Microfinance institutions which specialize on the provision of financial services to low-income clients and micro-entrepreneurs have grown significantly in recent years. Lützenkirchen and Weistroffer (2012) highlight that MFIs had extended loans to more than 200 million clients by the end of 2010, whereas through various socio-economic ties of the borrowers and their families, microfinance has influenced the lives of around 1 billion people in emerging and developing countries. Another particular characteristic of the MFIs’ borrowers is that they usually lack credit history and collateral which limits their access to financing from traditional commercial banks (Banerjee and Duflo, 2007). Therefore, it is not surprising that MFIs have attracted considerable attention by academics and policy makers, with recent studies focusing on a variety of topics like the impact of microfinance on poverty or child health outcomes (Imai et al., 2012; DeLoach and Lamanna, 2011), competition between microfinance non-governmental organizations (Ly and Mason, 2012), microfinance and female empowerment (Ngo and Wahhaj, 2012), the use of credit scoring models from MFIs (Blanco et al., 2013; Cubiles-De-La-Vega et al., 2013), the diversification benefits from adding microfinance funds to a portfolio of risky international assets (Galema et al., 2011), the drivers of buffer capital (Tchuigoua, 2016), and the determinants of governance quality (Tchuigoua, 2015).
The aim of the present study is twofold. The first aim is to provide an overall measure of the performance of MFIs. As discussed in Devinney et al. (2010), the performance of firms is of central interest to managers, researchers and policy makers; however, there is little convergence of opinion on how performance should be measured. To this end, Devinney et al. (2010) argue in favour of an overall measure of performance. This becomes even more crucial in the case of MFIs, due to the double challenge that they face. More detailed, MFIs not only have to provide financial services to the poor (outreach), but they also have to cover their costs to avoid bankruptcy (sustainability). Furthermore, as mentioned in von Stauffenberg et al. (2003) all performance indicators tend to be of limited value when examined in isolation and this is particularly the case for the profitability indicators of MFIs. They also highlight that to understand how an institution achieves its profits the analysis must also take into account other indicators that influence the operational performance of the institution, such as operational efficiency and portfolio quality. Finally, the profitability analysis is further complicated by the fact that a significant number of MFIs receive grants and subsidized loans.
Therefore, ideally various dimensions should be taken simultaneously into account in the assessment of their performance. Nonetheless, as discussed in Weber and Luzzi (2007) very few attempts have been made to aggregate the numerous indicators of MFI’s performance into a single measure and most of the studies simply compare the financial condition of MFIs on the basis of univariate tests of individual ratios such as the return on assets (e.g. Bi and Pandey, 2011; Agarwal and Sinha, 2010). Zeller et al. (2003) propose the construction of an overall measure; however, their suggestions are limited to the assignment of arbitrary weights to the indicators or the derivation of weights through principal components analysis (e.g. Weber and Luzzi, 2007). A few recent papers also estimate the efficiency and/or productivity of MFIs using frontier techniques (e.g. Servin et al., 2012; Wijesiri et al., 2015; Wijesiri and Meoli, 2015), which provide an overall score. However, the majority of these studies tend to measure how efficient the MFIs are in transforming inputs (e.g. number of credit officers, total assets) to outputs (e.g. financial revenue), while ignoring other aspects like portfolio risk and capital strength. In this paper, I follow a different approach, and I propose the use of the PROMETHEE II multicriteria method that summarizes both the financial and social performance of MFIs in a single score of relative performance on the basis of pairwise comparisons across a set of often conflicting criteria.
The second aim of the present study is to explain differences in the overall performance indicator, obtained from the PROMETHEE II method, on the basis of firm-specific and country-specific attributes. The investigation of the determinants of performance has attracted the interest of researchers from the fields of international business, strategic management, and finance (e.g. McGahan and Porter, 2002; Joh, 2003; Short et al., 2007; McGahan and Victer, 2010). However, MFIs are considerably under-research compared to non-financial firms and traditional banking institutions. The few existing studies examine the impact of firm-level attributes such as corporate governance and legal status (Hartarska, 2005; Mersland and Strøm, 2009; Tchakoute-Tchuigoua, 2010) or country-level characteristics such as regulations, macroeconomics, and institutional development (Cull et al., 2011; Ahlin et al., 2011) on single indicators of the profitability and growth of MFIs.