Pair

3

Pre 0.172 NS

Post

Information Technology Pair

1

Pre 0.913 NS

Event

Pair

2

Event 0.089* S

Post

Pair

3

Pre 0.234 NS

Post

Pharmaceutical Pair

1

Pre 0.388 NS

Event

Pair

2

Event 0.033*

*

S

Post

Pair

3

Pre 0.037*

*

S

Post

Large Capitalization Pair

1

Pre 0.258 NS

Event

Pair

2

Event 0.543 NS

Post

Pair

3

Pre 0.012*

*

S

Post

Mid Capitalization Pair

1

Pre 0.040*

*

S

Event

Pair

2

Event 0.395 NS

Post

Pair

3

Pre 0.031*

*

S

Post

Small Capitalization Pair

1

Pre 0.480 NS

Event

Pair

2

Event 0.154 NS

Post

Pair

3

Pre 0.143 NS

Post

S = Significant NS = Not Significant *** Significant at 1% level


85

** Significant at 5% level * Significant at 10%,

The following results were found from table no. 3.

Automobile Industry

Pair 1: Null hypothesis: There is no significant difference in the closing share

prices during pre-event period and event period in Automobile industry. Pair 2:

Null hypothesis: There is no significant difference in the closing share prices

during event period and post-event period in Automobile industry. Pair 3: Null

hypothesis: There is no significant difference in the closing share prices during

pre-event period and post-event period in Automobile industry.

It was observed that the p value for pair 1 was more than 5% significance level

but less than 10%hence null hypothesis was rejected. So, there was significant

difference in the closing share prices during pre-event period and event period in

Automobile industry at 10% level of significance. Since p value was more than

5% significance level, null hypothesis pair 2 was accepted. So, there was no

significant difference in the closing share prices during event period and post-

event period in Automobile industry and null hypothesis for pair 3 was rejected

since p value was less than 5% significance level. So, there was significant

difference in the closing share prices during pre-event period and post-event

period in Automobile industry.

Infrastructure & Construction Industry


prices during pre-event period and event period in Infrastructure & Construction

industry. Pair 2: Null hypothesis: There is no significant difference in the

closing share prices during event period and post-event period in Infrastructure

& Construction industry. Pair 3: Null hypothesis: There is no significant


period in Infrastructure & Construction industry.

It was observed that the p value for pair 1, pair 2 and pair 3 were more than 5%

significance level, hence all three null hypotheses were accepted. So, there was

no significant difference in the closing share prices during pre-event period and

event period in Infrastructure & Construction industry, there was no significant

difference in the closing share prices during event period and post-event period

in Infrastructure & Construction industry and no significant difference in the

closing share prices during pre-event period and post-event period in

Infrastructure & Construction industry.

Energy Industry


prices during pre-event period and event period in Energy industry. Pair 2: Null

hypothesis: There is no significant difference in the closing share prices during


86

event period and post-event period in Energy industry. Pair 3: Null hypothesis:

There is no significant difference in the closing share prices during pre-event

period and post-event period in Energy industry.


significance level, hence all three null hypotheses were accepted. So, there was


event period in Energy industry, there was no significant difference in the

closing share prices during event period and post event period in Energy

industry and there was no significant difference in the closing share prices

during pre-event period and post-event period in Energy industry.

Information Technology Industry


prices during pre-event period and event period in Information Technology

industry. Pair 2: Null hypothesis: There is no significant difference in the

closing share prices during event period and post-event period in Information

Technology industry. Pair 3: Null hypothesis: There is no significant difference

in the closing share prices during pre-event period and post-event period in

Information Technology industry.

It was observed that the p value for pair 1and pair 3 were more than 5%

significance level, hence null hypotheses were accepted. There was no

significant difference in the closing share prices during pre-event period and

event period as well as pre event and post event period in Information

Technology industry whereas null hypothesis for pair 2 was rejected at 10%

level of significance since p value was more than 5% significance level but less

than 10%. So there was significant difference in the closing share prices during

event period and post-event period in Information Technology industry.

Pharmaceutical Industry


prices during pre-event period and event period in Pharmaceutical industry.


prices during event period and post-event period in Pharmaceutical industry.


prices during pre-event period and post-event period in Pharmaceutical industry.

It was observed that the p value for pair 1 was more than 5%, hence null

hypothesis was accepted. So, there was no significant difference in the closing

share prices during pre-event period and event period in Pharmaceutical

industry. For pair 2 and pair 3, p value was less than 5% significance level,

hence null hypothesis for pair 2 and pair 3 were rejected. So, there was



87

event period and there was no significant difference in the closing share prices

during pre-event period and post-event period in Pharmaceutical industry.


88

Large Capitalization Companies


prices during pre-event period and event period for large capitalization

companies. Pair 2: Null hypothesis: There is no significant difference in the

closing share prices during event period and post-event period for large

capitalization companies. Pair 3: Null hypothesis: There is no significant


period for large capitalization companies.

It was observed that the p value for pair 1 and pair 2 were more than 5%

significance level, hence null hypotheses for pair 1 and pair 2 were accepted. So,

there was no significant difference in the closing share prices during pre-event

period and event period for large capitalization companies and there was no


event period for large capitalization companies. Since p value was less than 5%

significance level, null hypothesis for pair 3 was rejected. So, there was

significant difference in the closing share prices during pre-event period and

post-event period for large capitalization companies.

Mid Capitalization Companies


prices during pre-event period and event period for mid capitalization


closing share prices during event period and post-event period for mid



period for mid capitalization companies.

It was observed that the p value for pair 1 and pair 3 were less than 5%

significance level, hence null hypotheses were rejected. So, there was significant

difference in the closing share prices during pre-event period and event period

for mid capitalization companies as well as there was significant difference in

the closing share prices during pre-event period and post-event period for mid

capitalization companies. Null hypothesis for pair 2 was accepted since p value

was more than 5% significance level. Hence there was no significant difference

in the closing share prices during event period and post-event period for mid

capitalization companies.

Small Capitalization Companies


prices during pre-event period and event period for small capitalization


closing share prices during event period and post-event period for small



89


period for small capitalization companies.


significance level, hence all three null hypothesis were accepted. So, there was


event period, there was no significant difference in the closing share prices

during event period and post-event period and no significant difference in the

closing share prices during pre-event period and post-event period for small

capitalization companies. It was found that there was significant difference in

closing share between pre and post event for all selected industries large

capitalization companies from 2001 to 2015, all selected companies of

automobile industry from 2001 to 2015 and for all selected companies of

information technology industry.

5. Conclusion

Dividend payout had a negative impact on shareholders wealth for all selected

industries together from 2001 to 2015, all selected industries together from 2009

to 2015 (Post financial meltdown), all selected industries mid-capitalization

companies from 2001 to 2015, all selected companies of energy industry, all

selected companies of information technology industry and for all selected

companies of pharmaceutical industry. Dividend payout ratio had significant

negative impact on majority of selected industries and market capitalizations.

Payment of more dividend would reduce the shareholders wealth. According to

Hull, 2012, payment of dividend would reduce the share price on ex-dividend

date. Investors, managers and promoters would also want more investment than

dividend payout. Policy makers should design the optimum payout policy that

should increase the shareholders wealth. Dividend payout had positive impact on

shareholders wealth for all selected industries small capitalization companies

from 2001 to 2015 and all selected companies of automobile industry from 2001

to 2015 and it had no impact on shareholders wealth for all selected industries

together from 2001 to 2007 (Pre financial meltdown), all selected industries

large capitalization companies from 2001 to 2015 and for all selected companies

of infrastructure & construction industry. It was found that dividend

announcement impact on the closing share price of the companies was more

favourable during post event for all selected industries and market capitalization

than the pre event and event. It was found that there was significant difference in

closing share between pre and post event for all selected industries large

capitalization companies from 2001 to 2015, all selected companies of

automobile industry from 2001 to 2015 and for all selected companies of

information technology industry.


90

Acknowledgment

Our thanks to ICIRST for allowing us to modify templates they had developed.

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