impact of corporate governance on performance of mfis

Impact of Corporate Governance on Performance of MFIs: A Case from Pakistan

Raheel Gohar (Corresponding Author)

Assistant Professor

Dar Al Uloom University (DAU)

College of Business,

Riyadh, Kingdom of Saudi Arabia.

[email protected]

Tel: +966-505213088

Fax: +966-1-4949490

Amna Batool

Lecturer

COMSATS Islamabad.

[email protected]

mailto:[email protected]

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Impact of Corporate Governance on Performance of MFIs: A Case from Pakistan

Abstract

The determinants of economic/financial, social performance and productivity of twenty five

MFIs are estimated for the period 2005 to 2009 in case of Pakistan. The results indicate that

the governance variables influence the performance (economic and social) and productivity

of the MFIs in Pakistan. Larger boards inversely effect economic performance but has a

positive effect on outreach and productivity. Female directors do not play role in improving

economic performance but effect positively outreach. Duality of chair with CEO is a negative

contributor to performance, outreach and productivity. The firm size, experience, regulated

MFIs, non-profit activities in lending have positive effect on performance outreach and

productivity.

Keywords: Corporate governance, Financial performance, Microfinance Institutions,

Pakistan, , Social performance.

JEL CLASSIFICATION: G21, G32

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1. INTRODUCTION

Provision of loans, savings and other basic financial services like insurance, to the poor and

deprived segment of economy is referred as Microfinance (MF). Microfinance facilitates

poor and near poor households by providing them permanent access to not just credit but also

savings, insurance, and fund transfers against no collateral. (Christe, Roseberg, and Jayadev;

2004).

Major reason of poverty in developing economies is lack of credit availability to poor. Two

major reasons for non availability of loans to poor are: Inability of poor clients to provide

acceptable collateral and banks find it more costly to screen the poor customers i.e. problem

of adverse selection and to monitor the repayment by poor i.e. problem of moral Hazard.

Survey conducted by United Nations (UN) has found that almost one fifth of world

population is living in extreme poverty and their earning per day is less than dollar.

Microfinance is considered to be important instrument to combat with extreme poverty. UN

put lots of emphasis on microfinance for achievement of Millennium development goals

which aims at halving the extreme poverty. Concept of solidarity group lending is playing

boosting role in development of MF sector. It facilitates both the micro entrepreneurs as well

as credit providing institute. Peer pressure and mutual support of the entire group members

encourage each individual of group to put in best efforts for loan repayment as inability of

repayment will forfeit the chance for further loan. Pay back rates of group loans is

approximately 98% which is higher than individual loan repayment rate.

In evolution of MF sector two factors have brought tremendous progress. First, poor people

have very good repayment rates especially women and secondly, it is found that poor people

are ready and able to pay subsidized interest rate for survival and better performance of

Microfinance Institutions (MFI’s). Further more studies have shown that most of the loans

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are given to women by MFI’s that not only reinvest their earnings but also spend on their

families. It helps to improve their standard of living as well as community get benefit due to

job creation and knowledge sharing.

MF sector of Pakistan has well developed legal, regulatory and strategic framework. MFIs

have been working since late 1980’s but mentionable efforts of MFIs have started after

period of 2000. This sector plays an important role in alleviating poverty, improving living

standards of individuals and providence of health and education to deprived segment of

society. Lots of researches have been conducted to evaluate the performance of MFIs in

Pakistan which came up with guiding results. But up till now there is lack of studies which

cover Corporate Governance (CG) impact on MFI performance. Literature has recognized

good CG as key element for success of MFI. Importance of CG mechanism is alike for both

developing and developed sophisticated economies. Now long- term capital growth is not

possible for countries that lag behind in adoption of CG practices.

Concept of corporate governance was introduced globally in late 1990s. In Pakistan code of

corporate governance was applied to business firms in year 2002. For designing CG

framework of different type of business, it requires to cover different areas. MF entities are

of various types depending on variations among their institutional structures. Some NGOs

are incorporated and Securities and Exchange Commission of Pakistan (SECP) regulates

them, some work as societies registered under societies act and some are governed by

Ministry of Industries and work as Trust. So they do not have a single transparent and formal

governance structure and processes to follow.

The aim of this research is to study the relationship between performance and different

dimensions of CG for regulated MFIs of Pakistan. So the results of this research can be used

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to make a clear, well defined and formal CG structure to MFIs which ensure success of MFIs

in terms of both outreach and sustainability.

First time for Pakistan, this study is evaluating relationship of economic and social

performance of MFIs with corporate governance. This study helps to understand the current

scenario of MF sector regarding to economic and social performance, outreach and

productivity and also suggests that how MFIs in Pakistan can be improved if good

governance practices are introduced. This study also investigates that firm specific

characteristics such as type of lending, firm size, lending status (profit or non-profit) and

years of experience also contribute to performance and productivity.

This research is organized as follows. After introduction the overview of MFIs in Pakistan is

provided in section 2. The brief literature review of studies is given in section 3. The

empirical methodology and data is discussed in chapter 4. Chapter 5 presents the empirical

results and last section chapter 6 concludes the study.

2. OVERVIEW OF MICROFINANCE IN PAKISTAN

This section presents the origin and development of MF sector in Pakistan. Over view of MF

sector and different types of MFIs operating in Pakistan are also discussed and challenges

faced by various operational levels of MF sector are also presented in this part.

2.1. Origin and development

GNI per capita of Pakistan is $2780 by year 2010.With this figure Pakistan is ranked as low

income country. Almost 22.3% of total population is living below poverty line and 20.5% is

living on the 100-125 % of poverty line. Pakistan is facing problem of poverty since its

independence. Microfinance is considered as one of the important tool for eradicating the

poverty as well as it increases women empowerment. In Pakistan, microfinance is first

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introduced by development of Agha Khan Rural Support Program (AKRSP) and Orangi Pilot

Project (OPP) in early 1990s. These MFI’s were setup with the purpose of providing credit to

poor and alleviate poverty. In 1990’s Government of Pakistan (GoP) and Central Bank

realized that MF is key component of financial sector. At that time large number of

institutions was developed with the objective of offering micro credit on group lending basis.

With passage of time increase in number of new entrants, products, practices and growing

clientele showed expansion of Pakistan MF sector. In year 2000 MF sector experienced rapid

growth with establishment of Khushhali Bank (KB), first specialized microfinance bank and

Pakistan Poverty Alleviation Fund (PPAF) an apex funding body. Moreover, in year 2001

formulation of Microfinance Ordinance, invites commercial players to take part in MF

activities and bring some expansion in the sector. State bank of Pakistan (SBP) also takes

different initiatives for the florishment of MF sector. In year 2007, SBP and MF stake

holders together have designed a strategy named “Expanding Out reach of Microfinance”

(EMO). Main objective of this was to achieve target of three million borrowers by year 2010

and for year 2015 target of 10 million borrowers was set out.

2.2. Overview of Pakistan Microfinance Sector:

Due to its well-developed legal, regulatory and strategic frame work, the MF sector of

Pakistan is globally recognized. In terms of both outreach and asset base MF industry of

Pakistan is still very small. Currently MF sector is serving 2.07 million borrowers

representing that only 7% of potential market is served. Penetration level is lowest in

Pakistan. 56% of target market is totally excluded and 32% are served through informal

ways. Microfinance institutions are operating in country through 1379 branches and serving

almost 2.07 million borrowers with gross loan portfolio of PKR 26.4 billions. MF sector is

mainly operated by few major institutions which jointly serves 85% of the market. These are

fastest growing players of MF sector. Most of MFI’s are operative in provinces of Punjab and

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Sindh. Most of specialized MFIs are operative in Punjab due to its infrastructure and higher

population density. 60% of active borrowers are from Punjab and 23% of them are from

Sindh. These provinces attract maximum business of MFIs due to their dense population. By

year 2009, 56% of credit clients are women. Among the other peer groups, MFI peer group is

serving maximum women and its 90% of clients are women. Asset base of MF sector

reached to PKR 35 billion. Seven major MFIs hold 85% of total industry’s assets. Industry

improved its profitability in year 2009. Globally, industry was less profitable but some RSPs

and MFIs have positive ROA. One of the prominent reasons for low profitability is high

personnel ration for Pakistan. Group lending methodology is adapted by most of MFIs for

providing loans which are primarily used for agriculture, livestock and trade businesses.

Typical size of loan is from $100 to $500. Individual loans are also offered by some MFI’s as

most of them wants to avoid the risk associated with non social collateral in case of

individual loan.

3. LITERATURE SURVEY

A large body of literature exists on the economic and financial performance of MFIs and

their outreach for other developing countries; however, very few studies have been done for

Pakistan. As regards the impact of corporate governance on MFIs performance limited

research has been done so far and in case of Pakistan this research is non-existent. This

section provides the brief review of empirical literature in this area.

Keasey, Steve and Write (1997) concluded that framework of effective governance

comprises of key mechanisms like ownership, board and structure of boards, CEO, Director,

remuneration, auditing and markets for corporate control. Ownership checks whether firm is

owned by any institute or manger. Board structure will look for how large board is and of

which members it is composed of.

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Hartarska (2005) in her study of Central Europe and newly independent states found that

different CG mechanisms affect performance of MFI differently. For example, External

mechanisms of control i.e. auditing, regulation and rating of MFI, management remuneration

and board independence and diversity all have different impact on the outreach and

sustainability of MFI. Supervision by regulatory authority and Independent agency rating has

no impact on both sustainability and outreach. Auditing does not affect sustainability but

have positive impact on outreach. Characteristics of board have major effect on both

sustainability and outreach with MFI having local board have better sustainability, having

larger boards have poor performance and MFIs with boards comprising of higher proportion

of insiders showed worse financial results. Sustainability as well as depth and breadth of

outreach are improved when there is woman on board. Breadth of outreach is improved due

to presence of local businessmen on board but it does not affect sustainability. Presence of

financers and members with diverse skills enhances sustainability. Presence of donor

representatives on board promotes depth of outreach but have negative impact on breadth of

outreach and sustainability. Clients on board decrease the depth of outreach but improve

sustainability. There is no relation between MFI performance and performance based

compensation of manger. Less outreach is observed for such MFIs who have under paid

mangers. Experience of manger has weak positive impact on depth of outreach and no impact

on sustainability.

Akash (2008) studied some governance and ownership aspects of MFI’s of Bangladesh. He

found that top most MFIs of Bangladesh having entirely different ownership structure.

Results showed that performance of MFI has nothing to do much with its ownership

structure.

Mersland and Storm (2009) in their study of Central Europe and newly independent states

found that the presence of international directors and internal board auditors have no impact

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on financial performance of MFI. CEO / Chairman Duality undermine financial performance

and increases cost. Female CEO tends to decrease cost and improves financial performance.

Financial performance has no relation with the ownership type. Regulation shows the relation

with performance as it gives customers a feeling that they are treated fairly. Female CEO has

lesser branches. Monitoring practices are less in MFIs having larger boards. Outreach is

greater in case of group lending. Providence of individual loans decreases number of credit

clients but improves average loan. Number of clients increased with CEO/ Chairman duality.

MFI sector start emphasizing on individual lending instead of group loans which shows that

sustainability is given more importance by sector than outreach. MFI regulated by

Government has lower risk exposure and more experienced MFI faces more risk.

According to Keasey et al., (1997) effective governance framework should cover ownership,

board and board structure, CEO remuneration, director, auditing Information and nature of

corporate control. Fama and Jensen (1983) put large emphasis on the nature of MFI board

and its impact on performance of MFI. Lipton and Lorch (1992) found that large boards are

less effective than smaller boards. Internal board members show independence and have

positive impact on performance (Oxelheim and Randoy, 2002).

Board diversity is another important CG mechanism. Carter, Simkins and Simpson, (2003)

found that boards having higher proportions of women and ethnic minorities perform far

better. Presence of MFI clients on the board of MFI affects the performance.

Ashbaugh and Warfirelid (2003) pointed out auditing as most important aspect of CG. They

found positive relation between audited financial statement and MFI performance.

Scott and Hopkins (1999) have shown that if NGO mangers pay and for profit managers pay

are same and NGO has edge in technology over for- profit firm, then NGO will outperform

the industry.

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Adoption of best CG standards by MFIs helps them to achieve their social as well as their

commercial objectives and aims. Microfinance industry can increase its depositors,

borrowers, counter parties and investors by adherence to best CG mechanism. Furthermore

shareholders of MFI which has clear CG practices are protected against risks and are sure

about multiplicity of their wealth. Regulatory authorities can also get benefit from CG

practices as it helps in reducing frauds and mismanagement.

Different set of rules and different mechanisms are used by researchers for explanation of

best CG practices. Whatever theses dimensions are, but all of them strive to achieve fairness,

responsibility, respect for rights, corporate integrity, loyalty, compliance with regulations,

and transparency.

4. DATA AND METHODOLOGY

This section discusses the methodology used to estimate the performance and productivity

relationship with good governance in case of Pakistani MFIs. The data and sources of data

are also presented.

4.1: Data

Currently large number of MFIs is operating in Pakistan. However only 31 out of them are

regulated by September 2010, and other are non-regulated. Focus of this study is regulated

MFIs only. 27 MFIs out of 31 are member of Pakistan Microfinance Network (PMN) and

constitutes almost 95% of MFI business in Pakistan (State Bank of Pakistan, Department of

Microfinance, Jan 2011). Our data set comprises of 25 MFIs (list is provided in Appendix

“A”) for period of five years from 2005 to 2009. Those MFIs are included in data set whose

data is available for at least two consecutive years.

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Pakistan Microfinance Review has been used for information about institutions financial

performance, outreach and productivity. However individual social performance reports of

each company were accessed to collect data about governance mechanisms. MIX

(Microfinance Information Exchange) accessed through (www.mixmarket.org) provides

online information about MFIs operations and performance. Individual websites of MFIs

were also accessed to collect information regarding to Board characteristics and area of

operation.

4.2: Methodology

Performance measures are regressed on the corporate governance variables and other control

variables to examine the impact of corporate governance on the economic and social

performance of MFI.

The study estimates 6 performance models: three for economic and financial performance

and three for social performance (Table I); where Return on Asset (ROA), Operational Self

Sufficiency (OSS), and Portfolio Yield (PY) are used as performance measures. Social

performance is captured by outreach measured by 3 variables: Average Loan (AVL), Credit

Client (CC) and Number of Branches (NB).

“Please insert Table I about here”

Financial performance is measured by accounting based indicators i.e. ROA, OSS and PY.

As it is suggested that for studies with longer period of time accounting measures are more

appropriate as managers cannot manipulate financial statements for more than one year.

Three variables are used to measure corporate governance: Board Size (BS), CEO duality

(CEO), Female Director (FD). Other determinants of performance include: experience of

MFI (AGE), Firm Size (FS), productivity (PROD). Different measures are used to show

http://www.mixmarket.org/

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productivity of different types of business concerns. However in services sector like banking,

insurance and MFI productivity is calculated on the basis of labor productivity i.e. how much

output (number of clients produced) by incorporating how much input (number of staff

members). In Table II the individual loan made by MFI is represented by type of MFI

(INDL), MFI is regulated or not (REG), Urban Markets (UM), share holding firm (SHF). In

case of type of lending , group and other type of lending is taken as base category; for

regulated, unregulated; for urban markets, rural market; for non-profit, profit seeking MFI is

taken as base category.

“Please insert Table II about here”

These performance models are estimated for 25 MFIs belonging to Pakistan for the period of

2005 to 2009. As there are repeated observations for financial and social performance

variables for up to five years, while independent governance variables are reported once and

considered as constant throughout the whole period, so panel data estimation technique is

used to study the performance and productivity models. The common effect model, Fixed

model and Random Effect models are estimated. The Huasman test which tests the

asymptotically distributed chi square under the null hypothesis that the Random effect model

is better estimated turns out to be insignificant accepting that Random effect model describes

the data better.

Greene (2003) formulates Random Effect Model for such kind of panel data estimation. Due

to non- availability of data of some MFIs for the research period, this study has unbalanced

panels.

This study uses Multiple Regression Model to support hypothesis by taking six performance

variables (PV), ROA, OSS, PY, AVL, CC and NB as a dependent variable.

Model is as follow:

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………. (I)

The explanations of the variables are given in Tables I and II.

The study also investigates whether the productivity of the MFIs in Pakistan is affected by

good governance practices and performance (financial and social) of the firm after taking

account of firm specific control factors. The following models are estimated as suggested by

Cotler (2010):

……………. (II)

The PVit in equations (II) is financial and social performance variables as listed in Table I.

5. EMPIRICAL RESULTS AND DISCUSSION

First of all descriptive statistics is presented in Tables III and IV for all performance

measures, all determinants of performance measures and Corporate Governance measures.

Table III shows that the MFIs in Pakistan have negative return on asset and some

organizations also earns up to 16.32% on its assets. The operational sufficiency of the

institutions is good which shows that MFIs in Pakistan can manage in better way to cover

their costs through operating revenues. Portfolio yield of MFIs is also stable over the study

period but it shows that number of voluntary deposits at MFIs is not too large. In Pakistan,

making investments in MFIs is not considered as profitable so PY have less mean value. We

take natural log of Average loan and No. of credit client to mitigate the variation problem.

Figures for CC and NB show that overall Pakistani MFIs have small client base and shortage

of branches throughout the country.

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“Please insert Table III about here”

Table IV reports descriptive statistics for performance determinants and important corporate

governance variables are also presented.

“Please insert Table IV about here”

Table IV shows that number of observations of most independent variables are so small as

compared to number of observations of dependent variables in Table III. This difference in

number of observations is due to fact that former variables are used to explain firm’s fixed

characteristics, and give rise to use of Random effect model for estimation. Mean value of

variable can be interpreted as percentage of MFIs in that specific category. According to our

data average board size is 10 people in an organization and it deviate up to 50%. Chairman

/CEO duality is observed in 50% of organizations which is too high. Only 17% organizations

have female representation on their board.

This institution gives 42% loan to the individual customer for developing self employment

setup. And rest loans given on group bases to providing the credit facility to maximum

number of poor people. In the whole region 34% organizations are regulated by the bank

because the main capital provider is bank.

According to our sample 41% organizations facilitating the urban customer and remaining

59% organizations main focus is rural area. The age of the MFIs shows the time from when

the MFI industry is focused on the development of the poor in Pakistan. On average, age of

MF industry is 9 years. Some institutions are older up to 22 years but a recent start of twenty

first century show the flourishing of this industry. This study takes the log of the total asset to

measure the firm size. Productivity variable shows the efficiency of MFI as well as staff of

MFI. Mean value of Productivity shows that within given resources staff of MFIs in

Pakistani MFIs is performing outclass. Figure for Firm size shows that asset base of Pakistani

MFIs is not too large.

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5.1. Econometric Evidence and Results

In this section, panel data estimation results for the relationship of performance with

corporate governance variables are presented. The corporate governance variable includes

board size, CEO-chairman duality, and presence of female directors on the board. The set of

MFI specific variables include: years of operating in the market (Age), productivity

(PPROD), firm size (FS) measured as logarithm of total assets, lending to urban or rural

clients (UM), MFIs is giving loans to individual or group lending (IND), MFIs are regulated

or unregulated (REG), MFIs are profit non-profit organization (NPO).

5.1.1. Financial and Economic Performance

The Table V shows results from regression with ROA, OSS and Portfolio Yield as dependent

Variables.

“Please insert Table V about here”

Regression results show that board size is negatively related with ROA i.e. large board have

negative influence the economic and financial performance (ROA) as it becomes difficult to

handle large boards and to reach consensus about management decisions. This results support

Yermack (1996); Eisenberg et al. (1998); Bohren and Strom (2010), when firms performance

is measured as Tobin’s Q or ROA, larger boards are associated with lower firm performance.

The board size is negatively associated with Portfolio Yield of MFI. The CEO/Chairman

Duality has negative significant association with ROA and OSS. CEO / Chairman Duality

decreases ROA. Hermalin and Weisbach (1991) also have found that CEO prefers the

policies for his private benefits referred as CEO entrenchment. CEO / Chairman Duality is

known case of CEO entrenchment. Results for FD show that financial performance is not

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affected by presence of female members on board of directors as found by Smith et al. (2006)

who found no impact of female directors on financial performance of firm.

As regards the MFI specific characteristics, with increasing years of operations of FMIs,

ROA, OSS and PY of MFI are significantly improved. Already existence of MFI in this

sector helps them to reduce monitoring cost clients and there good relations with clients help

them to retain large number of clients which increase PY. There exits significant relation

between ROA, PY and labor productivity. Better the productivity of firm more will be its

ROA and PY as efficient staff motivates people to repay loan as well as attract new people to

make new investments. Firm size has significance relation with financial performance. Large

firms having large asset base out performs on three scales i.e. ROA, OSS and PY.

The results show that there is no impact of MFIs urban market relative to rural market on

financial performance of MFI which is not consistent with Armendariz and Morduch (2005)

study. According to their results MFIs operations in urban areas have positive significant

impact on performance for our research. Reason of inconsistency is strong and old RSPs in

Pakistan as compared to new entrants which mainly serve in urban areas. Individual loans

have significant on financial performance. It aligns with new trend of shifting from group

lending to individual lending. Our results also support that preferring individual loans due to

cost effectiveness over group lending due to more repayment improves financial performance

(Armendariz and Morduch, 2005).

Regulations have significant impact on MFIs financial performance because in regulated

MFIs customers have trust in MFIs. However, our results are not consistent with Hartarska

and Nadolnyak, 2007. The non-profit MFIs NPO has negative relations with financial

performance. Our results are consistent with results of Nieto et al, 2009. NPOs poor

performance can be attributed to weaker structure, as their owners do not have financial stake

in operations (Jansson et al, 2004).

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5.2.2. Outreach and Social Performance

The Table VI shows results from regression with, average loan size, number of credit clients

and number of branches as dependent Variables. The set of governance variables and MFI

specific variables remain the same as in economic performance

“Please insert Table VI about here”

Regression results show that board size has significant Impact on outreach. Larger boards are

known for delayed decisions which implies for reduced capacity of monitoring. However

number of branches increases with increase in board size but overall board size have negative

relation with outreach. CEO / Chairman Duality has no significant impact on outreach.

Female directors have positive impact on outreach when measured with average loan size.

Age of MFI is negatively associated with number of branches; it implies that old MFI's will

have less out reach. Inconsistency of results may be due to existence of two –three very old

MFIs in Pakistan but operating through just 2 or 3 branches with in city of their operation.

Examples are Sungi Development and Orangi Pilot Project. Results show that productivity

improves out reach. It is obvious that when firms factor of production are more productive

there will be more outreach in terms of average loan size and credit clients. Firm size has

positive significant impact on outreach. Firm has greater Asset base so can easily extend its

branches, provides more facilities to clients which results in more credit clients. Regulation

by banking authority has significant impact on outreach. It is more trusted by customers as

well as regulated MFI indulge itself in more risky lending because it is protected by

Government. Due to supervision of banking authority MFI can make savings which serves as

source of funding and results in increased number of clients and increase average loan

amount.

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Results suggest that there is significant impact of non-profit MFIs on outreach. It is

consistent with study results of Mersland and Strom (2009). According to them impact of

ownership is relatively more in outreach then in financial performance. Being NPO reduces

size of loan which shows that they reach more towards poorer people. Individual loan

methodology has no impact on outreach. Results are consistent with Mersland and Strom

(2009). According to them, group lending increases, average loan size but decreases credit

clients and branches.

“Please insert Table VII about here”

Regression results presented in Table VII shows that the larger board results in increasing

productivity, aged the firm more productive it will be consistent with the results of Cotler

(2010). Increase in firm size and provident of more loans to individuals improves as

productivity as number of credit clients per staff member increases. Target market of MFIs

has significant relation with productivity. Productivity decreases with MFIs operations in

urban market. In NPO productivity of MFI is better. OSS has significant impact on

productivity but PY has no impact on it.

“Please insert Table VIII about here”

Regression result shows that larger board improves productivity. Aged a firm more will be

productivity consistent with the results of Cotler (2010). CEO / Chairman Duality have

negative impact on productivity. Increase in firm size improves productivity. Individual

lending, bank regulation and non for profit MFI are positively affect productivity. Among

outreach variables average loan size has negative significant impact on productivity and more

CC will result in more productivity. However, numbers of branches have no significant

relation. Results of Table VII and Table VIII show that productivity of MFIs have much to

do with governance and performance measures. By adhering to good CG, MFI not only

outperforms but also can improve its productivity.

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Overall the results of the study indicate that governance variables influence the performance

(economic and social) and productivity of the MFIs in Pakistan. Larger boards inversely

effect economic performance but have a positive effect on outreach and productivity. Female

director do not play role in improving economic performance but effect positively outreach.

Duality of chair with CEO is a negative contributor to performance, outreach and

productivity. The firm size, experience, regulated MFIs; non-profit activities in lending have

positive effect on performance outreach and productivity. Urban lending relative to rural

lending has no significant impact on the performance and productivity of MFIs in Pakistan.

6. CONCLUSION

Micro financing i.e. providence of credit facility to poor who are unable to provide any

collateral plays an important role in poverty alleviation and women empowerment. Success

of MFI can be measured on the basis of its outreach and financial sustainability. Good CG

refers to a system of people, values, criteria, processes and procedures that ensure that an

organization is managed properly and that guides it towards its mission and vision. Literature

showed that better performance of MFI can be by adherence to good CG. Studies about CG

of various sectors have been conducted in Pakistan excluding to MF sector. However, CG

mechanisms are industry specific and vary from sector to sector. In order to fill this gap, this

research studies the impact of governance mechanisms on the performance of MFI for

Pakistan. 25 MFI’s who are member of PMN is used as focus of study. These 25 MFI’s

represents 95% business of Pakistani MF sector. Study period is from year 2005-2009. PMR

is used for performance, while Social performance report of each company serves the

purpose for collection of data of CG mechanisms. MIX serves an important online source of

data. Panel data estimations will be made by using Random effect Model Estimation.

Dependent variables i.e. ROA, OSS and portfolio yield are used to express the financial

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performance of MFI, and dependent variables used to express outreach are number of

branches, number of credit clients and average loan. To capture the impact of CG governance

independent variables used are CEO/chairman duality, board size, female CEO, SHF, NPO,

Individual loan, Bank regulation and urban market. Further impact of good CG and

performance both financial and social performance on MFI productivity is studied. Results

showed that MFI Age, Productivity of MFI, Firm size of MFI, Individual lending and Bank

regulations have positive significant impact on financial performance. However Board size

and CEO/ Chairman Duality has negative impact on financial performance. Female director,

Productivity, Firm size, Urban Market, Bank regulation have significant positive impact on

outreach and Board size has negative impact on outreach. Also find that there is significant

role of CG mechanism and MFI performance in boosting productivity of MFI.

This study highlights the fact that, as different regulatory authorities regulate different type of

MFIs so there exist remarkable difference in CG mechanisms followed by them for good

performance. This study provides the stakeholders of MF sector with such findings that can

lead them to efficiency and flourishment by giving them a unanimous code of corporate

Governance. On revisiting Expansion of Microfinance Operations (EMO) strategy 2007,

State Bank of Pakistan also found that inefficiency of MF sector can be attributed to absence

of defined CG code. This study suggests the impact of different CG mechanisms on

performance of different types of MFIs and suggests results which are applicable to MF

sector as a whole. Therefore it is recommended to apply these CG practices across the MF

sector to improve its performance.

Due to data availability constraint very few CG mechanisms are studied. Few very important

mechanisms like independent auditor and independent director which are considered as very

important CG mechanisms by literature are not studied here and this area is suggested for

future research.

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Armendariz de Aghion, B., and Morduch, J., 2005, The Economics of Microfinance. (MIT Press,

Cambridge).

Ashbaugh, H., and Warfield, T.D. 2003, Audits as a Corporate Governance Mechanism:

Evidence from the German Market, Journal of International Accounting Research 2, pp.1-21

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24

Table I: Description of dependent variables

Financial Performance Measures

Variable Explanation

ROA Return on assets; measures how well the MFI uses its total assets to

generate returns. It is adjusted for grants, donations and inflation, and is

obtained by Adjusted Net Operating Income / Average Total Assets.

OSS Operational self-sufficiency; Measures how well the MFI can cover its

costs through operating revenues. It is adjusted for grants and donations

and is obtained by Operating revenue / (Financial expense + Loan Loss

Provision + Operating Expense).

PY Portfolio Yield; it measures number of depositors maintaining voluntary

demand deposit and time deposit accounts with an MFP, adjusted for

inflation and is obtained by (Yield on Gross Portfolio (nominal) -

Inflation Rate)/(1 + Inflation Rate)

Social Performance Measures


AVL Average Loan Balance per Active Borrower; Indicates average loan

balance outstanding and is obtained by taking natural log of average loan

balance

CC Credit Client ; number of individuals that currently have an outstanding

loan balance with the MFI or are responsible for repaying any portion of

the gross loan portfolio and is measured by taking natural log of the

number of current borrowers

NB Number of Branches of MFP

25

Table II: Description of independent variables

Corporate Governance Measures


BS Board Size i.e. Number of directors on board

CEO CEO/chairman duality i.e. CEO and chairman are the same person

FD Female Director; A dummy indicating a female when 1

Other Performance Determinants


AGE MFI Age; Years of experience as an MFI

PROD

Productivity; It looks for how much output is produced by given

input. Total number of loan clients divided by total number of

employees

FS Firm size; The natural logarithm of assets

UM

Urban market; A dummy with the value 1 if the market served is

urban only

INDL

Individual loan; A dummy with the value 1 if loans are made

mainly to individuals

REG

Regulated MFI; A dummy with the value 1 if the MFI is regulated

by banking authorities

NPO Not for Profit Firm; A dummy indicating a non- profit firm when 1

26

Table III: Descriptive statistics of Dependent Variable

The table presents 6 performance models: three for economic and financial performance and

three for social performance; where Return on Asset (ROA), Operational Self Sufficiency

(OSS), and Portfolio Yield (PY) are used as performance measures. Social performance is

captured by outreach measured by 3 variables: Average Loan (AVL), Credit Client (CC) and

Number of Branches (NB).

Variables Mean Maximum Minimum Std. Dev.

ROA -7.037 16.320 -32.100 9.525

OSS 88.270 278.700 3.130 42.176

PY 11.701 34.930 -17.200 8.754

AVL 9.157 10.309 7.003 0.525

CC 9.871 13.732 3.951 1.628

NB 52.650 581.000 1.000 105.332

27

Table IV: Descriptive statistics of Independent Variables

In this table three variables are used to measure corporate governance: Board Size (BS), CEO

duality (CEO), Female Director (FD). Other determinants of performance include:

experience of MFI (AGE), productivity (PROD) and Firm Size (FS). Other variables include

Urban Markets (UM), type of MFI (IND), MFI is regulated or not (REG), and non-profit

MFI (NPO).

Variable Mean Maximum Minimum Std. Dev.

BS 10.49 20.00 5.00 4.27

CEO 0.50 1.00 0.00 0.50

FD 0.17 1.00 0.00 0.38

AGE 9.38 22.00 1.00 5.47

PROD 143.48 501.00 2.00 99.79

FS 12.86 18.02 9.96 1.59

UM 0.41 1.00 0.00 0.49

IND 0.42 1.00 0.00 0.50

REG 0.34 1.00 0.00 0.47

NPO 0.50 1.00 0.00 0.50

28

Table V: Effect of Governance on Economic and Financial Performance

Variables ROA t-Statistic OSS t-Statistic PY t-Statistic

c -0.31 -0.17 3.16 0.37 14.00 1.17

BS -0.56* -2.67 -1.01 -0.90 -0.39* -1.86

CEO Duality -0.73* -3.48 -0.24* -2.27 0.45 0.18

FD 0.23 1.25 0.51 0.39 0.18 0.06

AGE 0.65* 3.05 0.61* 6.05 0.06* 2.24

PROD 0.04* 2.15 0.17 0.04 0.01** 1.96

FS 0.27** 1.94 0.15* 2.01 0.26* 2.38

UM 0.30 0.14 0.10 0.90 0.86 0.36

IND 0.49* 2.02 0.40* 3.09 0.95 0.35

REG 0.31* 1.99 0.23*** 1.83 0.43* 2.12

NPO -1.03 -0.39 0.12 0.92 0.02 0.45

R-squared 0.46 0.51 0.46

Hausman test p-value 0.08 0.10 0.11

Note: The economic and financial performance measures are ROA, OSS, and PY. The t-stat

is given in the next column along with each coefficient. The * indicates significance at 1%,

** significance at 5% and *** at 10%. The Random Effect model is estimated. The Hausman

test turns out to be significant suggesting Random Effect model is to be estimated.

29

Table VI: Effect of Governance on Social Performance (Outreach)

Variables AVL t-Statistic CC t-Statistic NB t-Statistic

c 7.57 13.51 -1.13 -1.45 -4.66 -4.86

BS -0.03** -1.97 -0.05* -2.45 0.03 1.48

CEO Duality 0.01 0.07 -0.08 -0.48 -0.04 -0.23

FD 0.28* 2.01 -0.03 -0.13 -0.13 -0.59

AGE -0.10 -0.01 -0.03 -0.17 -0.05* -2.90

PROD 0.05* 1.99 0.06* 4.15 0.09 -0.11

FS 0.07* 2.19 0.92* 2.21 0.66* 12.13

UM 0.43* 3.77 -0.10 -0.61 0.07 0.39

IND -0.14 -1.14 0.03 0.17 -0.16 -0.74

REG 0.62* 3.59 0.14* 5.76 0.11* -3.73

NPO 0.25** 1.86 0.35** 1.86** 0.24 1.88**

R-squared 0.43 0.89 0.74






30

Table VII: Effect of Governance and Financial Performance on Productivity

Variables PROD t-Statistic PROD t-Statistic PROD t-Statistic

C 1.82 2.30 1.76 2.22 1.76 2.20

BS 0.02* 2.00 0.02** 1.92 0.02** 1.86

CEO Duality -0.13 -0.73 -0.15 -0.84 -0.16 -0.99

FD -0.01 -0.06 -0.01 -0.05 -0.03 -0.13

AGE 0.07* 5.10 0.07* 4.46 0.08* 5.70

FS 0.14* 3.17 0.14* 3.06 0.14* 3.20

UM -0.32* -1.99 -0.32* -1.93 -0.32* -1.96

IND 0.33*** 1.86 0.34*** 1.87 0.36* 2.01

REG 0.16 0.65 0.15 0.59 0.15 0.60

NPO 0.50* 2.17 0.49* 2.08 0.50* 2.18

ROA 0.01** 1.85

OSS 0.08* 2.41

PY 0.06 0.09

R-squared 0.46 0.48 0.49






31

Table VIII: Effect of Governance and Outreach on Productivity

Variables PROD t-Statistic PROD t-Statistic PROD t-Statistic

C 4.01* 2.95 2.89 4.84 1.48 1.61

BS 0.02** 1.86 0.04* 2.77 0.02 1.03

CEO Duality -0.16* -1.99 -0.11** -1.93 -0.15* -1.93

FD 0.06 0.28 0.06 -0.02 -0.03 -0.13

AGE 0.08* 5.69 0.06* 5.64 0.08* 5.45

FS 0.16* 3.61 -0.47* -6.12 0.16* 2.08

UM -0.19 -1.10 -0.21*** -1.84 -0.35* -2.11

IND 0.31** 1.85 0.23** 1.96 0.40* 2.24

REG 0.32** 1.86 0.94* 4.65 0.16** 1.82

NPO 0.57* 2.49 0.60* 3.53 0.55* 2.37

AVL -0.29* -2.02

CC 0.64* 8.83

NB 0.19 0.02

R-squared 0.48 0.70 0.46






32

Appendix A: Lists the MFIs which are included in this research:

Category MFP

Total

Market

Microfinance Banks Khushhali Bank

The First Microfinance Bank

Tameer Microfinance Bank

Network Microfinance Bank

Pak‐Oman Microfinance Bank

Kashf Bank

Rozgar Microfinance Bank

17.8%

11.2%

4.0%

0.2%

0.5%

0.8%

0.8%

MFI-NGO Kashf Foundation

Akhuwat

Asasah

ASA

Community Support Concern

Development Action for Mobilization and

Emancipation

Orangi Pilot Project

BRAC

Sindh Agricultural and Forestry Workers

Cooperative Organization

Centre for Women Cooperative Development

Rural Community Development Society

Sungi Development Foundation

Jinnah Welfare Society

ORIX Leasing Pakistan

14.3%

0.9%

1.4%

1.6%

0.6%

2.7%

2.7%

3.2%

1.7%

0.6%

1.1%

0.2%

0.1%

0.9%

Rural Support

Programs

National Rural Support Program

Punjab Rural Support Program

Sarhad Rural Support Program

Thardeep Rural Development Program

24.7%

4.4%

0.2%

1.7%

Total 95%

impact of corporate governance on performance of mfis

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