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D.U. Journal of Marketing, Vol. 16, No. 1, June 2013 (Published in December, 2015)

DETERMINANTS OF CORPORATE SOCIAL

RESPONSIBILITY OF BANKING INDUSTRY LISTED IN

THE DHAKA STOCK EXCHANGE LIMITED

Saud Ahmed1

Moriom Akter2

Abstract: The purpose of the study is to identify the impact of determinants

of Corporate Social Responsibility (CSR) of banking industry listed in

Dhaka Stock Exchange (DSE). The data set consists of 30 banks over 5

years (2008 - 2012) of observation formed a completely balanced panel

data set. Here OLS model with fixed effect has been conducted for

regression panel. CSR expenditure has been taken as a dependent variable

and total investment, total asset, promotional expenditure interest income,

total deposit, no. of branch, number of employees as the independent

variables in this model. Admittedly, promotional expenditure and number of

branch are statistically significant at 5% significance level in determining

the level of CSR expenditures of the respective banks in Bangladesh.

Subsequently, the beta coefficient of both promotional expenditure and

number of branch are positive, it indicates that larger the amount of

promotional expenditure and larger the size of the bank, higher will be the

level of CSR expenditure.

Key Words: Corporate Social Responsibility, Banking Industry.

INTRODUCTION

In this modern competitive business world profit is not considered as the ultimate

factor of success. The concept of business has converted from profit making

activities to social welfare activities where businesses are not only responsible to

its shareholders but also to all of its stakeholders. Apart from the generous social

services by the business firms, the new concept of corporate social responsibility

(CSR) is an emerging one. CSR is a form of corporate self-regulations integrated

into a business model. It is said that CSR is a concept whereby financial

institutions not only consider their profitability and growth, but also the interest

of society and the environment by taking responsibility for the impact of their

activities on stakeholders, employees, shareholders, customers, suppliers and

civil society.

Now-a-days CSR in Bangladesh is a vibrant issue and all the institutions are

trying to maintain this responsibility along with other responsibilities. Banking

1 Assistant Professor, Department of Tourism and Hospitality Management, University of Dhaka,

Bangladesh. 2 Financial Analyst, Chevron Bangladesh.

246 D.U. Journal of Marketing, Vol. 16, No. 1, June 2013

sector of this country has a glorious history of getting engaged themselves in

different kinds of social activities like donations to different organizations,

country beautification, patronizing cultural activities etc. CSR is always enthused

by Bangladesh Bank (BB). Subsequently it has set up a dedicated department on

"Green Banking & CSR" in April 2013 perhaps first time by any country‟s

Central Bank. Accordingly, BB has guideline for banks on CSR in place,

however, now it is more systematized to drive the entire banking sector to

involve in CSR activities in a more structured way.

Studies on CSR in various industries across the world mainly focused on the

impact of CSR on company‟s financial performance. However, very little work

has been done on the opposite phenomenon i.e. the impact of financial and non –

financial performance in determining the level of CSR. This study has conducted

to bridge this research gap by identifying the impact of firm specific determinants

of CSR expenditure.

LITERATURE REVIEW

Different researchers have worked on CSR in different time with different

variables. But very little work has been done on the firm specific determinants of

CSR of the banking Industry of Bangladesh. Studies on CSR across the world

mainly focus on the impact of CSR on a firm‟s financial performance. However,

there are hardly enough empirical evidences on the firm‟s specific determinants

of CSR expenditure.

Mamun et al. (2013) conducted an analysis with panel data of Bangladeshi

banking industry over a period of 2002-2011 augmented the financial

determinants of CSR expenditures. The results from panel ARDL model for 30

private commercial banks confirm that several financial determinants including

total investment, no. of branch, and no. of employees have significant long run

impact on the level of bank‟s CSR expenditure. More precisely, Samina

(2012)tried to find out whether the Islamic Banks of Bangladesh are adhering to

the prescribed forms of the CSR activities or not. The research found compliance

to the mandatory forms by the 6 fully fledged sample Islamic banks and found a

strong positive correlation between CSR expenditure and sample banks‟ deposit,

loan and profitability. Quazi et al. (2007)considered the CSR practices of a small

sample of 17 multinational corporations (MNCs) and local firms in Bangladesh.

Of the investigated 17 firms, 10 had implemented CSR for discretionary reasons,

nine for ethical reasons, and one firm implemented for legal reasons. Five of the

17 firms were observed to implement different types of CSR initiatives for

different strategic reasons. It is found that firms use their CSR records to create

the image of socially responsible firms and thereby influence consumer buying

decisions in favor of the goods and services marketed by them.

From another view point, Islam (2012) examines the relationship between

financial performance and CSR initiatives of banks in Bangladesh. Out of 47

Determinants of Corporate Social Responsibility of Banking Industry 247

banks, data were collected from 37 (78.72%) for four years from 2007 to 2010.

Panel data Generalized Least Square Regression Model was used for data

analysis. Four major financial performance indicators- Size of business, Return

on Equity (ROE) and Asset Quality (AstQt) and Capital Adequacy Ratio(CAR)-

were used for the study. Variance Inflation Factor for multicolinearity, White test

for heteroskedasticity and Wooldridge test for serial correlation were used for

data processing. The study finds that CSR initiatives represented by CSR

expenditure of banks are positively connected with the Size of business, ROE

and AstQt, and negatively with CAR. The policy implication of the study

recommends that better regulatory requirements will foster more CSR initiatives.

Another distinctive study by Shubiri et al. (2012)identified the financial and non-

financial determinants of corporate social responsibility (CSR) in Jordan .The

annual reports of 60 industrial companies listed on the Amman Stock Exchange

for a period from 2006 to 2010 in Jordan were used as a basis for the study. The

results of the analysis imply that companies that are expected to be large in firm

size, age of firm, maintaining growth and are highly leveraged are more likely to

voluntary disclose social responsibility information.

Harikkala (2010)identified the key determinants of CSR, the sphere of CSR and

the available guidelines to practice CSR. The study compared the found theory of

CSR with empirical findings from the Finnish banking industry. It evaluated how

banks utilize available information in their CSR strategies and communication.

Finally, it shows that the banking industry definitely follows guidelines and

provisions, but the extent to which it is a choice made by individual banks is

questionable. It is also revealed that while viable reports are published, the

implementation of reported measures is not disclosed either in writing or in

empirical findings. Ahmed et al. (2012)conducted a questionnaire survey on the

twenty domestic private banks of Bangladesh in order to show the relationship

between corporate social responsibility (CSR) and corporate financial

performance (CFP). The results of the study revealed that the average return on

asset ratios of the banks having high CSP is higher compared to that of the banks

having low CSP. In all cases of absolute comparison between ROA, EPS and P/E

ratio it was found that CSR banks outperformed the Non-CSR banks. Masud

(2011)conducted a descriptive research purely based on the information from

secondary data of annual reports for the year 2009-2010 of top five private

commercial banks listed on the Dhaka Stock Exchange (DSE). It is found in the

study that all banks contribute a little amount of profits to CSR. From the study it

is clear that participation of different areas of CSR activities of different banks is

limited. Another think noticed from the study that every bank has good attention

and consideration to education and health areas. Every bank of the study

contributed highest amount in education and the next area is health. Another

important matter, banks are very concern to contribute natural disaster and

disaster management specially cyclones (Aila), flood affected areas etc.

Moreover, Rouf (2011) designed an exploratory study to investigate the extent


and nature of corporate social responsibility disclosure (CSRD) in corporate

annual reports (CAR) of listed companies in Bangladesh. The result shows that a

higher proportion of independent non-executive directors on a board are

positively related to the level of corporate social responsibility disclosure but the

extent of corporate social responsibility disclosure is negatively related for

company‟s size. Another study investigates the data from Hong-Kong banking

industry collected through a questionnaire and identified four factors related to

CSR expenditure. It also concluded that management of a banking organization

should put in place an appropriate policy for establishing positive organizational

culture and socially responsible approach amongst the staff members. If

commitment for becoming a socially responsible banking organization among

board members, management and staffs is present while corporate accountability

and creditability can be demonstrated through effective and efficient internal

audit, customers and the community will be benefited with reduced risks and

enhanced quality(Shirley, 2011).

To sum up, studies on association between financial factors and CSR themes are

very infrequent in Bangladesh. Mostly, CSR are still an unexplored area in

Bangladesh, which creates notable scope for extensive and appealing research.

OBJECTIVES

The broad objective of this study is to identify the firm specific determinants of

CSR expenditure in the banking industry of Bangladesh. Consequently the

paper‟s aim is to understand the current state of CSR activities in this sector

under the guideline of Bangladesh Bank. Being part of the service industry,

banks have little impact on environment and are less concerned by challenges

related to human rights. But on the other hand, by considering the financial

power of this sector and its major role in the global economy, there is a necessity

to analyze different aspects of CSR activities of this industry.

METHODOLOGY

There are 35 private commercial banks (PCBs), 4 nationalized commercial banks

(NCBs), 9 foreign banks, and 4 developments banks in Bangladesh. Additional to

these numbers, recently another six banks have got license to commence in the

Bangladeshi market. Among them 30 local private commercial banks listed in

DSE are chosen randomly as the sample for this study. The sample excludes

public commercial banks, foreign banks and investment banks. This is due to

their different nature of ownership, operating guidelines and other regulatory

differences. The data set consists of 30 banks over 5 years (2008 - 2012) of

observation formed a completely balanced panel data set. Size differences in the

value of the observations across cross section and over time period has been

normalized with logarithmic transformation. Years before 2008 have not

cogitated because CSR activities are steering in a more systematized way from

the year 2008 after the circulation of BB guideline regarding this. Necessary data


for this study are collected from different secondary sources, as - bank‟s annual

reports, different organizations such as Dhaka Stock Exchage (DSE) and

Bangladesh Securities and Exchange Commission (BSEC), websites of the banks

and different publications of BB and DSE.

To examine the effect of firm specific characteristics of the banks on their CSR

expenditure the following cross sectional regression has been estimated:

Csrexpit = α + β ́ firm specific characteristicsit + εit …….. (i)

Thus, the functional form for financial characteristicsit is,

firm specific characteristicsit = ƒ (invit , assit , promexpit , intincit , totaldepit,

branchit, empit)

Here, CSR expenditure (logcsrexp) is dependent variable and total investment

(loginv), total asset (logass), promotional expenditure (logpromexp), interest

income (logintinc), total deposit (logtotaldep), no. of branch (logbranch), number

of employees (logemp) are used as the independent variables.

The model used the amount of CSR expenditure as dependent variable as it

characterizes firm‟s investment to social performance (Kitzmueller and

Shimshack, 2010). Moreover, by exercising CSR programs, firms can signal to

consumers that they are reliable, honest and will produce better products.

Accordingly, CSR is a form of product differentiation, a form of advertising to

establish or sustain brand loyalty (Siegel and Vitaliano, 2007). So, promotional

expenditure has been considered as one of the independent variable of this study.

Here total asset has been used as a proxy of firm size. Several authors used

natural logarithm form of total assets as a proxy of firm size rather than absolute

value (Lee & Song, 2013; Padgett & Galan, 2010; Brammer & Millington, 2008).

Besides, a content study (Singh and Aggarwal, 2011) refers that there is a

significant difference in community welfare and environment and rural

development when banks are compared with respect to number of employees.

Furthermore, it is an important step to understanding the effect of number of

branches on CSR as higher number branches is able to attract more deposits, a

reduction in costs through economies of scale. It also diversifies risks through

geographic expansion (Kuehn, 2014). Finally, total deposit, total investment and

interest income have been included in this study as these issues are important for

any banking operation (Hossain et al., 2013; Ogunbiyi and Ihejirika , 2014).

Finally, the regression equation is as below:

logCSRexp= α + β1 logInv + β2logAss + β3logProm Exp + β4logInt Inc +

β5logTotal Dep + β6logBranch# + β7logEmp# + ε …….(ii)

As it is a panel data set, for stationary testing Harris-Tzavalis z-statistics Test has

been used which is described by Harris and Tzavalis (1999). This has a null of

unit root versus an alternative with a single stationary value. It‟s designed to be

applied to data sets, which are relatively short in T. In order to provide relatively


exact corrections for small values, they very tightly restrict the model to exclude

the augmenting lags. Thus if the original panel is balanced (which they require),

it will remain so. The test assumes a homogeneous variance. It has large N, fixed

T asymptotic, again, with the centered and rescaled test statistic being N (0, 1).

Secondly, Hausman Specification Test has been done for choosing between two

panel OLS model: fixed and random effect. Finally, for regression panel OLS

model with fixed effect has been conducted in this study.

CSR IN BANKING INDUSTRY OF BANGLADESH AND REGULATORY

FRAMEWORK

Corporate social responsibility is “the responsibility of enterprises for their

impacts on society”. To fully meet their social responsibility, enterprises “should

have in place a process to integrate social, environmental, ethical human rights

and consumer concerns into their business operations and core strategy in close

collaboration with their stakeholders”(European Commission, 2011).Moral and

ethics are some of the drivers, while the values (both financial and ethical) and

culture of each individual company also have a great effect. The economic

incentives for CSR include demand for environmental/ethical products, public

image and material and energy efficiency. Bangladesh has a long history of

involvement in benevolent activities like providing donations to different

charitable organizations, poor people and religious institutions, city beautification

projects and patronizing art & culture, sports and education etc. These activities

constitute the primary basis of corporate social responsibility (CSR) for banking

industry in Bangladesh. Moreover, over the last decade banks have gradually

organized their involvements in more structured CSR initiatives with guidelines

of BB especially from the year of 2008.

Figure 1: CSR Expenditure by Bangladesh Banks over the 5 Year

Source: Review of CSR initiatives of banks by Bangladesh Bank- 2012

It is therefore encouraging that CSR activities of banks in Bangladesh have now

increased In 2012, the aggregate CSR expenditure of all the scheduled banks

totaled Tk. 3046.69 million, an eight-fold increase compared to the CSR

expenditure of 2008. The trend of sectoral patterns of CSR expenditure by

Bangladeshi banks for the year 2008 to 2012 are given below:


Table 1: The Trend of Sectoral Patterns of CSR Expenditure

for the Year 2008 to 2012

Sectors Taka in million

2008 2009 2010 2011 2012

Amount % Amount % Amount % Amount % Amount %

Humanitarian

& disaster

relief

58.6 14.27 125.1 22.59 460.41 19.76 188.03 8.59 788.37 25.88

Education 30.5 7.43 94.8 17.12 400.79 17.20 612.48 27.99 983.69 32.29

Health 112.1 27.29 245.5 44.33 689.07 29.58 520.42 23.78 435.43 14.29

Sports 49.8 12.13 1.2 0.22 265.23 11.38 359.07 16.41 183.85 6.03

Art & culture 0.8 0.19 0.3 0.05 328.91 14.12 171.52 7.84 213.31 7.00

Environment - - - - 59.78 2.57 138.07 6.31 140.23 4.60

Others 158.9 38.69 86.9 15.69 125.58 5.39 198.73 9.08 301.81 9.91

Total 410.7 100.00 553.8 100.00 2329.77 100.00 2188.32 100.00 3046.69 100.00


However, 16 PCBs, 3 SCBs and 1 FCB have formed separate Foundations or

Trustsas non-profitable institutions solely devoted to the cause of charity, social

welfare and other benevolent activities towards the promotion of CSR objectives.

45 out of 47 banks (2 SCBs, 4 SDBs, 30 PCBs and 9 FCBs) have taken steps for

adoption of socially and environmentally responsible practices in their own

internal operations in 2012. 2 SCBs, 2 SDBs, 28 PCBs and 6 FCBs reported have

taken actions towards providing a healthy and safe workplace and creating an

environment conducive to learning and development. Certainly, all banks have

embraced CSR in 2012 with decision at the highest corporate level. This is

shown in the table below:

Table 2: Number of Banks Ingraining CSR Practices within Own

Establishment and in their Client Businesses

CSR Objectives SCBs SDBs PCBs FCBs

Adopting Socially and environmentally responsible practices in own internal operations

2 4 30 9

Providing a modern, healthy and safe workplace and creating a learning and development environment

2 2 28 6

Reduce the bank’s environmental impact as a result of its operation and business activity

2 2 27 7

Fostering CSR in their client businesses 1 2 23 6


CSR Objectives SCBs SDBs PCBs FCBs

assessing the social and environmental impacts of the projects seeking finance

Ensuring compliance of regulatory environmental and social requirements

3 3 25 6

Engaging with clients in assessing project’s social and environmental impacts beyond the regulatory requirements

0 0 9 3


Regulatory Framework

National Board of Revenue (NBR) of Bangladesh issued Statutory Regulatory

Order (SRO) by providing tax exemption on the expenditure made by corporates

for CSR activities in 2011. The regulations stated in that SRO were further

amended in 2012 and the area of CSR applicable for tax exemption was

enhanced. The exemption facility is aimed at encouraging private companies to

be involved more in CSR conduct. In June 2008, Bangladesh Bank issued a

comprehensive circular titled „Mainstreaming Corporate Social Responsibility

(CSR) in banks and financial institutions in Bangladesh‟. In that circular, CSR

was defined as (a) considering the economic, social and environmental

consequences of a business, (b) mitigating the negative impacts and bolstering

the benign effects, (c) initiating action programs and community investments to

trim down social exclusion and inequality as well as to address the core

sustainable development challenges (fulfilling the requirements of the current

generation without cramping the capacity of future generations is a generally

agreed meaning of „sustainable development‟).

Bangladesh Bank has started guiding the banking sector to become more

environmentally responsive (e.g. via refinancing new loan products on solar

energy, bio-gas, effluent treatment plant etc.). All the commercial banks are

asked to formulate their own CSR policy with the annual outlay for CSR

programs and include the CSR programs in their mainstream banking activities

instead of short-term social works like providing grants, aids and donations. In

December 2010, Bangladesh Bank instructed the banks to establish separate CSR

desk to pay special attention on this issue. Reporting of the CSR initiatives by

banks was suggested as appendage to regular annual financial reports.


ANALYSIS AND FINDINGS

According to Pesaran and Pesaran (1997) if the variables are non-stationary then

it will generate spurious result. Nelson and Plosser (1982)led a large volume of

literature investigating possible non-stationarity of financial time series data.

Thus before proceeding with regression model, the test for the stationarity status

of the variables have been performed in order to determine the respective order

of integration of the variables under consideration. For this purpose Harris-

Tzavalis z-statistics has been conducted as it is the most suitable method for this

data set which has fixed time periods and finite panels. The result has been

shown in table 3:

Table 3: Result from Panel Unit Root Test

Variables Assumes common unit root process

Harris-Tzavalis z-statistics

Rho z-value Decision

Logcsrexp 0.1182** -2.6695** Stationary

Loginv 0.8720 4.4708 Unit Root

Logass 0.9157 4.8843 Unit Root

Logpromexp 0.4051 0.0480 Unit Root

Logintinc 1.1370 6.9806 Unit Root

Logtotaldep 0.8979 4.7161 Unit Root

Logbranch 0.7381 3.2020 Unit Root

Logemp 0.8220 3.9969 Unit Root

(**Indicates stationary at 5% significance level)

This test assumes that the number of panels tends to finite or infinite while the

number of time periods is fixed. The null hypothesis of the test is that the series

contains a unit root, and the alternative is that the series is stationary. It assumes

a common autoregressive parameter for all panels. Small sample adjustment to T

is applied. The result reveals that the CSR expenditure is statistically significant

because p-value of the z-statistics is less than 5% significance level. It means the

CSR expenditure accepts the alternative hypothesis of stationarity. All the other

variables such as investment, total asset, promotional expenditure, investment

income, total deposit, number of branch and number of employees are not

statistically significant because p-value of the z-statistics is greater than 5%

significance level. Hence, all the variables have unit root except CSR

expenditure.


As the data contains unit root, first difference has been used to remove the trend

of the data. Then panel unit root test is done on the first difference. The result of

the panel unit root test under first difference by removing cross sectional means

and using lag 0 is in table 4:

Table 4: Result from Panel Unit Root Test (With Individual Intercept and

No Trend under First Difference)

Variables Assumes common unit root process

Harris-Tzavalis z-statistics

Rho z-value Decision

Logcsrexp -0.542** -8.9255** Stationary

Loginv -0.175** -5.4477** Stationary

Logass -0.975** -13.020** Stationary

Logpromexp -0.330** -6.9168** Stationary

Logintinc -1.344** -16.515** Stationary

Logtotaldep -0.451** -8.0599** Stationary

Logbranch -0.238** -6.0419** Stationary

Logemp -0.569** -9.1771** Stationary

(**Indicates stationary at 5% significance level)

From the above result, it can be inferred that according to Harris-Tzavalis z-

statistics all the variables such as CSR expenditure, inv, ass, promexp, intinc,

totaldep, no. of branch and no. of employees are statistically significant because

p-value of the z-statistics is less than 5% significance level. It means all the

variables accept the alternative hypothesis and the data set is stationary under

first difference. So, the panel regression model can be applied to the data set.

For balanced panel data set two types of panel regression model are pertinent:

fixed effect and random effect. The regression result of fixed effect and random

effect has been provided below:


Table 5: Results of the Regression Model

Variables Fixed effect Random Effect

Long run coefficient

logInv -.580605 .1789295

logAss 2.503281 -.413178

logProm Exp .4714189** .4241064**

logInt Inc -.822357 -.6635923

logTotal Dep -.8911443 2.225402***

logBranch# 2.179088** .2285695

logEmp# -.4852537 -.1863485

Α -10.03072** -14.00831**

F-test 14.49*

LM test 31.79**

Hausman test 30.03**

R-square 0.1438

Rho .808707

Cross-section random 0.5353(.6909)

Period random 0.4093(.4574)

Idiosyncratic random 0.4852(.7525)

Values in the bracket represent standard deviation

(*,** and *** indicate significant at 1%, 5% and 10% levels, respectively)

To measure the effectiveness of both the model Hausman test has been

conducted. Hausman test examines whether the random effects estimate is

insignificantly different from the unbiased fixed effect estimate. If the null

hypothesis of no correlation is rejected, then the individual effects are

significantly correlated with at least one regressors in the model and it shows the

random effect model problematic. Therefore, the fixed effect model is better

rather than the random effect model. In this study, value of Hausman test is 30.03

(prob>chi2 = 0.000) the null hypothesis is rejected. So, there is a significant

difference between the fixed and random effect models. Thus the fixed effect

model is effective than the random effect model.

The result of fixed effect model (Appendix: Table – A1) represents the long run

coefficient of the panel regression showing the time-fixed effects. The regression

equation is:

logCSRexp = - 10.03 – 0.58 logInv +2.50 logAss + 0.47logpromExp – 0.822

logIntInc – 0.89 logTotalDep + 2.18 logBranch – 0.485 logEmp + ε ………. (iii)


The result shows that promotional expenditure and no. of branch have p-value

less than 5% significance level. Thus, the variables are statistically significant at

5% significance level in determining the level of long-term CSR expenditures by

the respective banks in Bangladesh. Since the beta coefficient of both

promotional expenditure and no. of branch are positive, it indicates that larger

the amount of promotional expenditure and larger the size of the bank in respect

to geographical outreach represented by number of branches, higher will be the

level of CSR expenditure. The result from the fixed effect model also suggests

that 80.88% variation in CSR expenditure is accounted for the cross sectional

difference as measured by the rho i.e. the interclass differences. The analysis of

variance (ANOVA) shows that the model‟s value of F-ratio at 5% significance

level with 7 and 113 degrees of freedom is F0.05 =2.09. The large F-ratio and its

small p-value (0.000) show the regression model is statistically significant.

CONCLUSION

Based on the above analysis, amongst all the determinants considered in the

study only two variables (promotional expenditure and number of branches) are

statistically significant. Compare to our total size of economy we have huge

number of banks. Therefore, banking industry is facing tremendous competition

from domestic as well as foreign banks. Hence, the banks expend huge amount of

money for promotional expenditure. Apparently they consider CSR activities as

their promotional activities.

On the other hand total number of branches has a great impact on CSR

expenditure. A bank with significant number of branches indicates its size. In

general big power begets big responsibility. For that reason, a bank with greater

size has to expend huge amount as CSR activities.

Day by day CSR is becoming more and more pronounced in the business sector

of Bangladesh. Banking industry is no exception. But the overall status of CSR in

Bangladesh is still very meager. Lack of Good Governance, absence of strong

labor unions or consumer rights groups, and inability of the business community

to perceive CSR as a survival pre-condition in the local market constitute some

of elements undermining the evolution of CSR practices. Consequently, the

message from the government is that CSR shall be applied both „inside‟ and

„outside‟ the company, but emphasis should be given to the environment, the

society and the workers.

Additionally, by leveraging Bangladesh Bank‟s policies in the fields of

consumption, investment and public procurement it is possible to promote market

reward for responsible business conduct by the banks. Furthermore, better

alignment between BB‟s approaches and global approaches to CSR can be

achieved by improving company disclosure of CSR information through a new

legislative proposal on this issue, monitoring the Corporate Governance system


in the industry, building and supporting a strong labor union, consumer rights

group, environmental right groups and human right group.

All in all, banks should identify their prioritize responsibilities towards the

society other than financial attainment. Through which they will be able to solve

societal problems which is impossible individually.

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APPENDICES

Table A-1: Fixed effect model

Table A-2: Random Effect model

.

F test that all u_i=0: F(29, 113) = 5.28 Prob > F = 0.0000 rho .80870749 (fraction of variance due to u_i) sigma_e .75255349 sigma_u 1.5473342 _cons -10.03072 4.596083 -2.18 0.031 -19.13639 -.9250491 emp -.4852537 .7319378 -0.66 0.509 -1.935354 .964847 branch 2.179088 .7768018 2.81 0.006 .6401039 3.718073 totaldep -.8911443 1.389127 -0.64 0.522 -3.643255 1.860966 intinc -.822357 .6109096 -1.35 0.181 -2.032679 .3879651 promexp .4714189 .2114497 2.23 0.028 .0524989 .8903388 ass 2.503281 1.56577 1.60 0.113 -.5987912 5.605354 inv -.580605 .4723867 -1.23 0.222 -1.516488 .3552782 csrexp Coef. Std. Err. t P>|t| [95% Conf. Interval]

corr(u_i, Xb) = -0.6304 Prob > F = 0.0000 F(7,113) = 14.49

overall = 0.1438 max = 5 between = 0.0820 avg = 5.0R-sq: within = 0.4730 Obs per group: min = 5

Group variable: id Number of groups = 30Fixed-effects (within) regression Number of obs = 150

. xtreg csrexp inv ass promexp intinc totaldep branch emp, fe

.

rho .45740668 (fraction of variance due to u_i) sigma_e .75255349 sigma_u .6909576 _cons -14.00831 3.71583 -3.77 0.000 -21.2912 -6.725414 emp -.1863485 .3940044 -0.47 0.636 -.9585828 .5858859 branch .2285695 .4083177 0.56 0.576 -.5717185 1.028858 totaldep 2.225402 1.248944 1.78 0.075 -.2224829 4.673286 intinc -.6635923 .5705683 -1.16 0.245 -1.781886 .454701 promexp .4241064 .1653471 2.56 0.010 .100032 .7481807 ass -.413178 1.263809 -0.33 0.744 -2.890198 2.063842 inv .1789295 .1973761 0.91 0.365 -.2079205 .5657796 csrexp Coef. Std. Err. z P>|z| [95% Conf. Interval]

corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(7) = 110.51

overall = 0.4852 max = 5 between = 0.5353 avg = 5.0R-sq: within = 0.4093 Obs per group: min = 5

Group variable: id Number of groups = 30Random-effects GLS regression Number of obs = 150

. xtreg csrexp inv ass promexp intinc totaldep branch emp, re


Table A-3: Hausman Specification test

Prob>chi2 = 0.0001 = 30.03 chi2(7) = (b-B)'[(V_b-V_B)^(-1)](b-B)

Test: Ho: difference in coefficients not systematic

B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg emp -.4852537 -.1863485 -.2989053 .6168415 branch 2.179088 .2285695 1.950519 .6608311 totaldep -.8911443 2.225402 -3.116546 .6081221 intinc -.822357 -.6635923 -.1587647 .2183171 promexp .4714189 .4241064 .0473125 .1318003 ass 2.503281 -.413178 2.916459 .9243498 inv -.580605 .1789295 -.7595345 .4291758 fixed random Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients

. hausman fixed random

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