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Citation: Mata, Mário Nuno, Sayyed
Sadaqat Hussain Shah, Nida Sohail,
and Anabela Batista Correira. 2023.
The Effect of Financial Development
and MFI’s Characteristics on the
Efficiency and Sustainability of Micro
Financial Institutions. Economies 11:
78. https://doi.org/10.3390/
economies11030078
Academic Editor: Robert Czudaj
Received: 18 August 2022
Revised: 20 December 2022
Accepted: 11 January 2023
Published: 1 March 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
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4.0/).
economies
Article
The Effect of Financial Development and MFI’s Characteristics
on the Efficiency and Sustainability of Micro
Financial Institutions
Mário Nuno Mata 1, Sayyed Sadaqat Hussain Shah 2, * , Nida Sohail 2and Anabela Batista Correira 1, *
1ISCAL-Instituto Superior de Contabilidade e Administração de Lisboa, Instituto Politécnico de Lisboa,
Avenida Miguel Bombarda 20, 1069-035 Lisbon, Portugal
2Faculty of Arts and Social Science, Department of Commerce and Finance, Government College University
Lahore, Lahore 54000, Pakistan
*Correspondence: shah.sadaqat@gmail.com (S.S.H.S.); ambatista@iscal.ipl.pt (A.B.C.);
Tel.: +92-333-445-3189 (S.S.H.S.)
Abstract:
The Micro Financial Institutions (MFIs) have been touted as development strategies for
Emerging Markets and Developing Economies (EMDEs) which merits research into the effect of
financial development on the efficiency and sustainability of the MFIs. The Efficient and sustain-
able MFIs significantly paved the way for the economic development of a country particularly in
developing countries. Surprisingly there are very rare studies that examine the nexus of financial
development, MFIs efficiency, and sustainability. Also, these studies are confined to the impact of
financial development either on the efficiency or sustainability of MFIs. Addressing this gap, the
study attempts to explore the country-specific and MFIs-specific factors which significantly affect
the efficiency and sustainability of the MFIs. For this purpose, the study first determines whether
financial development contributes to the efficiency and sustainability of MFI. Secondly, the effect of
MFIs’ specific characteristics such as credit risk, market risk, liquidity risk, lending strategy, Develop-
ment Financial Institutions (DFIs) funds management, financial outreach, and poverty alleviation
on the efficiency and sustainability of MFIs. The study has been conducted for Bangladesh, India,
and Pakistan consisting of a panel data set of 12 MFIs over a period spanning from 2008–2018 using
Stochastic Frontier Analysis and Cobb Douglas production function regression analysis. Overall
empirical analysis reveals that financial development has significantly affected the efficiency and
sustainability of the MFIs. While specific characteristics such as poverty alleviation and DFIs funds
management have been shown to improve MFIs efficiency whereas an increase in credit risk, lending
strategy, and market risk decrease MFIs sustainability and liquidity risk along with an increase
in financial outreach leads to a decrease in MFIs efficiency. The directions and magnitudes of the
findings suggest the stakeholders for all three countries for the significant direction leads to the
efficiency and sustainability of MFIs. Moreover, future research could strive to understand the aspects
of financial development which negatively correlate with the MFIs’ efficiency and sustainability such
as stringent tax policies, creditor rights protection, and implementation of rules and regulations.
Keywords:
Micro Financial Institutions; Emerging Markets and Developing Economies; sustain-
ability; Development Financial Institutions; Stochastic Frontier Analysis; Cobb Douglas production
function; market risk
1. Introduction
The Global Financial System with its vast and interconnected financial institutions
constituting central banks, commercial banks, insurance corporations, investment compa-
nies, capital markets, money markets, and finance ministries holds immense importance in
the financial stability of the world economy through managing public money being created
Economies 2023,11, 78. https://doi.org/10.3390/economies11030078 https://www.mdpi.com/journal/economies
Economies 2023,11, 78 2 of 16
by economic sectors ensuring its’ suitable use for beneficial objectives promoting the ex-
pansion of economic activity (Khawja 2013). However, financial development defined as
ensuring creditor’s rights protection, reducing agency-related costs, alleviating imbalance
in information, easing information accessibility, improving financial institution quality,
commitment to accounting policies, and financial disclosure transparency has primarily
been concentrated in developed economies (Lei et al. 2018).
The non-prevalence of financial development in the Emerging Markets and Devel-
oping Economies (EMDEs) has resulted in the financial exclusion of the 1.7 billion world
population from the formal financial sector defined as the inability of certain population
segments from availing finances due to their socioeconomic circumstances and the chal-
lenges they have in meeting the requirements of conventional financial institutions, their
involvement in the financial sector is restricted (Demirguc-Kunt et al. 2017). Development
Financial Institutions (DFIs) primarily function to provide capital for economic develop-
ment projects serving as drivers of industrialization which necessitates their presence for
economic growth. Micro Financial Institutions (MFIs) services are an extension of DFIs op-
erating for the provision of financial services to the Micro, Small, and Medium Enterprises
(MSMEs) which form an integral part of the developing economies (PIDE 2021).
As a result of the initiative taken by Muhammad Yunus of Bangladesh in the 1970s
in the form of Grameen Bank to mainstream the marginalized sectors of the economy by
providing financial services tailored to the credit needs of the poor, the world’s first micro-
finance institution with the dual functionality of social and financial inclusion emerged
MSMEs (Mainsah et al. 2004). The only objective of establishing MFIs was to combat the
informal intermediation impeding the economic development of MSMEs, a significant
economic sector in the Emerging Markets and Developing Economies (EMDEs) (IBRD IDA
2022). Lack of considerable collateral, borrower quality evaluation, and high expenses
associated with processing small loans have rendered MFIs the only source for granting
microloans to borrowers without collateral and credit checks, making it difficult to remove
credit restrictions on low-income MSMEs (World Bank 2015).
Traditional financial institutions are highly regulated due to their vital role in the
financial stability of a nation. Therefore, MFIs that aim to increase financial inclusion
while contributing to poverty alleviation must demonstrate financial sustainability and
profitability in their portfolio quality (Basharat et al. 2014;Falcone 2018). The issue of
shadow banking has led to the financial exclusion of MSMEs in emerging markets and
growing countries such as India, Pakistan, and Bangladesh. However, MSMEs that have
the potential to contribute to economic growth need financial support, and MFIs serve
the goal of integrating impoverished households and MSMEs into the financial sector,
contributing to the development of the financial sector (Falcone 2020;Jassim and Khawar
2018;Wu 2022).
To generate insights for the MFIs, it is necessary to investigate the cause-and-effect
relationship between financial development and the sustainability and efficacy of the mi-
crofinance sector to the MFIs’ mission of broadening financial integration through poverty
alleviation and expanding the reach of an economy’s financial sector. The Efficient and
sustainable MFIs significantly paved the way for the economic development of a country
particularly in developing countries (Barr 2004). But most of policymakers and scholars
conduct separate conversations about financial development and microfinance (Barr 2004).
While financial development and MFIs are inseparable that guide the stakeholders to devise
the policyholder for substantial future financial development goals. For bridging the gap
of these unnoticed phenomena, the study attempts to evaluate the effect of financial devel-
opment on the efficiency and sustainability of micro-financial institutions. Also, this study
incorporated MFI-specific characteristics such as financial outreach, poverty alleviation,
lending strategy, and DFIs’ funding management to of financial risks such as market risk,
credit risk, and liquidity risk on the efficiency and sustainability of MFIs to identify the
significant grass root factors that lead to economics progress.
Economies 2023,11, 78 3 of 16
2. Literature Review
Financial sector development assessed on four key dimensions of size, access, effi-
ciency, and sustainability focusing on increasing inclusiveness in the financial systems
while improving access to financial services for the underserved validates the role of MFIs
in eliminating the constraints to growth of MSMEs (World Bank 2009). Financial integration
of the shadow banking sector can assist the financial sector in the management of liquidity,
maturity, and credit risk thereby improving the financial system stability of Emerging
Markets and Developing Economies (EMDEs) (Ghosh et al. 2012). Financial development
leads to a reduction in liquidity risk, protecting creditor rights and facilitating possession of
collateral in case of default allowing intangibles such as patents to be pledged as collateral
for securing financial borrowing (Lei et al. 2018).
The importance of microfinance in reaping the benefits of an inclusive financial system
has been implemented in Islamic finance through the innovation of Islamic microfinance
currency encouraging financial stability while creating a community for Islamic microfi-
nance providers, participating merchants, Zakat and Waqf institutions providing capital
assistance to allow recipients in achieving poverty reduction and become Zakat payer in
the future (Rozzani et al. 2015). The theory of economic growth postulates the Growth
Model to analyze the effect of changes in technological progress modeled as production
function augmentation on the level of output Y in a production function over time. Capital
augmentation includes efficiency parameters in the production function through multi-
plication by Capital K and can be used to assess the effect of changes in technological
factors such as financial development on the productivity of the inputs in the production
of output (Mankiw 2012). Taking this into account, it seems possible to formulate the
following hypotheses:
Hypotheses 1 (H1).
Financial development leads to a decrease in the technical efficiency of
the MFIs.
Hypotheses 2 (H2).
Financial development results in the deterioration of the sustainability
of MFIs.
The uniqueness of microfinance in fulfilling social objectives as well as contributing
to financial development through serving productive sectors of the economy dominated
by MSMEs in developing economies has shown to be affected by the national income
and development stage of the country (Maksudova 2010). The impact of the financial
crisis of 2008 across different ownership types of MFIs showed that microfinance banks
showed a productivity drop due to a decline in technology, NBFIs showed decreased
productivity due decline in technology and inefficiency, cooperatives showed decreased
productivity due to a reduction in efficiency and innovation while among all the ownership
types, NGOs showed the lowest productivity decline (Wijesiri 2016). The effect of financial
development in terms of MFI ownership transition from state-owned to privately owned
banks on the profit and cost efficiency of MFIs showed better internal technical efficiency as
well as allocative efficiency of privately owned MFIs along with reforms such as listing on
stock exchanges and macroeconomic conditions such as growth rate and GDP per capita
(Mutarindwa et al. 2021).
Economic growth indicative of the developed financial sector increases demand for
credit due to the expansion of profitable opportunities for microenterprises allowing MFIs
to charge higher interest rates thereby lowering the cost of funds along with bolstering
financial sustainability through reducing default as Private Credit to GDP is negatively
associated with Portfolio at Risk for more than 30 days (PAR-30) which is a major indicator
of MFIs’ sustainability (Ahlin et al. 2011). Recent financial developments in microfinance
such as increasing competition, commercialization, technological advancement, financial
liberalization, and regulation policies of government have resulted in increasing focus
on the financial sustainability of the MFIs to reduce the cost of lending money and cover
Economies 2023,11, 78 4 of 16
it from the outstanding loan portfolio (Hermes and Lensink 2011). Compliance with
prudential regulations and supervision can be especially costly for MFIs equaling 12–13%
of their non-interest payments as MFI supervision has a causal effect on the trade-off
between profitability and outreach with profit-oriented MFIs facing prudential supervision
responding through curtailing their outreach (Cull et al. 2011). The following hypothesis is
as follows:
Hypotheses 3 (H3).
MFIs’ sustainability is affected by the market risk arising from the extent of
financial development in the economy.
The intersection of microfinance at three points renders MFIs viable as a development
strategy with firstly the primary purpose served by MFIs being poverty alleviation, sec-
ondly providing intermediation channels for financial inclusion and thirdly regulating
MFIs having access to capital markets and taking deposits to ensure an increase in the
financial outreach (Otero 1999). Profit-oriented MFIs have been shown to operate efficiently
setting more appropriate loan prices due to being able to easily access investment into
the sector regardless of ‘Mission Drift’ concerns of trading-off social impact for financial
performance while not-for-profit organizations have been assumed to be insulated from
competitive pressures and hence prone to inefficiencies (Roberts 2013). The success of MFIs
in a country is determined by the incumbent government’s political ideology as financial
inclusion of the poorly received attention in the political agendas of governments in de-
veloping economies while MFIs under right-wing governments or centrist regimes have
higher efficiency than MFIs operating under left-wing governments due to government
intervention forcing charging of lower interest rates on loans (Gul et al. 2017).
MFIs’ outreach is negatively correlated with their efficiency, and MFIs with a lower
average loan balance, which is a measure of the depth of outreach, and more women
borrowers, which is a measure of the breadth of outreach, are less efficient, indicating that
MFIs striving for efficiency while registering decreased outreach to the poor led to greater
poverty reduction (Hermes et al. 2011). One of the main functions of MFIs is the provision of
financial services to the excluded segments of the economy measured as financial outreach
and MFIs pursuing higher levels of outreach can be achieved through an increase in
total assets and the number of active borrowers
(Liñares-Zegarra and Wilson 2018).
The
strength of corporate governance is considered a major determinant of MFI efficiency after
indebtedness as the efficiency of the Board of Directors in its monitoring and advising
roles is positively associated with its independence, board expertise, audit committee, and
separation of CEO and Chairman while it is negatively associated with the size of the board
(Tchuigoua 2015). Taking this into the account, it seems possible to formulate the following
hypothesis:
Hypotheses 4 (H4).
MFIs’ objectives of poverty alleviation and improving the outreach of the
financial sector affect MFIs’ efficiency.
The analysis of the impact of microfinance on the MSMEs as compared to other sources
of credit such as bank loans and informal credit showed that microfinance loans have the
advantage of meeting the working capital expenditure of MSMEs which raises the issue of
the ‘Financial systems’ approach stressing MFIs to improve operational self-sufficiency vs.
‘Poverty lending’ approach focusing on poverty eradication through subsidized credit on
low-interest rates (Hermes and Lensink 2011). The importance of Comprehensive Group
Training in microfinance can be assessed through Microfinance Client Awareness Index
used to gauge the financial literacy of the customers of MFIs which allows respondents to
score their understanding of services being availed from the MFI. (Kalra et al. 2015).
The diversification of MFIs’ revenue sources deals with high operational costs as-
sociated with smaller loans; however, diversified MFIs may have to deal with moni-
toring difficulties and operational inefficiencies while MFIs employing group lending
strategy show improved operational sustainability although regulation negatively affects
Economies 2023,11, 78 5 of 16
sustainability (Zamore 2018). Social capital is favorably connected with European MFIs’
repayment, profitability, outreach, and efficacy. through lowering credit risk while increas-
ing financial performance and social outreach as the intensity of social capital increases
(
Chmelíkováet al. 2018
). The tradeoff between the microfinance institutionalist approach
for sustainability and welfarist approach for outreach stresses appropriate lending strategy
along with optimum loan amount maximizing efficiency for the three loan techniques
of individual lending, group lending, and village banking, or a combination of the three
loan methods (Widiarto et al. 2017). Taking this into consideration, it seems possible to
formulate the following hypothesis:
Hypotheses 5 (H5).
Credit risk arising from MFIs’ lending strategy affects the sustainability
of MFIs.
International institutions’ funding South Asian MFIs emphasize the social objective
of high operational costs for loan generation hurt the breadth and depth of outreach,
while the breadth of outreach has a positive correlation with performance determinants of
MFIs and depth of outreach has a negative association with performance determinants of
MFIs (
Bibi et al. 2013
). The provision of financial services to the micro-enterprises requires
subsidies for financial efficiency as efficient MFIs show better performance than commercial
banks in portfolio quality facilitating the rate of loan recovery by increasing financial literacy
and group monitoring (Koveos and Randhawa 2004). MFIs’ transformation from NGOs into
shareholder-owned financial institutions for independence from donors and gaining access
to commercial funding caused an average reduction in operational costs and volatility in
funding costs while overall profits decreased due to enforcing compliance on regulations
imposing stricter risk management (D’Espallier et al. 2017).
The business model of MFIs is categorized as profit-oriented and self-sustaining busi-
nesses or subsidized and not-for-profit organizations choosing between maximizing their
financial revenue or yield which again can be segregated into output that maximizes aver-
age loan size or output that maximizes the number of loans (Bos and Millone 2015). The
social cost of subsidies granted to MFIs, as measured by the Subsidy Dependent Index,
is an input for subsidized MFIs, whereas outreach is the social output, as measured by
the Outreach Index. The financial sustainability of MFIs improves through learning by
doing, which makes mature MFIs financially efficient (Wijesiri et al. 2017). The recent de-
velopments in microfinance such as increasing commercialization, the decline in subsidies,
and the intensification of global competition have created an uncertain environment in
the microfinance industry with the MFI size variable having a negative and significant
relationship with the social efficiency as compared to financial efficiency (Fall et al. 2018).
The microfinance sector of developing economies is exposed to three main types of financial
risk, namely liquidity risk, interest rate risk, and foreign exchange (FX) risk, necessitating
increased financial assistance from international donors and DFIs for risk mitigation, as
banks offering microcredit facilities face greater liquidity risk and lower FX risk, whereas
MFIs operating as NGOs, Credit Unions, and cooperatives have high-interest rate risk and
FX risk (Gietzen 2017). In line with the above-cited literature, it seems possible to formulate
the following hypothesis:
Hypotheses 6 (H6).
MFIs’ exposure to liquidity risk due to the Development of Financial Institu-
tions’ funding management affects the efficiency of MFIs.
3. Methodology
The research will determine the impact of financial sector development on the effi-
ciency and sustainability of Micro Financial Institutions, with MFIs’ efficiency and sustain-
ability as the response or dependent variables and financial development as the predictor
or independent variable, while assessing the impact of MFIs’ financial risk management,
financial outreach, poverty alleviation, advancing methodology, and DFIs’ funds. with
Economies 2023,11, 78 6 of 16
MFIs’ efficiency and sustainability as the dependent variables and poverty alleviation,
financial outreach, market risk, credit risk, and liquidity risk as the independent variables
while moderating variables are the MFIs’ market risk
×
financial development, credit
risk ×advancing
methodology and liquidity risk
×
DFIs’ fund’s management. A detailed
explanation of the variables and their constructs is provided in Table 1below:
Table 1. Explanation of variables and their constructions.
Variables Indicators Financial Ratios
Financial Development Bank Deposits/GDP Bank Deposits
GDP
MFI Efficiency Return on Equity Profit After Tax
Total Equity
MFI Sustainability Operational Self Sufficiency Operating Revenue
Loan loss provision+Financial Exp.+Operating Exp.
Credit Risk Loans Written Off Loans Written Off
Avg. Loans Outstanding
Market Risk Debt to Equity Ratio Total Liabilities
Total Equity
Liquidity Risk Cash Position Indicator Cash and Deposits
Total Assets
Lending strategy Operating Expense Ratio Operating Expense
Avg. Gross Portfolio
DFIs’ Funds Management Funding Expense Ratio Interest Expense
Avg. Gross Portfolio
Financial Outreach Cost per borrower Operating Expense
No. of borrowers
Poverty Alleviation GNI per capita Gross National Income Per Capita
Note: See Appendix A—Characteristics of Variables.
3.1. Stochastic Frontier Analysis
Previous research has primarily employed stochastic frontier analysis to estimate the
efficiency of production functions. It is a parametric frontier technique based on the theory
that no economic agent can exceed the ideal frontier, and it estimates efficiency, which is
defined as the maximization of output with a given level of input or production technology.
Statistically, frontier parameters and inefficiency can be deduced by providing a production,
cost, or profit function and differentiating between measurement error and residual term
expressing inefficiency. SFA presupposes the quasi-concavity of the production function
and predicts a declining marginal rate of technical substitution, as the entity is considered
technically efficient when it is working at the best practice level or producing maximum
output with resources equal to its capacity. The optimal production function for bank
performance has the following functional form and taking into account the above, it is
possible to construct the following expressions for testing the relevant hypotheses:
yit =βxit +εit (1)
where εit = vit + ui(2)
The abovementioned equation indicates y
it
as the observed dependent variable or
MFIs’ efficiency which has been measured through ROE,
β
is the parameter vector of
inputs, x
it
is our independent variables i.e., poverty alleviation, financial outreach, market
risk, credit risk, and liquidity risk,
εit
is the error term, v
it
is time-variant random error
and u
i
is the time-invariant firm specific parameter (Mutarindwa et al. 2021). A stochastic
production function with output-oriented technical inefficiency is specified as:
lnyi= lnyi
0−ui(3)
lnyi= xiβ+ vi(4)
The presence of constraints will reduce observed ROE from efficient ROE y
i
0
or optimal
ROE by non-negative term u
i
and the percentage difference is attributed to the presence
of technical inefficiency. The interpretation of u is u times 100 measures the percentage
shortfall of the desired frontier level of output due to technical constraints. The value of u
is equal to inefficiency having a distribution with mean
µ
and variance
σ2
exponentially
Economies 2023,11, 78 7 of 16
distributed (
µ
=
σ2
) where modeling of inefficiency variance is a function of exogenous
covariates (Kumbhakar et al. 2015). SFA will be applied to evaluate the first and the second
hypothesis to assess the impact of financial development on the efficiency and sustainability
of the Micro Financial Institutions.
Hypotheses 1 (H1).
Financial development leads to a decrease in the technical efficiency of
the MFIs.
lnPAT
Equityit
=α1+β1lnBank Dep.
GDP ct
+vit +ui(5)
In Equation (5), the PAT/Equity is the ratio between profit after tax and the total
equity of microfinance organizations as a proxy of MFI Efficiency, i.e., observed dependent
variable while Bank Deposit/GDP is the ratio between total bank deposit of microfinance
organization to the gross domestic product of the country as a proxy of financial develop-
ment.
α1
is a constant,
β1
is a co-efficient of financial development, v
it
is the time-variant
error term, and uiis the time-invariant firm-specific term.
Hypotheses 2 (H2).
Financial development results in the deterioration of the sustainability
of MFIs.
ln(OSS)it =α2+β2lnBank Dep.
GDP ct
+vit +ui(6)
In Equation (6), OSS is the Operational Self Sufficiency as an indicator of MFI Sustain-
ability while Bank Deposit/GDP is the ratio between total bank deposits of microfinance
organization to the gross domestic product of the country as an indicator of financial
development to test H2 mentioned above.
Stochastic Frontier Analysis will be employed to examine the effect of financial de-
velopment on the sustainability and efficacy of MFIs operating in Pakistan, India, and
Bangladesh. MFIs and to test the relevant hypothesis we developed above.
3.2. Cobb Douglas Production Function
The Cobb-Douglas production function in economics illustrates the technological
relationship between two or more inputs and the output that can be produced by those
inputs. It is a method for calculating the effect of changes in a production function’s inputs,
relevant efficiencies, and outputs. Considering the above, it is possible to construct the
following expressions for testing the relevant hypotheses:
Yt=α0×Lα1
t×Kα2
t(7)
Ln Yt=α0+α1Ln Lt+α2Ln Kt+ ut(8)
The above equation denotes Y
t
as the output,
α0
as the constant, L
t
as the labor
input, K
t
as the capital input,
α1
and
α2
are the elasticity parameters and u
t
as a random
disturbance (Zellner et al. 1966). Cobb Douglas production function was used to develop
the mathematical guidelines for estimating the sustainability of MFIs through the impact
of financial development on the market risk those MFIs face and the impact of credit risk
depending on the lending strategy while determining the efficiency of MFIs through the
impact of poverty alleviation and financial outreach as well as the impact of liquidity risk
brought on by DFIs’ funding management using Generalized Least Squares
Hypotheses 3 (H3).
The effect of the market risk arising from the extent of the financial development
of the economy on MFIs’ sustainability.
Economies 2023,11, 78 8 of 16
To test the relation in H3, the following equation is constructed;
ln (OSS)it =β0+β1lnLiabs
Equi. it
+β2Bank Dep.
Gross Domestic Product ×Liabs
Equi. ct
+εit (9)
In Equation (9), OSS is the Operational Self Sufficiency as an indicator of MFI Sustain-
ability while Bank Deposit/GDP is the ratio between the total bank deposit of microfinance
organization to the gross domestic product of the country as an indicator of financial
development to the test H3 mentioned above.
Hypotheses 4 (H4).
The effect of improving the outreach of the financial sector and MFIs’ objective
of poverty alleviation on MFIs’ efficiency.
lnPAT
Equityit
=β0+β3ln(GNI Per Capita)ct +β4ln(Cost Per Borrower)it +εit (10)
Above constructed Equation (10) addresses the relation in H4 where PAT/Equity is
the ratio between profit after tax and the total equity of microfinance organizations as a
poxy of MFI Efficiency, i.e., observed dependent variable while GNI Per Capita as a proxy
for poverty alleviation and Cost Per Borrower is an indicator for financial outreach.
Hypotheses 5 (H5).
The effect of the credit risk arising from MFIs’ lending strategy on the
MFIs’ sustainability.
ln (OSS)it =β0+β1lnLoans Written Off
Avg. Loans Outstandingit
+β2LiabsLoans Written Off
Avg. Loans Outstanding ×Cash and Deposits
Total Assets. ct +εit
(11)
Equation (11) explains the association of H5, where OSS is the Operational Self Suffi-
ciency as an indicator of MFI Sustainability while Loans Written Off/Avg. Loans Outstand-
ing is the ratio between loans written by microfinance organizations with their outstanding
average loans for the poxy of credit risk. Further, the Cash and Deposits/Total Assets are
used for assessing the liquidity risk associated with the MFI.
Hypotheses 6 (H6).
The effect of the MFIs’ exposure to liquidity risk due to the Development of
Financial Institutions’ funding management on MFIs’ efficiency.
lnPAT
Equi. it =β0+β7lnCash and Deposits
Total Assets it
+β8Interest Expense
Avg Gross Portfolio ×Cash and Deposits
Total Assets it +εit
(12)
Equation (12) attempts to explain the logical relation of H6, where PAT/Equity is the
ratio between profit after tax and the total equity of microfinance organizations as a poxy
of MFI Efficiency i.e., observed dependent variable while Cash and Deposits/Total Assets
are used for assessing the liquidity risk associated with the MFI and Interest Expense/Avg
Gross Portfolio is used for DFIs’.
3.3. Data Collection Procedure
The research data consists of panel data from twelve MFIs chosen from Bangladesh,
India, and Pakistan over 10 years. The selected MFIs were ranked highest in each individual
and financial data were obtained from the World Bank’s Microfinance Information Exchange
(MIX)
1
data for the period FY2008 to FY2018. For the period of FY2008–FY2018, data for
country-specific variables such as financial development and poverty alleviation were
collected from the World Bank
2
and incorporated into efficiency estimation using the Meta
frontier technique to generate comparative efficiency scores for each economy.
Economies 2023,11, 78 9 of 16
4. Results and Discussion
The section provides a detailed estimation of the tests we ran on our dataset. Models 5
to 12 were run for all three countries Bangladesh, India, and Pakistan. The tables below
provide the output of the variable and a detailed explanation is provided against each table
that satisfies our hypotheses. Tables 2and 3describe the effects of financial development
on the efficiency and sustainability of MFIs, whereas Tables 4–7describe the unique effects
of MFIs’ specific characteristics on those outcomes.
In Table 2, the Stochastic Frontier Analysis (SFA), shows a log-likelihood value for all
three countries is less than the value of Wald chi-square, which means that the financial
development does not result in technical inefficiency in Bangladesh, India, and Pakistan
and paved the ways for determining the impact of financial development on the financial
resources of MFIs similar to loans, DFIs’ funds, cash and the financial services of MFIs.
Table 2. SFA of Financial development and MFI efficiency.
MFI Efficiency Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Financial Development
−1.638 0.000 8.429 0.001 −9.741 6.376
_cons 0.447 0.001 −41.326 0.006 28.451 21.926
p > |z| 0.000 0.000 0.000 0.000 0.127 0.194
Sigma_v 0.000 0.000 0.000 0.000 0.635 0.321
Sigma_u 1.309 0.395 3.102 0.935 1.372 0.587
Wald Chi 264 381 233
Log-likelihood −13.960 −23.452 −18.642
Years Yes Yes Yes
The coefficient value for financial development in Bangladesh is
−
1.637 meaning
that return on equity of the Bangladesh MFIs decreases by 1.637 with a 1 unit increase in
financial development indicating that in Bangladesh financial markets are more established
than the MFIs which may lead to MFI clients taking up multiple loans, reducing efficiency
(Hermes et al. 2011). While the value for constant is 0.447 which means that assuming
financial development is absent in the production function then the value for MFI efficiency
will be 44 percent. While in India, the financial development coefficient is 8.429 implying an
increase in MFI efficiency by 8.429 percent with a 1 unit increase in financial development
signifying increased creditor rights’ protection. Results are in line with the findings of
Hermes et al. (2011) that MFI efficiency is positively associated with the level of financial
market development. The value of the coefficient for constant is
−
41.325 which shows
that MFIs’ will decrease 41.325 percent with a lack of financial development implying that
the financial development leads to technical efficiency for MFIs. Lastly, in Pakistan, the
coefficient suggests that the efficiency of MFI Pakistan decreases by 9.740 percent with
a 1 unit increase in financial development (Hermes et al. 2011). The coefficient value
for constant is 28.45 which shows that the MFIs’ efficiency will increase in the absence
of financial development. Whereas, the minimum value of sigma_v and sigma_u, the
time-variant and invariant random errors indicate the least shortfall of MFIs’ efficiency
(Hartarska and Nadolnyak 2007).
The effect of financial development on the sustainability of MFIs shows that financial
development does not negatively impact MFI characteristics such as write-off ratio, finan-
cial leverage, and lending strategy to assess its influence on Operational Self-Sufficiency
(OSS) which has been used to gauge MFI sustainability for each of the economies namely
Bangladesh, India, and Pakistan (Nurmakhanova et al. 2015). In Table 3, Financial develop-
ment has been shown to improve MFIs’ loan portfolio and repayment rates for Bangladesh
and India consequently improving MFIs’ sustainability as 1 unit change in financial de-
velopment for Bangladesh causes a 1.571 unit increase in MFI sustainability means that
the MFIs on the welfare of the poor in Bangladesh are sustainable due to its good financial
performance (Hossain and Khan 2016) and 1 unit change in financial development for
Economies 2023,11, 78 10 of 16
Pakistan causes 10.590 unit increase in MFI sustainability whereas the sustainability of
MFIs for India is irrelevant of the financial development as the MFI sustainability decreases
4.25 unit with an increase in financial development instead depending on loan recovery
and borrower retention (Njeru 2016).
Table 3. MFI sustainability and SFA of Financial development.
MFI Sustainability Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Financial Development
1.571 0.000 −4.253 0.000 10.591 0.000
_cons −4.179 0.000 18.764 0.000 −35.761 0.001
p > |z| 0.000 0.000 0.000 0.000 0.000 0.000
Sigma_v 0.000 0.000 0.000 0.000 0.000 0.000
Sigma_u 0.281 0.085 0.509 0.153 1.034 0.312
Wald Chi2121 212 639
Log-likelihood 2.947 −3.566 −11.365
Years Yes Yes Yes
In Table 4, the regression analysis of MFI sustainability as the dependent variable
and market risk as the independent variable with market risk
×
financial development as
moderating variable shows that Bangladesh has a negative relationship between market
risk and MFI sustainability implying MFI sustainability decreases by 0.10 unit with 1 unit
change in market risk. MFI sustainability increases by 0.029 units with a 1 unit increase in
the effect of financial development on the market risk faced by MFIs. The coefficient value
for the market risk of India is
−
0.146 showing increase in market risk causes a
0.146-unit
decrease in MFI sustainability while the coefficient value for market risk
×
financial
development is –0.301 showing an increase in market risk due to financial development
leads to a decrease in MFI sustainability (Bich 2016). The coefficient value for the market
risk of Pakistan is
−
0.114 showing increase in market risk causes a 0.114-unit decrease in
MFI sustainability while the coefficient value for market risk
×
financial development is
−
0.118 implying a 0.118 unit decrease in MFI sustainability with a 1 unit increase in the
market risk due to financial development (Illangakoon et al. 2022).
Table 4. MFI Sustainability and Market risk.
MFI Sustainability Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Ln Market Risk −0.109 0.093 −0.146 0.037 −0.115 0.099
Market Risk ×FD 0.029 0.051 −0.302 0.072 −0.119 0.225
_cons 1.527 0.088 0.214 0.036 −0.375 0.215
p > |t| 0.247 0.566 0.000 0.000 0.255 0.602
R20.472 0.273 0.002
Sigma_u 0.273 0.072 0.346
Sigma_e 0.146 0.159 0.474
Years Yes Yes Yes
In Table 5, the coefficient value for poverty alleviation in Bangladesh is 0.170 meaning
MFI efficiency increases by 0.170 unit with 1 unit change in poverty alleviation while the
coefficient value for financial outreach of MFIs is
−
0.151 showing 1 unit increase in financial
outreach decreases MFI efficiency by 0.151 unit (Hermes et al. 2011). The coefficient value
for poverty alleviation in India is 0.610 showing a 1-unit increase in poverty alleviation
causing MFI efficiency to increase by 0.610 units while the value for financial outreach is
−
0.699 showing a 1-unit increase in MFI financial outreach causing a 0.699 unit decrease in
MFI efficiency. The coefficient value for poverty alleviation in Pakistan is 1.028 showing
1 unit increase in poverty alleviation causes a 1.028-unit increase in MFI efficiency. The
Economies 2023,11, 78 11 of 16
coefficient value of financial outreach is 0.1613 showing 1 unit increase in financial outreach
causes a 0.1613-unit increase in MFI efficiency (Kamarudin and Anwar 2020).
Table 5. MFI efficiency and Poverty Alleviation.
MFI Efficiency Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Ln Poverty Alleviation 0.170 0.122 0.610 0.836 1.028 0.436
Ln Financial Outreach −0.152 0.097 −0.700 0.463 0.161 0.273
_cons −0.523 0.593 −5.081 6.026 −7.661 2.721
p > |t| 0.170 0.127 0.470 0.139 0.023 0.558
R20.011 0.065 0.038
Sigma_u 0.115 0.330 0.345
Sigma_e 0.105 1.094 0.385
Years Yes Yes Yes
In Table 6, the coefficient value for credit risk faced by MFIs of Bangladesh is 0.163
showing an increase in MFI sustainability by 0.163 units with a 1 unit increase in MFI
credit risk, and the value for moderating variable of credit risk
×
lending strategy is
0.048 implying 1 unit increase in the effect of MFI’s lending strategy on credit risk increases
MFI sustainability by 0.048 unit. The coefficient value for credit risk for MFIs of India
is
−
0.1641 showing 1 unit increase in credit risk causes a 0.164-unit decrease in MFI
sustainability while the value for the moderating variable of credit risk
×
lending strategy
is 0.2400 which shows a 1 unit increase in the effect of credit risk on lending strategy
decreases MFI sustainability by 0.24007 pc. The value of credit risk for MFIs of Pakistan
is
−
1.221 showing a 1 unit increase in credit risk causes a 1.221-unit decrease in MFI
sustainability while the value for credit risk
×
lending strategy is 0.038 showing a 1 unit
increase in moderating variable of credit risk
×
lending strategy causes 0.038 unit increase
in MFI sustainability.
Table 6. MFI sustainability and Credit risk and Lending strategy.
MFI Sustainability Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Ln Credit Risk 0.163 0.022 −0.164 0.051 −1.221 1.202
Ln Credit Risk ×Lending strategy 0.048 0.063 0.240 0.062 0.039 0.013
_cons 0.331 0.064 1.153 0.054 0.692 0.107
p > |t| 0.467 0.451 0.003 0.000 0.316 0.004
R20.281 0.712 0.705
Sigma_u 0.225 0.058 0.282
Sigma_e 0.104 0.185 0.257
Years Yes Yes Yes
In Table 7, the coefficient value for liquidity risk faced by MFIs of Bangladesh is
−
0.296
showing 1 unit increase in liquidity risk causes MFI efficiency to decrease by 0.296 units.
While the value for moderating variable of liquidity risk
×
DFI funding management
is
−
0.028 showing a 0.028-unit decrease in MFI efficiency with a 1-unit increase in the
effect of liquidity risk on DFI funding management. The coefficient value of liquidity risk
for MFIs of India is 0.916 showing 1 unit increase in liquidity risk measured by the cash
position indicator causes a 0.916-unit increase in MFI efficiency. The coefficient value for
moderating variable of liquidity risk
×
DFI funding management is 1.412 which shows that
MFI efficiency increases by 1.412 units with a 1 unit increase in the effect of DFI funding
management on the liquidity risk. The coefficient value for the liquidity risk of Pakistan
is
−
0.523 showing 1 unit increase in liquidity risk causes MFI efficiency to decrease by
0.523 units and the moderating variable of liquidity risk
×
DFI funding management has a
Economies 2023,11, 78 12 of 16
coefficient value of
−
0.272 showing a 1 unit increase in the effect of liquidity risk on DFI
funding management causes 0.272 unit decrease in MFI efficiency.
Table 7. MFI efficiency and Liquidity risk.
MFI Efficiency Bangladesh India Pakistan
Coeff. SE Coeff. SE Coeff. SE
Ln Liquidity Risk −0.296 0.349 0.917 0.625 −0.523 0.190
Ln Liquidity Risk ×DFIs Fund Manag −0.288 0.285 1.411 1.234 −0.273 0.071
_cons 0.221 0.140 −2.584 0.826 0.237 0.242
p > |t| 0.401 0.317 0.151 0.260 0.009 0.000
R20.025 0.051 0.109
Sigma_u 0.081 0.364 0.323
Sigma_e 0.107 1.093 0.367
Years Yes Yes Yes
5. Conclusions
The efficiency and sustainability of MFIs are dependent on the financial development
of the economy as a result of improvements in the quality of financial disclosures, creditor
rights protection, and the quality of financial institutions, which provide MFIs with a
competitive advantage in terms of timely loan repayment, increased poverty alleviation,
and continued provision of microloans, thereby expanding the financial reach of the MFIs
(Lensink et al. 2018).
According to the regression analysis, market risk stemming from unfavorable move-
ments in equity prices, interest rates, and FX rates has a detrimental influence on the
sustainability of MFIs. Bangladesh, Pakistan, and India are classified as EMDEs in need
of financial development to enhance the financial integration and inclusion essential for
economic success. Due to a growth in the debt-to-equity ratio, the influence of financial
development on market risk is detrimental to the sustainability of MFIs as suggested by
(Ayayi and Sene 2010).
The increase in the credit risk of MFIs causes a decrease in MFI sustainability, while
the increase in the effect of credit risk on MFIs’ lending strategy (Hossain and Khan 2016),
as measured by the operating expense ratio, also causes a decrease in MFI sustainability,
resulting in a debate over the optimal lending strategy for ensuring that subsidized credit
reaches eligible households. MFIs have relied mostly on group lending and village banking,
which include a formal agreement between a group of borrowers to borrow and repay
money as a single entity, hence reducing borrowing costs (Hermes et al. 2011). Effective
microfinance techniques for individual lending depend on allowing micro borrowers to
apply for a larger loan based on the repayment history of their existing loan and frequent
monthly installments, regardless of the return on investments that may be earned over
longer periods (Augsburg et al. 2015).
The influence of poverty alleviation on the efficiency of MFIs demonstrates that growth
in GNI per capita is positively correlated with the efficiency of MFIs as a result of an increase
in the proportion of an economy’s savings to its income, which raises the level of national
income per capita. The rise in financial outreach leads to a drop in MFI efficiency, which
can be ascribed to an increase in cost per borrower, as impoverished borrowers cannot
afford to pay a high-interest rate given their realistic business potential as consistent with
the study of Awaworyi Churchill (2020).
An increase in the liquidity risk of MFIs, as evaluated by the cash position indicator,
diminishes MFI efficiency in India and Bangladesh while increasing MFI efficiency in
Pakistan, hence boosting economic growth. The influence of liquidity risk on the DFI’s
funding management, as measured by the funding expense ratio, increases the MFI’s
efficiency in Pakistan and decreases the likelihood of insolvency. Unlike the previous
studies (Barr 2004;Hermes et al. 2011;Hossain and Khan 2016), the objective of the
current study is to not only comprehend the impact of financial development on the
Economies 2023,11, 78 13 of 16
efficiency and sustainability of MFIs but also to inform potential users about the impact
of the MFIs’ specific characteristics on these outcomes and point them in the direction of
beneficial outcomes.
Overall results are consistent with the findings of (Barr 2004;Hermes et al. 2011;
Hossain and Khan 2016
) and reveal that Indian MFIs relatively more efficient and sustain-
able due to the well-established financial markets but this effect is adversely affected MFIs
due to high market risk and low financial outreach. Whereas, in Bangladesh and Pakistan
MFIs efficiency are relatively lower than India but more sustainable in progress which
means that both countries are achieving good financial performance than India. Addi-
tionally, the moderate factor of risk exhibits the success of MFIs in Bangladesh more than
in Pakistan. In Pakistan MFIs’ efficiency and sustainably are subject to the constraints of
market risk, poverty alleviation, and liquidity risk.
The regularity authorities, responsible for the efficiency and sustainability of the MFIs
such as the Reserve Bank of India (RBI) for India, the Microcredit Regulatory Authority
(MRA) for Bangladesh, and the State Bank of Pakistan (SBP) for Pakistan, are the probable
users of this study. Hence, the findings of the study enlighten the ways to the competent
authorities for strengthening the MFIs leading to the economic progress of the country.
More precisely, this study advises RBI to create a policy to reduce market and credit risk
pressures on MFI sustainability, which may be accomplished by further enhancing the
lending strategy. The study recommends MRA develop a strategy to get over the MFIs’
limitations on financial outreach, market risk, and liquidity risk. Also, the study advises
MRA to take better financial development and lending practices into account if it wants
to reap favorable results consistently. Although MFI policies in Pakistan are effective at
reducing poverty and providing financial assistance, these effects do not appear to be
long-lasting. The study makes the recommendation that SBP alters the policies, particularly
through growing financial institutions and their financial growth mechanisms. As a result
of these enhanced financial developments, SBP would be able to manage the market, credit,
and liquidity risk by strengthening its lending strategy.
The research was conducted with the utmost effort in ensuring transparency and
accuracy involving the collection of data, analysis via the application of econometric
models, and the presentation of the statistical results notwithstanding the limitations due to
unavailability of resources along with difficulties in accessing the data regarding differences
in policy implementation across the selected countries along with tax regulations governing
the financial institutions. Furthermore, the heterogeneity in the corporate governance
mechanisms and the financial strength of the analyzed Micro Financial Institutions provided
another challenge to the reliability of the results.
The scope for future research should encompass a selection of the MFIs based on their
ranking in the financial sector of their respective economies, their corporate governance
mechanisms, and their legal status such as MFB, NBFCs, NGOs, etc. Furthermore, data
regarding the ease of policy implementation and stringent tax implementation should
guide further studies in the field investigating the adverse impact of financial development
on MFIs. There is also a need the distinguishing MFI-specific characteristics within the
selected MFIs for data collection to determine their effect on the efficiency and sustainability
of the MFIs.
Author Contributions:
All authors equally contributed to this study. All authors have read and
agreed to the published version of the manuscript.
Funding: This research was supported by Instituto Politécnico de Lisboa.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Informed consent was obtained from the respondents of the survey.
Data Availability Statement:
The data will be made available on request from the correspond-
ing author.
Acknowledgments: We thank Instituto Politécnico de Lisboa for providing funding for this study.
Economies 2023,11, 78 14 of 16
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Characteristics of Variables
Financial Development
Financial Development concerns the protection of creditor
rights, contract enforcement, reducing agency costs,
eliminating information asymmetry, and promoting
transparency and compliance with accounting standards.
MFI Efficiency
MFI efficiency relates to the financial inclusion of excluded
economic divisions, the expansion of the financial sector’s
reach, and the alleviation of poverty. An MFI’s inputs consist
of its equity, customer deposits, and interest on advances,
while its output is its after-tax net income.
MFI Sustainability
Financial viability is vital for MFIs to meet the credit needs of
excluded economic sectors without excessive reliance on
subsidies and cash. Thus, the sustainability of MFIs refers to
continuing repayments of loans by its borrowers, which is
why the MFI’s survival is not affected by questionable debts
and defaults.
Credit Risk
Credit risk is the borrower’s incapacity to meet its
commitments by the pre-decided terms, necessitating a focus
on lending principles and an evaluation of the borrowing
capacity of the borrower.
Market Risk
Market risk is the risk of loss owing to unpropitious
fluctuations in the market, and influenced factors, such as
interest rate and FX rate, resulting in an increase in the debt or
liabilities of MFIs as a result of an increase in market
interest rates.
Liquidity Risk
Liquidity risk is the probability of loss owing to a financial
institution’s inability to meet its obligations without incurring
unacceptable expenses, resulting in a loss of repute, loss of
faith between depositors, and nonpayment to creditors.
Poverty Alleviation
One of the key objectives of MFIs is the financial inclusion of
impoverished borrowers who are unable to provide adequate
collateral or have a valid legal status, as well as the supply of
credit to help development by reducing poverty.
Financial Outreach
Conventional financial service providers experience high costs
while attempting to bring services to far-flung rural areas with
low cash liquidity, seasonality of incomes, outdated
infrastructure, and little literacy rates, whereas MFIs aim to
provide micro-credit to the underprivileged by expanding the
financial sector’s reach.
Lending Strategy
The lending strategy of microfinance institutions (MFIs) plays
a key role in the institution’s continued survival, as its
primary objective is to alleviate poverty through the provision
of loans and other financial services to financially
excluded sectors.
DFIs’ Funds Management
MFIs have the same objective of financing economic growth
and development initiatives as DFIs, whose capital is derived
from resources provided by national or global organizations
to invest in private sector sustainable projects. Therefore,
MFIs that receive assistance from DFIs to support the
development of MSMEs should use these funds appropriately.
Economies 2023,11, 78 15 of 16
Notes
1https://datacatalog.worldbank.org/dataset/mix-market (accessed on 12 July 2022).
2https://data.worldbank.org/ (accessed on 12 July 2022).
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