Introducing a Theoretical Model for the Performance of Microfinance Firms

Introducing a Theoretical Model for the Performance of Microfinance Firms

Lakshmi Goel (Department of Management, Coggin College of Business, The University of North Florida, Jacksonville, FL, USA) and Oliver Schnusenberg (Department of Accounting and Finance, Coggin College of Business, The University of North Florida, Jacksonville, FL, USA)
Copyright: © 2014 |Pages: 16
DOI: 10.4018/ijabe.2014070101
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Abstract

Because borrowers sometimes take out additional loans in order to repay their earlier microfinance loans, microfinance loan repayment rates may be artificially inflated. The authors therefore propose a temporal socio-cultural model based on Hofstede's (1980) cultural dimensions, the diffusion of innovations, and the social network theory, that can be used to think about the performance of microfinance firms in general. The authors specifically apply this model to longitudinally assess the performance of SKS Microfinance, a microfinance firm in India. This approach adds a new dimension to understanding how to steer the industry away from some of the problems it has recently faced.
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Introduction

Microfinance lending programs are aimed at individuals to help them rise out of poverty, resulting in access to credit for low income groups that did not traditionally have such access (Brau & Woller, 2004). Ultimately, this should allow them to expand and diversify their economic activity and to become economically successful entrepreneurs (Davis, 2009). Thus, microfinance uses direct engagement with the poor and attempts to generate economic growth via market-driven business initiatives. Several researchers have documented that the majority of microfinance is aimed at the estimated 2.8 billion people who live on less than $2 per day (Khavul, 2010).

The recent growth of the field of microfinance is impressive. Reille and Glisovic-Mezieres (2009) report that there are about 100 private equity funds managing about $6.5 billion and channeling money to microfinance organizations. Recently, the number of for-profit microfinance organizations has increased (Battilana & Dorado, 2010). According to the International Monetary Fund (IMF), there were approximately 1,500 microfinance institutions functioning in 85 nations in Asia, Latin America, and Africa. These have about $18 billion of credit to over 54 million borrowers outstanding. This results in an average loan balance of about $500 per person.

The incredible growth and presence of microfinance in recent years has been confirmed by the United Nations’ declaration of 2005 as the International Year for Microcredit and the receipt of the Nobel Prize in 2006 by Muhammad Yunus of Grameen Bank.1 According to Richardson (2009), microfinance is now a mainstay of international finance, and Swibel (2007) comments on the increasing supply of microcredit around the world. Another author reports that the average individual microfinance debt in India has increased fivefold, from $27 in 2004 to $135 in 2009 (Khavul, 2010).

The growth and popularity of the microfinance industry also increase the riskiness of that industry, especially considering that there is still substantial room for growth. The OECD Observer (2011) reports that there are currently about 700 million micro-entrepreneurs, but only 190 million of them have access to microcredit. Recent experiences with the global financial crisis carry with them substantial fears of overinflated asset markets. Therefore, some authors (Gokhale, 2009; Khavul, 2010) have warned that there could be a microfinance lending bubble on the horizon, particularly since there may be a developing sense that microfinance organizations are “too big to fail.”2 This higher perceived risk has resulted in higher interest rates on microfinance loans. As a result, it is important to obtain a better sense of the risks that these microfinance institutions (henceforth MFIs) are subject to. Historically speaking, a primary measure of MFI performance has been loan repayment rates, which are very high for microfinance loans.3 However, because borrowers sometimes take out additional loans in order to repay their earlier loans, these rates may be artificially inflated.

While it would be extremely difficult to develop a methodology to attempt to predict default rates on microfinance loans, our goal is to develop a theoretical lens through which the microfinance industry can be viewed. In order to accomplish this, we propose a temporal socio-cultural model based on three theories - Hofstede’s cultural dimensions, diffusion of innovations, and the social network theory - that can be used to gain a better understanding of the microfinance industry and firms operating within that industry. We will then use this theoretical model to examine one firm, SKS Microfinance, more closely in order to better understand that firm’s development over time. A pure financial or economic analysis may not yield the insights that can come from the temporal socio-cultural approach.

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