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Introduction

In this report analysis on governance and performance of microfinance
Institutions(MFI) in India. MFIs supply banking services to micro-
enterprises and poor families. The MFI has governance problems that
are similar to ordinary banks, but also peculiar problems of its own. For
instance, most MFIs have a dual mission of reaching poor clients and
being financial sustainable, few MFIs are regulated, and several MFIs
still depend on donor funding. Good corporate governance has been
identified as a key bottleneck to strengthen the financial performance of
MFIs and increase outreach of microfinance. This report aims to fill the
void by analyzing governance mechanisms on a wide range of
performance and risk measures using a unique data set spanning 60
companies.

Beside the owner-manager agency relationship in ordinary firms, the
firm customer relationship is important in banks. This makes it
important to use a broad set of relevant corporate governance variables
for explanation of the MFI's performance and risk. We look at such
traditional aspects as board characteristics and ownership but also bring
in the role that innovations in the MFI loan methodology play in
overcoming its repayment problems, perhaps the best known is group
lending. The microfinance organization’s ownership type may play a
role. In microfinance, both ordinary shareholder owned firms and non-
profit organizations exist. Furthermore, due to their role in the country's
financial infrastructure, and the individual MFI's access to funds, the
regulation of the MFI is important. In all, we analyze the effect on
governance and the MFI's performance.

Stakeholders, such as customers, employees and donors sit on the MFI
board. In this report a very small incidence of stakeholder board
representations, making regression and hypothesis analyses based on
secondary data. Find that there are systematic differences between the
governance of banking and manufacturing firms. This indicates that
governance structures are industry specific. Hence, to improve the
performance of MFIs there is a need to better understand the influence
of different corporate governance mechanisms in this specific industry.
This further motivates the need for this report as it claims to be the first
global study on the influence of corporate governance on MFI firm
performance and risk.

The UN Year of Microcredit in 2005 and the Nobel Peace Prize to
Mohammed Yunus and Grameen Bank in 2006 have given considerable
public recognition to microfinance as a development tool. Christen et al.
(2004) report an astonishing 500 million persons served, mostly with
savings accounts, while the Microcredit Summit in the 2006-meeting in
Halifax celebrated the milestone of 100 million borrowers reached.
Nevertheless, microfinance still reaches only a fraction of the world's
poor (Robinson, 2001; Christen et al., 2004). Hence, there is a supply
challenge in the industry (Helms, 2006; C-GAP, 2004, 2006). Our data
is a self constructed dataset with unusually high-quality information,
collected by third party rating agencies, for up to four financial years
from 148 MFIs in India.

The institutions are united in their willingness to open up their accounts
to careful scrutiny carried out by specialized rating agencies and to
accept that the reports become publicly available. The institutions thus
represent the best hopes for reaching the dual goal of reaching poor
clients and being financial sustainable. Since we want to explore
performance and risk effects from characteristics that are fixed over the
sample period, such as ownership type, we perform econometric
analyses with the random effects panel data method.

Considerable research efforts have been dedicated to microfinance.
Especially the possible impact from getting access to microfinance the
economics of group lending the building of inclusive financial sectors
as well as the development of theory has motivated researchers. Linked
to the schism debate is the study of the performance of microfinance
organizations. Here the Mixmarket and the Microbanking Bulletin
(www.mixmarket.org) have provided the industry with important
knowledge and benchmarks. Nevertheless, empirical progress on better
understanding of the corporate governance mechanisms influencing
performance is still held back by the lack of reliable cross-country data.
Thus, by introducing a unique dataset to link MFI and performance at
the individual MFI level our paper complements the existing research in
the microfinance field.


1.2. Governance and performance in MFI

Governance is about achieving corporate goals. For the MFI, multiple
goals exist. The fundamental goal is to contribute to development. This
involves reaching more clients and poorer population strata, the so called
main outreach 'frontier' of microfinance (Helms, 2006; Johnson et al.,
2006). A second goal is to do this in a way that achieves financial
sustainability, preferably independence from donors. While Rhyne
(1998) considers these two main goal areas to be a 'win-win' situation,
claiming that those MFI institutions that follow the principles of good
banking will also be those that alleviate the most poverty, Woller et al.
(1999); Morduch (2000) think that the proposition is far more
complicated. In this paper, we are able to throw light on the controversy
by using both financial and outreach measures. In addition, we also look
at the governance impact upon risk.

In this paper, we differentiate between financial performance and
outreach. However, in the microfinance literature the lines are not as
clear cut. For instance, Hartarska (2005) uses dependent variables based
on outreach and sustainability. Outreach is measured in breadth and
depth. Breadth of outreach is the logarithm of active borrowers, depth is
the average loan size on GDP per capita. Sustainability is ROA and
operational self-sufficiency. We maintain the division between financial
performance and outreach. The financial performance variables include
ROA, but also variables that go behind ROA, including operational
costs and operational self- sufficiency. These are major underlying
variables influencing ROA. In addition we also include debt/equity ratio
(DE) since good corporate governance should show an impact upon this
variable.
Table 1 gives an overview of dependent variable definitions.



Before discussing specific mechanisms for achieving goals, we need to
consider the special nature of banks. As a provider of banking services,
the MFI is subject to adverse selection and moral hazard from credit
clients with little or no collateral. Adverse selection arises since the MFI
does not have enough information to differentiate between good and bad
risks. Moral hazard is the problem that the borrower will not exert
necessary efforts to repay the loan, when the bank is unable to monitor
the effort. What sets the new microfinance initiatives apart is that of
finding new ways to deal with these problems, and thereby, to establish
workable business models.

I have differentiated between financial performance and outreach in the
comments to board characteristics. This seems unnecessary, as a board
that is performing well on the financial side must be expected to do well
on its business side, or outreach, too. Likewise, a better board should
show up in lower values in operational cost regression as well as higher
values on debt/equity since better boards should be able to attract more
debt. For risk levels the analysis is not straightforward. Lower risk
should reduce losses and improve ROA. However, there can sometimes
be a trade-off between slight increases in risk levels and lower
operational costs. A good board should strike the balance between risk
levels and operational costs to maximise its ROA. Microfinance has
produced innovations in lending that may overcome the adverse
selection and moral hazard problems mentioned above. This happens
because group lending leads to assortative grouping, that is, that the best
credit risk groups band together naturally, out of local knowledge of
trustworthiness. Borrowers have a joint liability for the individual loans.
This creates social capital collateral, which the individual borrower will
seek to protect. Thus, the fear of losing this collateral leads to better
repayment rates.
Microfinance is the provision of financial and non-financial services to
the poor who are excluded from financial /credit markets because they
are considered unbankable. Indeed, microfinance institutions have
evolved primarily as a consequence of the efforts individuals and
assistance agencies have committed to the idea of ensuring that the poor
people have access to some form of credit. The majority of MFIs claim
having a dual mission of reaching poor borrowers (outreach), and
profitability,   being    financially    sustainable    (sustainability).

While the social goals of reaching the poorest and poverty alleviation are
valid, financial sustainability has emerged as one of the core
management and governance issues. The shrinking resources base for
donor funds to support the increasing demand for grants and soft loans
implies that MFIs will eventually have to support themselves. However,
their sustainability will focus on governance structures within the
industry. Indeed, in the last decade corporate governance principles have
imposed themselves as the basic rules for any well-run company to
follow. The trend has however transcended from traditional business
companies but now is part of the globalization process often seen as a
tool for standardizing the controlling vision for any major organization
in the world. The drive towards Governance has been propelled by a
number of factors, particularly the collapses of some of the major
players in the Industry, the influx of private Equity and fall in donor
funding.


Governance is about achieving corporate goals. The fundamental
purpose of MFIs is to contribute to a country development. This
involves reaching out to more clients, especially the poor. Not least but
now growing in importance, especially among donors, is the requirement
that        MFIs         achieve         financial         sustainability.

Microfinance practitioners assert that good governance is the key to a
successful MFI. In spite of these observations, only few studies have
focused on governance and the examination of the linkage of various
governance mechanisms and performance (McGuire 1999). It seems
relevant to examine closely the role of various governance mechanisms
since MFIs managers control significant resources. No more studies
attempt to shed light on the link between governance and performance,
especially in the Indian countries, although it is a very active zone with a
microfinance industry quite diverse (NGO (2), NBFI (3), Bank) where
actors should simultaneously pursue the most effective way of realizing
their social objective while achieving superior levels of profitability.

While exploiting a recently conducted survey by the author in order to
study the efficiency of MFIs in India, the annual financial reports of the
microfinance institutions, and other relevant information collected from
Microfinance Information Exchange (MIX), this report aims to
investigate the link between governance and MFIs' performance in terms
of outreach and sustainability since governance guides an institution in
fulfilling its corporate mission and protects the institutions assets over
time. The empirical model explores the joint and individual effect of
management compensation, board diversity, and external governance
mechanisms on both MFI sustainability and the depth and breath of
outreach while controlling for individual characteristics and, as well as
country's specific factors. The results show that performance-based
compensation does not improve performance. MFIs with larger boards
seem to do better. More independent boards are more effective,
however. Board diversity (Higher proportion of women) seems to
ameliorate the outreach. External governance mechanisms especially
auditing and regulation improve the financial sustainability.

This report analyzes the relationship between firm performance and
corporate governance in Microfinance Institutions (MFIs). It studies the
effects of ownership type, competition and regulation using a global data
set on MFIs, collected from third-party rating agencies.
LITERATURE REVIEW
Governance in microfinance has been recognized to be an important
issue. However, the biggest problem to microfinance practitioners has
been balancing the dual mission of outreach and sustainability. The
changing of microfinance environment has shown a move towards
sustainability ultimately leading to governance issues as donor funds
shrink and equity inflows increase in the microfinance sector.
Microfinance institutions have therefore embraced boards and adopted
principles of corporate governance to ensure their survival.

Investigating the link between good governance and the performance of
MFIs in terms of outreach and sustainability is crucial since governance
guides an institution in fulfilling its corporate mission and protects the
institution assets over the time. However, there is a limited amount of
academic studies dealing with this subject, partly due to the lack of data.

While using three surveys of rated and unrated East European MFIs
from three random samples in the period 1998 to 2002, Hartarska
(2005), investigates the relation between governance mechanisms and
financial performance. Financial performance and outreach constitute
dependant variable dimensions and governance mechanisms include
board characteristics, managerial compensation, and external
governance mechanisms such as rating, financial statements audited, and
supervision. The author finds that performance-based compensation of
managers is not associated with better performing MFIs; lower wages
suggested for mission-driven organization worsen outreach. She also
identifies that a more independent board has the better ROA, but the
board of employee directors gives lower financial performance and
lower outreach. Finally, the author concludes that external governance
mechanism seems to have a limited role in the study region.

In a recent study, Mersland and Strom (2007), use a self-constructed
global data set on MFIs spanning 57 countries collected from third-party
rating agencies. The authors study the effect of board characteristics,
ownership type, competition and regulations on the MFIs outreach to
poor clients and its financial performance. They found that split roles of
CEO Chairman, a female CEO, and competition are an important
explanation. Moreover, the authors found that the larger board size
decreased the average loan size, while individual guaranteed loan
increased it. Finally, they conclude that there is no difference between
non-profit organizations and shareholder firms in financial performance
and                                                             outreach.

The third study was conducted by Cull et al. (2007) looking at MFIs
financial performance and outreach as well, with a focus on lending
methodology (5), controlling for capital and labour cost as well as
institutional features. While using the data from 124 rated MFIs, the
authors found that MFIs which focus on providing loans to individuals
perform better in terms of profitability. Yet, the fraction of poor
borrowers and female borrowers in the loan portfolio of these MFIs is
lower than for MFIs which focus on lending to groups. The study
suggests also that individual-based MFIs, especially if they grow larger,
focus increasingly on wealthier clients, a phenomenon termed as
"mission drift". This mission drift does not occur as strongly for the
group-based MFIs. However, no governance variables, such as board
characteristics or ownership type are taken into consideration.

The limited academic investigation into the link between governance
mechanisms and performance of MFIs in terms of outreach and
sustainability, and the fact that other governance mechanisms such as the
proportion of women in the board remain unexplored justify the
importance of a similar study in the Euro-Mediterranean zone,
characterized by a very active and quite diverse microfinance industry,
that                complete                  former             studies.
4.Conceptual        framework         and        working        hypothesis

While focusing on the microfinance field, the governance can be defined
as the process of guiding an institution to achieve its objectives while
protecting its assets. It refers to the mechanisms through which donors,
equity, investors, and other providers of funds ensure themselves that
their funds will be used according to the intended purposes. The
presence of these control mechanisms is crucial either to align the
interests of managers and providers of funds since they may have
diverting preferences and objectives, or to monitor the performance of
managers to ensure that they use their delegated power to generate the
highest possible returns for the providers of funds. This notion comes
from the agency perspective. The explanatory model of the structures of
financing and shareholding is founded on the assumption of
asymmetry of information and conflicts of interests between managers
and providers of funds, agency relationship is a contract under which
"one or more persons (principal) engage another person (agent) to
perform some service on their behalf, which involves delegating some
decision-making authority to the agent". In this case the relation of
agency will relate the principal (owner) and his agent (manager), this
last being engaged to serve the interests of the first. From these relations
the concept of agency costs emanates, costs which result from the
potentially opportunist character of the actors (moral hazard) and
information asymmetry between the contracting parties (adverse
selection). These agency costs represent the loss in value compared to an
ideal situation where there is no information asymmetry and conflict of
interests. According to the theorist of agency, an organization is
considered efficient if it minimizes the agency costs. This purpose can
be intended through an effective governance mechanism.
4.1.            External              governance               mechanisms

The external governance mechanism can be implemented as a result of
the failure or the weakness of internal governance mechanisms. In the
microfinance industry donors and creditors are increasingly relying on
information from audited financial statement and rating agencies. These
external governance mechanisms are an important mechanism that
provides depositors, creditors and shareholders with credible assurances
that they will refrain from fraudulent activities. In other words, it
reduces     informational    asymmetries     between     the    different
stakeholders and                         the                        firm.

Audited financial statements are an important tool for the assessment of
MFIs by regulators and capital markets. They form an important part of
the effective corporate governance. The auditor's role is to provide a
disinterested and objective view whether the financial statements on the
MFI are in line with generally accepted accounting standards. It is a
means to ensure potential investors and donors that MFI complies with
the accounting practices and managers do not misrepresent financial
information.

 In the absence of developed equity and debt market, donors and
investors rely on independent evaluation of MFIs performance. A MFIs
rating reflects a rating agency's opinion of entity's overall
creditworthiness and its capacity to satisfy its financial obligations. The
raters evaluate objectively and independently the corporate governance
in MFI and rank it on a relative rating scale that would facilitate
comparison. Unlike typical rating agencies that rate the riskiness of
issued debt, microfinance rating agencies rate the overall performance of
the     MFI     in     terms    of     outreach      and     sustainability.
5. Data and methodological issues

Data for this study are obtained from MIX (Microfinance Information
Exchange). The performance variables and some governance variables
are also obtained from the annual financial reports of the microfinance
institutions collected from Microfinance Information Exchange (MIX), a
nongovernmental organization whose object is to promote the exchange
of information on the microfinance sector in India. All data are
secondary collected from the MIX and based on these data. There are
mainly two variable; dependent and independent. Dependent variables
are OSS (Operational self-sufficiency), OER (Operating cost) and ROA
(Return on asset).Where independent variable are SIZE, LOAN,
DEPOSITE RATIO, CAPITAL, NO.OF ACTIVE BORROWER,
AVG.LOAN BAL.BORROWER, WOMEN BORROWER etc..

There are 60 MFIs out of 148 includes NGOs, NBFIs and BANKs. This
is analyzed through hypothesis and regression models.

The descriptive statistics for this study are shown in Table 3. The
performances of Microfinance Institutions are widely spread. On
average, the MFIs recorded a return on assets of 5,935%. While the
minimum was-7.58%, the maximum performance was 33% indicating a
widely spread performance. Similarly, the studied MFIs have on average
an Operational Self-Sufficiency of 85.41% with respectively a minimum
and a maximum of 20.345% and 143.33%. With regard to the DEPTH,
the average values of relatively weak 220 indicate that the poor
borrowers            are           very           well          served.

On average, the MFIs managers have 8.4 years of experience and 82.4%
of these managers are receiving a Fixed-wage. On average, 5 persons
serve on the board of an MFI and a standard deviation of 3,32 coupled
with a maximum board size of 16 members and a minimum board size
of 4 members suggest that these boards are widely dispersed. The
unaffiliated directors represent on average 45% of the board members.
The descriptive statistics also indicate that on average 39% of all boards
are             made              up             of              women.

In our sample, around half of the MFIs have an internal auditor reporting
directly to the board. Moreover, 81% of the MFIs studied have their
financial statement audited and 37% of the MFIs forming the sample are
rated. The result also shows that 42% of the institutions are regulated,
and the individual lending technology constitutes 73% of the cases. The
average age standing for the MFI is about 3 years. The NGOs represent
59% of our sample, however, the NBFI and Bank represent respectively
17% and 9% of the sample. Finally, the average inflation rate in all the
countries      subject    to     the    study     is     about      16%.
FINDINGS

As shown in Table 4 dealing with the estimation of the impact on
sustainability and outreach, our first hypothesis stipulating that the
remuneration system (performance-based compensation or fixed
salary) is confirmed. The coefficient of Fixed-wage is not
significant in any of the specification.

Managerial qualifications as shown by the positive and significant
sign of Experience in the OSS, ROA and OER regressions as well
as the enviable negative and significant coefficient in the depth
indicate that the acquired experience allows MFIs managers to
reach poor borrowers and produce better sustainability.

Board size is rather positively related to ROA, OSS, and OER
suggesting to the contrary that MFIs with larger boards seem to do
better. The results reduplicate our second hypothesis and confirm
studies that support the view that larger boards are better for
corporate performance since members have a range of expertise to
help to make better decision, and are harder for powerful CEO to
dominate. An important result of this study is the support MFIs
with a higher proportion of unaffiliated directors had better
sustainability (ROA & OSS) and also reach poor borrowers.

The results of the study show that board diversity (higher
dproportion of women) improves social performance. This is
consistent with recent thinking and discussions which point to the
fact that governance reforms have been geared towards the
importance of gender diversity, especially in the boardroom, and
that the issue of gender diversity is central and could enhance
board effectiveness by tapping broader talent pools for their
directors resulting in the more diverse board having better relations
with other stakeholders such as customers, suppliers, and
employees which inevitably translate into performance and firm
value.

Although microfinance rating agencies rate the overall
performance of the MFIs in terms of outreach and sustainability,
the empirical results show that this variable does not have any
significant influence on MFIs performance. In addition, the study
reveals that MFIs having their financial statement audited achieve
better sustainability. These MFIs comply with accounting practices
and are able to reach higher levels of financial performance.

Regulated MFIs do not reach more borrowers but according to the
results in Table 4, have significant and positive ROA & OSS.
Although this result is diverse from past studies which did not find
any relation between these two dimensions, or found a weak
relation, it brings the evidence that regulation may assure
customers that they are treated fairly and this could lead to more
business and better financial performance.

Results indicate that the lending technology improves considerably
the financial performance of the MFIs. This result can be attributed
to the fact that the cost argument is more important than the
repayment argument for group lending or village bank. The
supposed efficiency in group lending does not hold in India. From
another point of view, it can be justified by the new tendency
toward the individual micro lending, since this methodology
becomes highly recommended.
In conformity with the theory, the age of the firm as proxy for reputation
impacts positively on performance likewise the size of the MFI.
Expectedly, the size of MFI has a significant positive impact on
performance. This may be due to the fact that a large firm has the ability
to accommodate risk and to enhance productivity through diversification
of products and services. The study shows that NGOs are more efficient
than NBFI and show better social performance by reaching the poor. It
becomes clear that NGOs are more consistent with their social mission
than with their financial performance. The results reveal also the
significance of controlling for cross country differences. The level of
inflation affects negatively the sustainability of MFIs. Finally, the study
suggests that the economy of big size affects outreach.
Conclusion and Recommendation

This report tests empirically the relationship between governance MFIs
performance in terms of outreach and sustainability. While using
secondary data from MIX as well as from the annual financial reports
and from the Mix Market, the study examines the impact of management
remuneration, board independence and diversity, internal auditor
reporting directly to the board, external governance mechanisms of
control, and MFIs in India. Results indicate that not all known
governance mechanisms affect performance and in addition, different
factors have the differential effect on outreach and sustainability.

The study shows that explicit and implicit incentives schemes such as
compensation, perks, etc. become less powerful and less able to motivate
managers. Results also show that larger boards are better for MFIs
performance since members have a range of expertise to help to make
better decision and are harder for powerful CEO to dominate. Moreover,
the study reveals that microfinance boards with larger proportions of
unaffiliated directors achieve better results. Thus, independence of the
microfinance          board         should         be        encouraged.

The fundamental result of this study is that board diversity (higher
proportion of women) enhances performance and again the more women
there are on the board, the better the performance. Thus board diversity
is paramount for enhanced performance of microfinance institution.



Having financial statement audited, and being rated by international
agencies is synonym to a better financial performance. It seems that
external governance mechanisms help MFIs to reach their financial
performance. This study allows us to distinguish other factors leading
also to a better sustainability such as Regulation and the use of
individual lending methodology. However, the MFIs type (NGO) seems
to be more consistent with their social mission than with their financial
performance. The microfinance institutions characteristics such as age
and size affect positively the performance; nevertheless, the level of
inflation has a negative impact on the sustainability of MFIs.

Although this study brings some clarifications on the link between the
governance mechanisms and performance of microfinance in India,
several governance mechanisms remain unexplored such as CEO
duality, graduate board members, international directors, ownership
structure. Thus, it seems relevant to conduct more studies in order to
learn more about the impact of these governance mechanisms on
outreach and sustainability of MFIs not only in the India.
Bibiliography

 MFIs in india | Microfinance india
 Governance and performance of microfinance institutions in Mediterranean countries. - Free
   Online Library
 Books, journals, articles.
 Research papers, reports of researchers etc……..
 Indian Association for Savings and Credit | MFIs in India
 BSS Microfinance Pvt. Ltd. | MFIs in India
 ADARSHA | MFIs in India
 Anisha Microfin Association | MFIs in India
 Camel Mahila Macts Limited | MFIs in India
References:

(1) Microfinance Institutions
(2) Non-Governmental Organisation
(3) Non-Financial Bank Institution
(4) This figure quotes the most famous MFIs in the Mediterranean
region.

(5) Lending methodology refers to the way loans are given. Individual
loans, group loans, and village banks (which are bigger groups that often
have wider objectives than to serve as a guarantee mechanism only) are
the categories used.

(6) Jensen, M. C.; Meckling, W. H. 1976. Theory of the firm:
managerial behaviour, agency costs, and ownership structure, Journal of
Financial Economics 3: 305-350.

(7) Informations on the MIX are available on the Web site
www.themix.org. The data bases on the MFIs are accessible by the mix-
market, an online data base accessible from the MIX site. Mix Market,
known formerly under the name of "Virtual Market of Microfinance"
was initiated jointly by the UNCTAD and the Government of
Luxembourg. In 2001, it was taken in charge by the Consultative Group
to Assist the Poor (CGAP), a consortium of backers which works for the
development of Microfinance in the world.

(8) Although the properties of the Hausman test for endogeneity are not
well understood in small samples, this test does not indicate that the
individual governance mechanisms are endogenous (Wooldridge 2002).
(9) The higher the value of DEPTH, the less poor clients are being
served. Therefore from a poverty-alleviation perspective, a smaller value
of this variable is preferred.


Table 1. Definitions of dependent variables used in analyses

Variable                       Explanation

Social Performance:
Outreach

NAB                   Logarithm of the number of active borrowers

DEPTH                 The average loan size on GDP per capita

Financial Performance:
Sustainability

ROA                   Return On Assets

OSS                 Operational Self-Sufficiency


Table 2. Definitions of independent variables used in analyses

Variable                    Explanation

Loan             A loan outstanding per total assets.

Women            The proportion of the women on the board
Audited          A dummy that equals one if the financial statement
                 reports directly to the board
Rated                   A dummy that equals one if the MFI is four rated and
five                    rated is equals zero zero

Regulation     A dummy being one if the MFI is regulated by
                banking authorities
MFI age        Number of years since the commencement
MFI size       Logarithm of the total assets of the MFI
NGO            The MFI is an NGO and dummy that equals one
NBFI           The MFI is an non-financial bank institution and
dummy that     equals one
Bank           The MFI is an bank and dummy that equals three
Economy size Logarithm of total GDP (Gross Domestic Product of
                the country) for the year t
Borrower/staff The active borrower divided by staff members
Deposite ratio Total deposite divided by total asset
Capital        Tptal equity divided by total asset




    (1)      ROA:
                                               b
                                        ANOVA

Model                  Sum of Squares     df           Mean Square    F       Sig.
                                                                                       a
1         Regression             .205              6           .034   2.292     .036

          Residual              3.445          231             .015

          Total                 3.650          237

a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, LOAN, PORTFOLIOAT30DAYS,
CAPITAL, DEPOSITERATIO

b. Dependent Variable: ROA
Suggestion= here f significant level is less than 5%, so H0 is accepted.
a
                                                                     Coefficients

                                                                     Standardized
                              Unstandardized Coefficients            Coefficients                                       95.0% Confidence Interval for B

Model                              B           Std. Error                  Beta              t               Sig.       Lower Bound        Upper Bound

1       (Constant)                      .005             .032                                    .142            .888              -.058            .067

        CAPITAL                        -.100             .038                     -.176      -2.642              .009              -.174           -.025

        PORTFOLIOAT3                   -.004             .056                     -.005          -.070           .945              -.114            .106
        0DAYS

        LOAN                           -.007             .008                     -.057          -.882           .379              -.024            .009

        SIZE                            .032             .032                     .068       1.015               .311              -.031            .095

        DEPOSITERATIO                  -.005             .065                     -.005          -.072           .942              -.133            .123

        NO.OFACTIVEB                    .001             .001                     .122       1.886               .060              .000             .002
        ORROWER

a. Dependent Variable: ROA

          Y=a+bx
          Y=.005-0.1x1-0.004x2-0.007x3+0.032x4-.005x5+0.001x6


          X1=capital
          X2=portfolio
          X3=days
          X4=loan
          X4=size
          X5=deposit
          X6=no. of nab


                (2)      OER:
                                                                       b
                                                          ANOVA

           Model                       Sum of Squares           df             Mean Square               F          Sig.
                                                                                                                               a
           1          Regression                  .839                     6              .140           2.965          .008

                      Residual                 10.937                 232                 .047

                      Total                    11.776                 238
a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, PORTFOLIOAT30DAYS, LOAN,
               CAPITAL, DEPOSITERATIO

               b. Dependent Variable: OER



               Suggestion= here f significant level is more than 5%, so H1 (alternate
               hypothesis) is rejected.




                                                                                                                         a
                                                                                                          Coefficients

                                                                                Standardized
                                     Unstandardized Coefficients                Coefficients                                 95.0% Confidence Interval for B

Model                                       B              Std. Error              Beta           t           Sig.           Lower Bound       Upper Bound

1       (Constant)                              .145               .058                           2.515           .013                 .031              .258

        CAPITAL                                 .236               .067                   .231    3.503           .001                 .103              .368

        PORTFOLIOAT30DAYS                       -.082              .099                   -.053       -.828       .409                 -.277             .113

        LOAN                                    -.022              .015                   -.094   -1.461          .145                 -.051             .008

        SIZE                                    -.009              .058                   -.011       -.161       .873                 -.123             .105

        DEPOSITERATIO                           -.021              .115                   -.012       -.185       .854                 -.249             .206

        NO.OFACTIVEBORROWER                     .000               .001                   -.015       -.231       .818                 -.002             .002

a. Dependent Variable: OER



               Y=a+bX
               Y=0.145+0.236X1-0.082X2-0.022X3-0.009X4-0.021X5+0.00X6


               (3) OSS:
                                                                        b
                                                               ANOVA

               Model                  Sum of Squares              df            Mean Square       F            Sig.
                                                                                                                         a
               1       Regression                       .678                6              .113        .964       .451

                       Residual                   27.201                232                .117

                       Total                      27.879                238
a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, PORTFOLIOAT30DAYS, LOAN,
               CAPITAL, DEPOSITERATIO

               b. Dependent Variable: OSS



               Suggestion= here f significant level is less than 5%, so H0 is accepted.




                                                                                                                a
                                                                                                 Coefficients

                                                                       Standardized
                                      Unstandardized Coefficients      Coefficients                                 95.0% Confidence Interval for B

Model                                       B           Std. Error        Beta           t           Sig.           Lower Bound       Upper Bound

1       (Constant)                              1.264           .091                     13.918          .000                1.085             1.443

        CAPITAL                                 -.118           .106             -.075   -1.108          .269                 -.326             .091

        PORTFOLIOAT30DAYS                       -.129           .156             -.055       -.826       .409                 -.437             .179

        LOAN                                     .029           .023             .081     1.226          .221                 -.017             .074

        SIZE                                    -.073           .091             -.054       -.796       .427                 -.253             .107

        DEPOSITERATIO                           -.198           .182             -.075   -1.090          .277                 -.557             .160

        NO.OFACTIVEBORROWER                     -.001           .002             -.055       -.830       .407                 -.005             .002

a. Dependent Variable: OSS




               Y=a+bX
               Y=1.264-0.118X1-0.129X2+0.029X3-0.073X4-0.198X5-0.001X6

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  • 1. Introduction In this report analysis on governance and performance of microfinance Institutions(MFI) in India. MFIs supply banking services to micro- enterprises and poor families. The MFI has governance problems that are similar to ordinary banks, but also peculiar problems of its own. For instance, most MFIs have a dual mission of reaching poor clients and being financial sustainable, few MFIs are regulated, and several MFIs still depend on donor funding. Good corporate governance has been identified as a key bottleneck to strengthen the financial performance of MFIs and increase outreach of microfinance. This report aims to fill the void by analyzing governance mechanisms on a wide range of performance and risk measures using a unique data set spanning 60 companies. Beside the owner-manager agency relationship in ordinary firms, the firm customer relationship is important in banks. This makes it important to use a broad set of relevant corporate governance variables for explanation of the MFI's performance and risk. We look at such traditional aspects as board characteristics and ownership but also bring in the role that innovations in the MFI loan methodology play in overcoming its repayment problems, perhaps the best known is group lending. The microfinance organization’s ownership type may play a role. In microfinance, both ordinary shareholder owned firms and non- profit organizations exist. Furthermore, due to their role in the country's financial infrastructure, and the individual MFI's access to funds, the regulation of the MFI is important. In all, we analyze the effect on governance and the MFI's performance. Stakeholders, such as customers, employees and donors sit on the MFI board. In this report a very small incidence of stakeholder board representations, making regression and hypothesis analyses based on secondary data. Find that there are systematic differences between the governance of banking and manufacturing firms. This indicates that
  • 2. governance structures are industry specific. Hence, to improve the performance of MFIs there is a need to better understand the influence of different corporate governance mechanisms in this specific industry. This further motivates the need for this report as it claims to be the first global study on the influence of corporate governance on MFI firm performance and risk. The UN Year of Microcredit in 2005 and the Nobel Peace Prize to Mohammed Yunus and Grameen Bank in 2006 have given considerable public recognition to microfinance as a development tool. Christen et al. (2004) report an astonishing 500 million persons served, mostly with savings accounts, while the Microcredit Summit in the 2006-meeting in Halifax celebrated the milestone of 100 million borrowers reached. Nevertheless, microfinance still reaches only a fraction of the world's poor (Robinson, 2001; Christen et al., 2004). Hence, there is a supply challenge in the industry (Helms, 2006; C-GAP, 2004, 2006). Our data is a self constructed dataset with unusually high-quality information, collected by third party rating agencies, for up to four financial years from 148 MFIs in India. The institutions are united in their willingness to open up their accounts to careful scrutiny carried out by specialized rating agencies and to accept that the reports become publicly available. The institutions thus represent the best hopes for reaching the dual goal of reaching poor clients and being financial sustainable. Since we want to explore performance and risk effects from characteristics that are fixed over the sample period, such as ownership type, we perform econometric analyses with the random effects panel data method. Considerable research efforts have been dedicated to microfinance. Especially the possible impact from getting access to microfinance the economics of group lending the building of inclusive financial sectors as well as the development of theory has motivated researchers. Linked to the schism debate is the study of the performance of microfinance organizations. Here the Mixmarket and the Microbanking Bulletin
  • 3. (www.mixmarket.org) have provided the industry with important knowledge and benchmarks. Nevertheless, empirical progress on better understanding of the corporate governance mechanisms influencing performance is still held back by the lack of reliable cross-country data. Thus, by introducing a unique dataset to link MFI and performance at the individual MFI level our paper complements the existing research in the microfinance field. 1.2. Governance and performance in MFI Governance is about achieving corporate goals. For the MFI, multiple goals exist. The fundamental goal is to contribute to development. This involves reaching more clients and poorer population strata, the so called main outreach 'frontier' of microfinance (Helms, 2006; Johnson et al., 2006). A second goal is to do this in a way that achieves financial sustainability, preferably independence from donors. While Rhyne (1998) considers these two main goal areas to be a 'win-win' situation, claiming that those MFI institutions that follow the principles of good banking will also be those that alleviate the most poverty, Woller et al. (1999); Morduch (2000) think that the proposition is far more complicated. In this paper, we are able to throw light on the controversy by using both financial and outreach measures. In addition, we also look at the governance impact upon risk. In this paper, we differentiate between financial performance and outreach. However, in the microfinance literature the lines are not as clear cut. For instance, Hartarska (2005) uses dependent variables based on outreach and sustainability. Outreach is measured in breadth and depth. Breadth of outreach is the logarithm of active borrowers, depth is the average loan size on GDP per capita. Sustainability is ROA and operational self-sufficiency. We maintain the division between financial performance and outreach. The financial performance variables include ROA, but also variables that go behind ROA, including operational
  • 4. costs and operational self- sufficiency. These are major underlying variables influencing ROA. In addition we also include debt/equity ratio (DE) since good corporate governance should show an impact upon this variable.
  • 5. Table 1 gives an overview of dependent variable definitions. Before discussing specific mechanisms for achieving goals, we need to consider the special nature of banks. As a provider of banking services, the MFI is subject to adverse selection and moral hazard from credit clients with little or no collateral. Adverse selection arises since the MFI does not have enough information to differentiate between good and bad risks. Moral hazard is the problem that the borrower will not exert necessary efforts to repay the loan, when the bank is unable to monitor the effort. What sets the new microfinance initiatives apart is that of finding new ways to deal with these problems, and thereby, to establish workable business models. I have differentiated between financial performance and outreach in the comments to board characteristics. This seems unnecessary, as a board that is performing well on the financial side must be expected to do well on its business side, or outreach, too. Likewise, a better board should show up in lower values in operational cost regression as well as higher values on debt/equity since better boards should be able to attract more debt. For risk levels the analysis is not straightforward. Lower risk should reduce losses and improve ROA. However, there can sometimes be a trade-off between slight increases in risk levels and lower operational costs. A good board should strike the balance between risk levels and operational costs to maximise its ROA. Microfinance has produced innovations in lending that may overcome the adverse selection and moral hazard problems mentioned above. This happens because group lending leads to assortative grouping, that is, that the best credit risk groups band together naturally, out of local knowledge of trustworthiness. Borrowers have a joint liability for the individual loans. This creates social capital collateral, which the individual borrower will seek to protect. Thus, the fear of losing this collateral leads to better repayment rates.
  • 6. Microfinance is the provision of financial and non-financial services to the poor who are excluded from financial /credit markets because they are considered unbankable. Indeed, microfinance institutions have evolved primarily as a consequence of the efforts individuals and assistance agencies have committed to the idea of ensuring that the poor people have access to some form of credit. The majority of MFIs claim having a dual mission of reaching poor borrowers (outreach), and profitability, being financially sustainable (sustainability). While the social goals of reaching the poorest and poverty alleviation are valid, financial sustainability has emerged as one of the core management and governance issues. The shrinking resources base for donor funds to support the increasing demand for grants and soft loans implies that MFIs will eventually have to support themselves. However, their sustainability will focus on governance structures within the industry. Indeed, in the last decade corporate governance principles have imposed themselves as the basic rules for any well-run company to follow. The trend has however transcended from traditional business companies but now is part of the globalization process often seen as a tool for standardizing the controlling vision for any major organization in the world. The drive towards Governance has been propelled by a number of factors, particularly the collapses of some of the major players in the Industry, the influx of private Equity and fall in donor funding. Governance is about achieving corporate goals. The fundamental purpose of MFIs is to contribute to a country development. This involves reaching out to more clients, especially the poor. Not least but now growing in importance, especially among donors, is the requirement that MFIs achieve financial sustainability. Microfinance practitioners assert that good governance is the key to a successful MFI. In spite of these observations, only few studies have
  • 7. focused on governance and the examination of the linkage of various governance mechanisms and performance (McGuire 1999). It seems relevant to examine closely the role of various governance mechanisms since MFIs managers control significant resources. No more studies attempt to shed light on the link between governance and performance, especially in the Indian countries, although it is a very active zone with a microfinance industry quite diverse (NGO (2), NBFI (3), Bank) where actors should simultaneously pursue the most effective way of realizing their social objective while achieving superior levels of profitability. While exploiting a recently conducted survey by the author in order to study the efficiency of MFIs in India, the annual financial reports of the microfinance institutions, and other relevant information collected from Microfinance Information Exchange (MIX), this report aims to investigate the link between governance and MFIs' performance in terms of outreach and sustainability since governance guides an institution in fulfilling its corporate mission and protects the institutions assets over time. The empirical model explores the joint and individual effect of management compensation, board diversity, and external governance mechanisms on both MFI sustainability and the depth and breath of outreach while controlling for individual characteristics and, as well as country's specific factors. The results show that performance-based compensation does not improve performance. MFIs with larger boards seem to do better. More independent boards are more effective, however. Board diversity (Higher proportion of women) seems to ameliorate the outreach. External governance mechanisms especially auditing and regulation improve the financial sustainability. This report analyzes the relationship between firm performance and corporate governance in Microfinance Institutions (MFIs). It studies the effects of ownership type, competition and regulation using a global data set on MFIs, collected from third-party rating agencies.
  • 8. LITERATURE REVIEW Governance in microfinance has been recognized to be an important issue. However, the biggest problem to microfinance practitioners has been balancing the dual mission of outreach and sustainability. The changing of microfinance environment has shown a move towards sustainability ultimately leading to governance issues as donor funds shrink and equity inflows increase in the microfinance sector. Microfinance institutions have therefore embraced boards and adopted principles of corporate governance to ensure their survival. Investigating the link between good governance and the performance of MFIs in terms of outreach and sustainability is crucial since governance guides an institution in fulfilling its corporate mission and protects the institution assets over the time. However, there is a limited amount of academic studies dealing with this subject, partly due to the lack of data. While using three surveys of rated and unrated East European MFIs from three random samples in the period 1998 to 2002, Hartarska (2005), investigates the relation between governance mechanisms and financial performance. Financial performance and outreach constitute dependant variable dimensions and governance mechanisms include board characteristics, managerial compensation, and external governance mechanisms such as rating, financial statements audited, and supervision. The author finds that performance-based compensation of managers is not associated with better performing MFIs; lower wages suggested for mission-driven organization worsen outreach. She also identifies that a more independent board has the better ROA, but the board of employee directors gives lower financial performance and lower outreach. Finally, the author concludes that external governance mechanism seems to have a limited role in the study region. In a recent study, Mersland and Strom (2007), use a self-constructed global data set on MFIs spanning 57 countries collected from third-party rating agencies. The authors study the effect of board characteristics,
  • 9. ownership type, competition and regulations on the MFIs outreach to poor clients and its financial performance. They found that split roles of CEO Chairman, a female CEO, and competition are an important explanation. Moreover, the authors found that the larger board size decreased the average loan size, while individual guaranteed loan increased it. Finally, they conclude that there is no difference between non-profit organizations and shareholder firms in financial performance and outreach. The third study was conducted by Cull et al. (2007) looking at MFIs financial performance and outreach as well, with a focus on lending methodology (5), controlling for capital and labour cost as well as institutional features. While using the data from 124 rated MFIs, the authors found that MFIs which focus on providing loans to individuals perform better in terms of profitability. Yet, the fraction of poor borrowers and female borrowers in the loan portfolio of these MFIs is lower than for MFIs which focus on lending to groups. The study suggests also that individual-based MFIs, especially if they grow larger, focus increasingly on wealthier clients, a phenomenon termed as "mission drift". This mission drift does not occur as strongly for the group-based MFIs. However, no governance variables, such as board characteristics or ownership type are taken into consideration. The limited academic investigation into the link between governance mechanisms and performance of MFIs in terms of outreach and sustainability, and the fact that other governance mechanisms such as the proportion of women in the board remain unexplored justify the importance of a similar study in the Euro-Mediterranean zone, characterized by a very active and quite diverse microfinance industry, that complete former studies.
  • 10. 4.Conceptual framework and working hypothesis While focusing on the microfinance field, the governance can be defined as the process of guiding an institution to achieve its objectives while protecting its assets. It refers to the mechanisms through which donors, equity, investors, and other providers of funds ensure themselves that their funds will be used according to the intended purposes. The presence of these control mechanisms is crucial either to align the interests of managers and providers of funds since they may have diverting preferences and objectives, or to monitor the performance of managers to ensure that they use their delegated power to generate the highest possible returns for the providers of funds. This notion comes from the agency perspective. The explanatory model of the structures of financing and shareholding is founded on the assumption of asymmetry of information and conflicts of interests between managers and providers of funds, agency relationship is a contract under which "one or more persons (principal) engage another person (agent) to perform some service on their behalf, which involves delegating some decision-making authority to the agent". In this case the relation of agency will relate the principal (owner) and his agent (manager), this last being engaged to serve the interests of the first. From these relations the concept of agency costs emanates, costs which result from the potentially opportunist character of the actors (moral hazard) and information asymmetry between the contracting parties (adverse selection). These agency costs represent the loss in value compared to an ideal situation where there is no information asymmetry and conflict of interests. According to the theorist of agency, an organization is considered efficient if it minimizes the agency costs. This purpose can be intended through an effective governance mechanism.
  • 11. 4.1. External governance mechanisms The external governance mechanism can be implemented as a result of the failure or the weakness of internal governance mechanisms. In the microfinance industry donors and creditors are increasingly relying on information from audited financial statement and rating agencies. These external governance mechanisms are an important mechanism that provides depositors, creditors and shareholders with credible assurances that they will refrain from fraudulent activities. In other words, it reduces informational asymmetries between the different stakeholders and the firm. Audited financial statements are an important tool for the assessment of MFIs by regulators and capital markets. They form an important part of the effective corporate governance. The auditor's role is to provide a disinterested and objective view whether the financial statements on the MFI are in line with generally accepted accounting standards. It is a means to ensure potential investors and donors that MFI complies with the accounting practices and managers do not misrepresent financial information. In the absence of developed equity and debt market, donors and investors rely on independent evaluation of MFIs performance. A MFIs rating reflects a rating agency's opinion of entity's overall creditworthiness and its capacity to satisfy its financial obligations. The raters evaluate objectively and independently the corporate governance in MFI and rank it on a relative rating scale that would facilitate comparison. Unlike typical rating agencies that rate the riskiness of issued debt, microfinance rating agencies rate the overall performance of the MFI in terms of outreach and sustainability.
  • 12. 5. Data and methodological issues Data for this study are obtained from MIX (Microfinance Information Exchange). The performance variables and some governance variables are also obtained from the annual financial reports of the microfinance institutions collected from Microfinance Information Exchange (MIX), a nongovernmental organization whose object is to promote the exchange of information on the microfinance sector in India. All data are secondary collected from the MIX and based on these data. There are mainly two variable; dependent and independent. Dependent variables are OSS (Operational self-sufficiency), OER (Operating cost) and ROA (Return on asset).Where independent variable are SIZE, LOAN, DEPOSITE RATIO, CAPITAL, NO.OF ACTIVE BORROWER, AVG.LOAN BAL.BORROWER, WOMEN BORROWER etc.. There are 60 MFIs out of 148 includes NGOs, NBFIs and BANKs. This is analyzed through hypothesis and regression models. The descriptive statistics for this study are shown in Table 3. The performances of Microfinance Institutions are widely spread. On average, the MFIs recorded a return on assets of 5,935%. While the minimum was-7.58%, the maximum performance was 33% indicating a widely spread performance. Similarly, the studied MFIs have on average an Operational Self-Sufficiency of 85.41% with respectively a minimum and a maximum of 20.345% and 143.33%. With regard to the DEPTH, the average values of relatively weak 220 indicate that the poor borrowers are very well served. On average, the MFIs managers have 8.4 years of experience and 82.4% of these managers are receiving a Fixed-wage. On average, 5 persons serve on the board of an MFI and a standard deviation of 3,32 coupled with a maximum board size of 16 members and a minimum board size of 4 members suggest that these boards are widely dispersed. The unaffiliated directors represent on average 45% of the board members. The descriptive statistics also indicate that on average 39% of all boards
  • 13. are made up of women. In our sample, around half of the MFIs have an internal auditor reporting directly to the board. Moreover, 81% of the MFIs studied have their financial statement audited and 37% of the MFIs forming the sample are rated. The result also shows that 42% of the institutions are regulated, and the individual lending technology constitutes 73% of the cases. The average age standing for the MFI is about 3 years. The NGOs represent 59% of our sample, however, the NBFI and Bank represent respectively 17% and 9% of the sample. Finally, the average inflation rate in all the countries subject to the study is about 16%.
  • 14. FINDINGS As shown in Table 4 dealing with the estimation of the impact on sustainability and outreach, our first hypothesis stipulating that the remuneration system (performance-based compensation or fixed salary) is confirmed. The coefficient of Fixed-wage is not significant in any of the specification. Managerial qualifications as shown by the positive and significant sign of Experience in the OSS, ROA and OER regressions as well as the enviable negative and significant coefficient in the depth indicate that the acquired experience allows MFIs managers to reach poor borrowers and produce better sustainability. Board size is rather positively related to ROA, OSS, and OER suggesting to the contrary that MFIs with larger boards seem to do better. The results reduplicate our second hypothesis and confirm studies that support the view that larger boards are better for corporate performance since members have a range of expertise to help to make better decision, and are harder for powerful CEO to dominate. An important result of this study is the support MFIs with a higher proportion of unaffiliated directors had better sustainability (ROA & OSS) and also reach poor borrowers. The results of the study show that board diversity (higher dproportion of women) improves social performance. This is consistent with recent thinking and discussions which point to the fact that governance reforms have been geared towards the importance of gender diversity, especially in the boardroom, and that the issue of gender diversity is central and could enhance board effectiveness by tapping broader talent pools for their directors resulting in the more diverse board having better relations with other stakeholders such as customers, suppliers, and
  • 15. employees which inevitably translate into performance and firm value. Although microfinance rating agencies rate the overall performance of the MFIs in terms of outreach and sustainability, the empirical results show that this variable does not have any significant influence on MFIs performance. In addition, the study reveals that MFIs having their financial statement audited achieve better sustainability. These MFIs comply with accounting practices and are able to reach higher levels of financial performance. Regulated MFIs do not reach more borrowers but according to the results in Table 4, have significant and positive ROA & OSS. Although this result is diverse from past studies which did not find any relation between these two dimensions, or found a weak relation, it brings the evidence that regulation may assure customers that they are treated fairly and this could lead to more business and better financial performance. Results indicate that the lending technology improves considerably the financial performance of the MFIs. This result can be attributed to the fact that the cost argument is more important than the repayment argument for group lending or village bank. The supposed efficiency in group lending does not hold in India. From another point of view, it can be justified by the new tendency toward the individual micro lending, since this methodology becomes highly recommended.
  • 16. In conformity with the theory, the age of the firm as proxy for reputation impacts positively on performance likewise the size of the MFI. Expectedly, the size of MFI has a significant positive impact on performance. This may be due to the fact that a large firm has the ability to accommodate risk and to enhance productivity through diversification of products and services. The study shows that NGOs are more efficient than NBFI and show better social performance by reaching the poor. It becomes clear that NGOs are more consistent with their social mission than with their financial performance. The results reveal also the significance of controlling for cross country differences. The level of inflation affects negatively the sustainability of MFIs. Finally, the study suggests that the economy of big size affects outreach.
  • 17. Conclusion and Recommendation This report tests empirically the relationship between governance MFIs performance in terms of outreach and sustainability. While using secondary data from MIX as well as from the annual financial reports and from the Mix Market, the study examines the impact of management remuneration, board independence and diversity, internal auditor reporting directly to the board, external governance mechanisms of control, and MFIs in India. Results indicate that not all known governance mechanisms affect performance and in addition, different factors have the differential effect on outreach and sustainability. The study shows that explicit and implicit incentives schemes such as compensation, perks, etc. become less powerful and less able to motivate managers. Results also show that larger boards are better for MFIs performance since members have a range of expertise to help to make better decision and are harder for powerful CEO to dominate. Moreover, the study reveals that microfinance boards with larger proportions of unaffiliated directors achieve better results. Thus, independence of the microfinance board should be encouraged. The fundamental result of this study is that board diversity (higher proportion of women) enhances performance and again the more women there are on the board, the better the performance. Thus board diversity is paramount for enhanced performance of microfinance institution. Having financial statement audited, and being rated by international agencies is synonym to a better financial performance. It seems that external governance mechanisms help MFIs to reach their financial performance. This study allows us to distinguish other factors leading also to a better sustainability such as Regulation and the use of individual lending methodology. However, the MFIs type (NGO) seems
  • 18. to be more consistent with their social mission than with their financial performance. The microfinance institutions characteristics such as age and size affect positively the performance; nevertheless, the level of inflation has a negative impact on the sustainability of MFIs. Although this study brings some clarifications on the link between the governance mechanisms and performance of microfinance in India, several governance mechanisms remain unexplored such as CEO duality, graduate board members, international directors, ownership structure. Thus, it seems relevant to conduct more studies in order to learn more about the impact of these governance mechanisms on outreach and sustainability of MFIs not only in the India.
  • 19. Bibiliography  MFIs in india | Microfinance india  Governance and performance of microfinance institutions in Mediterranean countries. - Free Online Library  Books, journals, articles.  Research papers, reports of researchers etc……..  Indian Association for Savings and Credit | MFIs in India  BSS Microfinance Pvt. Ltd. | MFIs in India  ADARSHA | MFIs in India  Anisha Microfin Association | MFIs in India  Camel Mahila Macts Limited | MFIs in India
  • 20. References: (1) Microfinance Institutions (2) Non-Governmental Organisation (3) Non-Financial Bank Institution (4) This figure quotes the most famous MFIs in the Mediterranean region. (5) Lending methodology refers to the way loans are given. Individual loans, group loans, and village banks (which are bigger groups that often have wider objectives than to serve as a guarantee mechanism only) are the categories used. (6) Jensen, M. C.; Meckling, W. H. 1976. Theory of the firm: managerial behaviour, agency costs, and ownership structure, Journal of Financial Economics 3: 305-350. (7) Informations on the MIX are available on the Web site www.themix.org. The data bases on the MFIs are accessible by the mix- market, an online data base accessible from the MIX site. Mix Market, known formerly under the name of "Virtual Market of Microfinance" was initiated jointly by the UNCTAD and the Government of Luxembourg. In 2001, it was taken in charge by the Consultative Group to Assist the Poor (CGAP), a consortium of backers which works for the development of Microfinance in the world. (8) Although the properties of the Hausman test for endogeneity are not well understood in small samples, this test does not indicate that the individual governance mechanisms are endogenous (Wooldridge 2002).
  • 21. (9) The higher the value of DEPTH, the less poor clients are being served. Therefore from a poverty-alleviation perspective, a smaller value of this variable is preferred. Table 1. Definitions of dependent variables used in analyses Variable Explanation Social Performance: Outreach NAB Logarithm of the number of active borrowers DEPTH The average loan size on GDP per capita Financial Performance: Sustainability ROA Return On Assets OSS Operational Self-Sufficiency Table 2. Definitions of independent variables used in analyses Variable Explanation Loan A loan outstanding per total assets. Women The proportion of the women on the board Audited A dummy that equals one if the financial statement reports directly to the board
  • 22. Rated A dummy that equals one if the MFI is four rated and five rated is equals zero zero Regulation A dummy being one if the MFI is regulated by banking authorities MFI age Number of years since the commencement MFI size Logarithm of the total assets of the MFI NGO The MFI is an NGO and dummy that equals one NBFI The MFI is an non-financial bank institution and dummy that equals one Bank The MFI is an bank and dummy that equals three Economy size Logarithm of total GDP (Gross Domestic Product of the country) for the year t Borrower/staff The active borrower divided by staff members Deposite ratio Total deposite divided by total asset Capital Tptal equity divided by total asset (1) ROA: b ANOVA Model Sum of Squares df Mean Square F Sig. a 1 Regression .205 6 .034 2.292 .036 Residual 3.445 231 .015 Total 3.650 237 a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, LOAN, PORTFOLIOAT30DAYS, CAPITAL, DEPOSITERATIO b. Dependent Variable: ROA Suggestion= here f significant level is less than 5%, so H0 is accepted.
  • 23. a Coefficients Standardized Unstandardized Coefficients Coefficients 95.0% Confidence Interval for B Model B Std. Error Beta t Sig. Lower Bound Upper Bound 1 (Constant) .005 .032 .142 .888 -.058 .067 CAPITAL -.100 .038 -.176 -2.642 .009 -.174 -.025 PORTFOLIOAT3 -.004 .056 -.005 -.070 .945 -.114 .106 0DAYS LOAN -.007 .008 -.057 -.882 .379 -.024 .009 SIZE .032 .032 .068 1.015 .311 -.031 .095 DEPOSITERATIO -.005 .065 -.005 -.072 .942 -.133 .123 NO.OFACTIVEB .001 .001 .122 1.886 .060 .000 .002 ORROWER a. Dependent Variable: ROA Y=a+bx Y=.005-0.1x1-0.004x2-0.007x3+0.032x4-.005x5+0.001x6 X1=capital X2=portfolio X3=days X4=loan X4=size X5=deposit X6=no. of nab (2) OER: b ANOVA Model Sum of Squares df Mean Square F Sig. a 1 Regression .839 6 .140 2.965 .008 Residual 10.937 232 .047 Total 11.776 238
  • 24. a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, PORTFOLIOAT30DAYS, LOAN, CAPITAL, DEPOSITERATIO b. Dependent Variable: OER Suggestion= here f significant level is more than 5%, so H1 (alternate hypothesis) is rejected. a Coefficients Standardized Unstandardized Coefficients Coefficients 95.0% Confidence Interval for B Model B Std. Error Beta t Sig. Lower Bound Upper Bound 1 (Constant) .145 .058 2.515 .013 .031 .258 CAPITAL .236 .067 .231 3.503 .001 .103 .368 PORTFOLIOAT30DAYS -.082 .099 -.053 -.828 .409 -.277 .113 LOAN -.022 .015 -.094 -1.461 .145 -.051 .008 SIZE -.009 .058 -.011 -.161 .873 -.123 .105 DEPOSITERATIO -.021 .115 -.012 -.185 .854 -.249 .206 NO.OFACTIVEBORROWER .000 .001 -.015 -.231 .818 -.002 .002 a. Dependent Variable: OER Y=a+bX Y=0.145+0.236X1-0.082X2-0.022X3-0.009X4-0.021X5+0.00X6 (3) OSS: b ANOVA Model Sum of Squares df Mean Square F Sig. a 1 Regression .678 6 .113 .964 .451 Residual 27.201 232 .117 Total 27.879 238
  • 25. a. Predictors: (Constant), NO.OFACTIVEBORROWER, SIZE, PORTFOLIOAT30DAYS, LOAN, CAPITAL, DEPOSITERATIO b. Dependent Variable: OSS Suggestion= here f significant level is less than 5%, so H0 is accepted. a Coefficients Standardized Unstandardized Coefficients Coefficients 95.0% Confidence Interval for B Model B Std. Error Beta t Sig. Lower Bound Upper Bound 1 (Constant) 1.264 .091 13.918 .000 1.085 1.443 CAPITAL -.118 .106 -.075 -1.108 .269 -.326 .091 PORTFOLIOAT30DAYS -.129 .156 -.055 -.826 .409 -.437 .179 LOAN .029 .023 .081 1.226 .221 -.017 .074 SIZE -.073 .091 -.054 -.796 .427 -.253 .107 DEPOSITERATIO -.198 .182 -.075 -1.090 .277 -.557 .160 NO.OFACTIVEBORROWER -.001 .002 -.055 -.830 .407 -.005 .002 a. Dependent Variable: OSS Y=a+bX Y=1.264-0.118X1-0.129X2+0.029X3-0.073X4-0.198X5-0.001X6