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Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 
2011, Vol. 2, No. 1, 172-178 

172 

 

Factors Determining the Operational Self-Sufficiency Among Microfinance Institutions 
 

Kai Schäfer, Midwestern State University 
Yoshi Fukasawa, Midwestern State University 
 

 

This paper is to determine factors best describing a microfinance institution’s (MFI’s) operational self-
sufficiency (OSS). The OSS is defined as the ratio of an MFI’s operating revenues to it operating 

expenses including the financial costs and impairment losses on loans. The outreach of an MFI, the write-
off ratio and regional differences are found significant in determining the OSS of MFIs. Surprisingly, 
neither an MFI’s depositors-to-borrowers ratio nor its deposits-to-loan portfolio ratio was found to be 

significant to explain an MFI’s OSS. There was no significant difference in the OSS in 2006 - before the 
worldwide financial crisis - and in 2008. 
 

 

One of the eight Millennium Development Goals of the United Nations is the “eradication of extreme 
poverty and hunger.” The UN defines extreme poverty as living on U.S. $1.25 or less per day. In 2005 1.4 
billion people worldwide were declared extremely poor. The UN’s target is to halve the proportion of the 
extreme poor by 2015 using the year 1990 as a basis. Microfinance is considered to be one of the 
measures that will help reach that goal (United Nations, 2008). The year 2005 was declared as the 
“International Year of Microfinance” (United Nations, 2004). 

Dr. Muhammad Yunus, the founder of the Bangladeshi Microfinance Institution (MFI) Grameen Bank, 
received together with his bank the Nobel Peace Prize in 2006 “for their efforts to create economic and 
social development from below” (Nobel Foundation, 2008). Grameen’s pioneering work made 
microfinance more and more popular worldwide.   
 The Microcredit Summit Campaign brings together microcredit practitioners, advocates, educational 
institutions, donor agencies, international financial institutions and non-governmental organizations 
(Microcredit Summit Campaign a, 2009). Since 1999 it has published annually The State of the 
Microcredit Summit Report. In its reports the organization compiles outreach data from MFIs all around 
the world (Microcredit Summit Campaign b, 2009). 

The 2009 report shows growth in the number of MFIs from 618 in 1997 to 3,552 in 2007. That is an 
increase of almost 500 percent over the ten-year period. The microfinance movement is not limited to 
developing countries; the report also mentions a total of 192 microfinance programs in developed 
countries in 2007 (Daley-Harris, 2009). In January 2008, for example, the Bangladeshi MFI Grameen 
Bank expanded its service from Bangladesh to a developed country by opening its first branch in the U.S. 
Surprisingly, Grameen America was established during the greatest financial crisis in modern history 
(Foroohar, 2010). 
 The main purpose of this paper is to examine the sustainability of MFIs worldwide by studying the 
factors that determine their operational self-sufficiency (OSS). The OSS rather than the financial self-
sufficiency (FSS) can easily be related to the standard profitability definition of revenues minus 
associated expenses. Furthermore, the OSS helps determine whether an MFI is able to cover all its costs 
that incur by doing business. OSS also allows getting a subjective and global picture of the institution in 
terms of its financial performance (Barres, 2006). The examination of the FSS requires such additional 
information as the inflation rate and the adjusted cost of capital, which are often not readily available for 
the developing countries included in this study. The year 2006 and 2008 are chosen to test if the recent 
worldwide recession had any significant impact on the OSS of MFIs. 

The microfinance sector differs mainly from other financial sectors in that microfinance addresses 
clients who are less financially rewarding or are not in conventional banks’ interest. MFIs serve poor 
populations which cannot post any collateral or other financial securities with microfinance services, such 
as small-sized loans, often $100 or even less, so called micro credits (Reno-Weber, 2008). The success of 



Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

173 

 

MFIs is based on their two main goals: the group-lending concept and teaching self-help to the poor, as 

pointed out by Robinson (2001)  

 The provision of financial services to the poor has gone through three distinct, but overlapping phases. 

In the first phase, the focus was on providing subsidies to the poor and was the dominating form in the 

1960’s. This form was mainly implemented by governmental agencies and the aim was to help farmers 

improve their productivity and achieve food security (CGAP, 2003). During the 1960s and 1970s the poor 

population was considered to be “unbankable” (Campion and White, 1999). Imboden (2005) describes the 

term “bankable” as individuals or enterprises being in a position to benefit from financial services. 

Generating income enables them to repay loans, to save or to build assets. Thus, “unbankable” refers to 

individuals or enterprises that are not in such a position.   

 In the early 1970s the first microfinance pioneers, such as the Bangladeshi Grameen Bank or ACCION 

International in Latin America, experimented with small loans given to poor women for small businesses. 

In the mid-1970s, NGOs took the role of giving credit to the poor and developed more innovative 

methods, such as group lending, to meet the requirements of the poor. This period is seen as the birth of 

microcredit. In the 1980s, an increasing number of MFIs improved their efficiency and were able to 

recover their costs and even attract deposits, commercial loans and investment capital (Helms, 2006). 

This was followed by the third phase in the mid-1990’s, when NGOs were transformed into commercial 

banks or formal financial institutions (Getu and Kempton). Rather than just granting micro credits, the 

range of financial services was extended to more comprehensive services, including savings and 

insurance (Helms, 2006).   
 

The SEEP Network (SEEP Network, 2005) defines an MFI’s OSS as percentage ratio as follows:  
 

OSS = (Operating Revenue) / (Operating Expenses + Financial Costs + Impairment Losses on Loans) 
 

The operating expenses include administrative and personnel expenses that are incurred by providing 

financial services while financial revenues represent the product of an MFI’s loan portfolio and the 

interest rates charged on loans. The OSS focuses on an MFI’s core business revenues and expenses. 

Financial expenses and impairment losses on loans are included in this calculation because they are 

normal and significant costs of microfinance operation. The OSS indicates also if an MFI is able to 

continue business without further external subsidies or not. This is the case when the OSS is above 100%. 

A ratio of 100% in OSS is also a break-even point for an MFI’s operation.  A ratio below 100%, however, 

indicates that the MFI is incurring losses. The SEEP Network found that start-up MFIs tend to have a 

lower OSS than mature MFIs, implying start-ups are less profitable. 
 

Model and Empirical Results 
 

 For the analysis of the model, the ordinary least squares regression method was used. The data sample 

used in this study was retrieved from the MIX and is based on the MIX Global Composite Ranking in 

2006 and 2008. The ranking contains factors such as efficiency, outreach, and financial performance. The 

ranking from 2008 includes data from 500 MFIs worldwide and is based on data from the financial year 

2008. The 2006 ranking is based on 500MFIs using the 2006 data. Overall the sample includes 1,000 

MFIs composed of 113 serving in Eastern Europe/Central Asia (ECA), 117 in Latin America/Caribbean 

(LAC), 27 in Middle East/North Africa (MENA), 59 in Sub-Saharan Africa (Africa), and 684 serving in 

the region of Southern and Eastern Asia (Asia).  
 

The model in this study is specified as follows: 
 

 !"!#0 $!#1X1 $!#2X2 $!#3X3 $!#4X4 $!#5X5 $!#6X6 $!#7X7 $!#8X8 $!#9X9 $!#10X10 + #11X11 $!#12X12 + 

#13X13 $!% 
 

 
 



Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

174 

 

Where: 

Y  = Operational self-sufficiency (OSS) of an MFI; 

X1 = Number of borrowers in 1,000s served by an MFI; 

X2 = Write-off ratio (%);  

X3 =  Depositors/borrowers ratio; 

X4 = Cost per borrower/GNI per capita ratio (%); 

X5 = Gross loan portfolio at risk > 30 days (%); 

X6 = Deposits/gross loan portfolio ratio; 

X7 = Market Penetration (%); 

X8 = Growth in borrowers (%); 

X9, X10, X11, X12 = Dummy variables for the region; and 

X13 = Dummy variable for the year. 
 

 With respect to the variable X1, it is expected that an MFI’s OSS is positively related to the number of 

borrowers served by the financial institution. With a greater number of borrowers, an MFI can experience 

economies of scale, reducing its average cost of operation by spreading overhead costs over a large 

number of borrowers, and ultimately increase its profit. A bigger case of borrowers also means a greater 

potential for larger revenue from interest earning, thus the expected sign for the coefficient being positive. 

 The write-off ratio (X2) represents the percentage of the gross loan written off. An increase in the 

write-off ratio means a greater loss of outstanding loans relative to an MFI’s loan portfolio, forgoing the 

chance to realize the loans’ revenues. The revenues from interests on the loans are not generated and 

therefore have a negative impact on an MFI’s OSS. The expected sign for the coefficient estimate is thus 

negative. 

 The variable X3 measures an MFI’s depositors- to-borrowers ratio. A higher depositors-to-borrowers 

ratio has a significantly positive effect on an MFI’s OSS. The higher the ratio, the greater the diversity in 

the funding sources for potential loans by the MFI, improving its OSS. 

 The variable X4 represents the ratio of the cost per borrower as a percentage of the gross national 

income (GNI) per capita. The cost per borrower is defined as the operating expenses divided by an MFI’s 

average number of borrowers. The lower cost per borrower relative to the country’s per GNI implies that 

an MFI is more efficient to reduce the borrowing cost compared to the per-capita income of potential 

borrowers. A loser cost structure through the economies of scale, for example, gives the MFI a 

comparative advantage and can lead to a higher profit. Therefore, MFIs with a lower ratio have a higher 

OSS, leading to a negative sign for the coefficient. 

 The gross loan portfolio at risk > 30 days (X5) is the value of all loans outstanding that have one or 

more installments of principal past due longer than 30 days. This includes the entire unpaid principal 

balance including both the past due and future installments but not accrued interest. It also includes loans 

that have been restructured, rescheduled, or renegotiated. The greater is the portfolio at risk, the greater is 

the potential for a loss in revenue, lowering the OSS of an MFI. The expected sign for the coefficient is 

negative. 

 The variable X6 represents the ratio of deposits to gross loan portfolio of an MFI. It is hypothesized 

that a higher deposit to loan portfolio ratio leads to a lower OSS, because a higher amount of deposits to 

loan portfolio reduces the opportunity to make revenues through interest earnings on loans, giving the 

negative sign for the coefficient. 

 Market penetration, the variable X7, measures the outreach of borrowers relative to the potential 

market and how many clients are actually served compared to an MFI’s potential market. The potential 

market is the number of people living below the national poverty level in which the MFI is operating. The 

great is market penetration, the greater the revenue, and the higher the OSS. The expected sign for the 

coefficient is positive. 

 The variable X8 measures growth in borrows in percentage. An MFI that has strong growth in the 

number of borrowers is able to serve more clients. A larger customer base triggers a positive economy-of-



Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

175 

 

scale effect, leading to lower operating costs. A reduction in costs per borrower helps raise the overall 

OSS of an MFI, thus the coefficient is expected to be positive. 

 The variables X9, X10, X11, and X12 are dummy variable for the region of the examined MFIs, 

representing ECA (X9), LAC (X10), MENA (X11), and Africa (X12). The benchmark in this model is the 

region of Asia.  It is hypothesized that there are regional differences in MFI’s OSS. MFIs in Asia have the 

longest experience in microfinance and therefore have an advantage of economies of scale and economies 

of scope. 

 The variable X13 is the dummy variable for the year of retrieving data. The benchmark for this model 

is the year 2006. It is expected that MFIs in 2008 would have a lower operational self-sufficiency than in 

2006, because of the worldwide recession beginning in December 2007 in the U.S. MFIs, as any other 

financial intermediaries, would have suffered during the financial and economic crisis that reached its 

peak in 2008. It is expected that MFIs were less profitable in 2008 than in 2006. 

 The results of the ordinary least squares regression is shown in Table 1. The overall fit of the model is 

relatively weak with the adjusted R2
 of 0.025. The F-statistic is highly significant at 0.0003, implying that 

the independent variables are important as factors determining the OSS. Among the independent variables, 

the number of borrowers (X1), the write-off ratio (X2), the depositors/borrowers ratio (X3), the gross loan 

portfolio at risk > 30 days (X5), and the deposits/gross loan portfolio ratio (X6) show the expected signs 

and the first three variables are significant at 0.05 level. 
 

Table 1: Regression Results 
 

 
Regression Statistics 

_____________________________ 

 
Multiple R    0.1937 

R Square    0.0375 

Adjusted R Square  0.0248 
Standard Error   30.5958 

Observations    1000 
_____________________________ 
 

ANOVA 

_______________________________________________________________________________________ 
 

Df   SS     MS          F    Significance F 

 
Regression  13     35988.1738   2768.3211   2.9573   0.0003 

 

Residual     986   923000.2012   936.1057 
 

Total   999     958988.3750 
_____________________________________________________________________________________ 

           

Coefficient  Standard Error t-Stat  P-value 

 
Intercept                      124.5751     2.8756   43.3220  0.0000 

Number of Borrowers                          0.0077      0.0028     2.7465  0.0061 

Write-Off Ratio (%)                     -1.7560     0.5802    -3.0264  0.0025 
Depositors/Borrowers Ratio          1.3711      1.1013     1.2450  0.2134 

Cost per Borrower/DNP per capita (%)        0.0233      0.0264    0.8799  0.3791 

Gross Loan Portfolio at Risk > 30 days (%)      -0.3432      0.2197    -1.5621  0.1186 
Deposits/Gross Loan Portfolio Ratio   -4.1064      3.3006    -1.2441  0.2137 

Market Penetration (%)      -0.0657      0.4898    -0.1341  0.8934 

Growth in Borrowers (%)      -0.0020      0.0043    -0.4621  0.6441 
ECA          10.4915      4.0147     2.6133  0.0091 

LAC          3.6935      3.5605     1.0373  0.2998 

MENA          17.0084      6.4757     2.6265  0.0088 
Africa          5.2535      4.7935     1.0960  0.2734 

Year of Retrieving Data      3.3442      2.9859     1.1200  0.2630 

 

 



Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

176 

 

First, the outreach measured in the number of borrowers of an MFI was found to be important factor 

determining the sustainability of an MFI. As other research had already found in the past and was 

hypothesized in this model, an MFI that is able to expand its outreach and serve more customers with 

micro finance intermediation has a higher financial stability and OSS. It can make use of both economies 

of scale and economies of scope by serving a greater number of borrowers. The write-off ratio that 

represents uncollectable loans relative to an MFI’s gross loan portfolio was also found significant in the 

model. As it reduces the gross loan portfolio, it reduces the ability to earn interest on the loan and reduces 

an MFI’s revenue. In turn, less revenue, ceteris paribus, eventually reduces an MFI’s OSS. Surprisingly, 

neither the balance between an MFI’s deposit and lending mobilization (depositors/borrowers ratio) nor 

the same ratio in terms of assets (deposits/gross loan portfolio) was found to be significant to explain an 

MFI’s OSS. As expected, there are regional differences in the OSS. The OSS of MFIs in the ECA and 

MENA regions were found to be significantly higher than in the benchmark Asian region.  

The most surprising discovery was that there was no significant difference in the OSS from MFIs 

reporting in 2006, before the worldwide financial crisis, and those reporting in 2008. 

It was expected that the microfinance sector was impacted by the crisis as was the rest of the global 

finances. The coefficient estimate for the year X13, although insignificant, implies that the OSS for MFIs 

was higher in 2008 than in 2006, despite the fact that the industrialized economies entered recession 

beginning December 2007. In addition, the market penetration was not a significant factor. It is thus 

concluded that market power did not have a significant influence on a MFI’s OSS in the model. 
 

Conclusions 

 

This paper examined the factors best describing an MFI’s OSS. The examination of those factors is 

important to help understand the sustainability, and the survival, of MFIs that serve a vital role in 

economic development of many less-developed countries. 

 The number of borrowers, the write-off ratio, and the depositors/borrowers ratio were found to be 

important factors determining the sustainability of an MFI. The MFIs in the Eastern Europe/Central Asia 

exhibited the better operational self-sufficiency than those in the benchmark region, Asia. There was no 

evidence to support that significant deterioration in the sustainability of MFIs occurred due to the 2007-

2009 recession. 

 In the future, the model can be modified to attain a more comprehensive picture of an MFI’s overall 

performance. Additional variables such as the lending mechanism (group lending vs. individual lending) 

that is used by an MFI or the type of an MFI (NGO, bank etc.) could be included since the revenue and 

cost structure may differ. Since the model in this paper focuses on the determinants of the OSS, it does 

not reveal the causes of variables being (in) significant. 

The following questions would be interesting to answer: Why are there regional difference in the 

OSS? Is it because of the cost structure, the average loan amount, the level of interest rates, or even the 

clients’ characteristics? Why does neither the client (depositors/borrowers ratio) nor the asset 

(deposits/gross loan portfolio ratio) structure impact an MFI’s OSS, even though an MFI generates its 

revenues from interest rates on loans and public deposits? Furthermore, why the recent worldwide 

financial crisis and economic downturn had no significant impact on the OSS in the model? Is it because 

crisis like this have a delayed effect on the microfinance sector and therefore not yet found significant? Or 

is it because the microfinance sector is more resilient to crisis? If it is found in the future that the crisis 

actually has affected MFIs’ profitability, operational sustainability, or the ability to grant loans, how will 

they provide service to the poor? 

 As mentioned, OSS is a good measure of the financial sustainability of an MFI, but as any other 

measure of financial performance, it does not assess the social benefit to a single client, a community, or 

even a whole country in terms of increasing welfare or reducing poverty. Financial performance and 

sustainability in the microfinance sector has become increasingly important to attract socially responsible 

investors. But, at the same time MFIs must achieve their fundamental goal of reducing poverty by helping 

to build inclusive financial sector and by giving the poor access to financial intermediation. Both goals, 



Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

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being financially sustainable and achieving the social objective, have to be considered. A promising 

future of the microfinance sector and its providers (MFIs) will only be possible if both goals are realized. 

Only then will it be possible to achieve the Millennium Development Goal of the United Nations to 

“eradicate extreme poverty and hunger” by the use of microfinance. 
 

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Schäfer and Fukasawa                                                                                                                                                   Advances in Business Research 

2011, Vol. 2, No. 1, 172-178 

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Barres, I., Bruett, T., Curran, L., Escalona, A., Nelson, E., & Norell, P. 2005. Measuring performance of 

microfinance institutions - A framework for reporting, analysis, and monitoring. Washington, D.C.: 

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Kai Schäfer received his MBA from Midwestern State University in 2010 while simultaneously earned a 

Masters degree in environmental business administration from University of Applied Sciences Trier in 

Germany. He works for a business consulting firm in the field of energy and public services in Germany. 

He has published in Journal of Managerial Issues. 
 

Yoshi Fukasawa is professor of economics at Midwestern State University in Wichita Falls, Texas. He 

received his Ph.D. in economics from Kansas State University. His research interest includes international 

economics and the Texas economy. He has published in Journal of Business and Leadership, 

Southwestern Journal of Economics, and Texas Business Review. 

 

 


