Performance of microfinance institutions in achieving the poverty outreach and financial sustainability: When age and size matter?

Using a two-stage DEA bootstrapped metafrontier approach, we investigate the effects of age and size on efficiency estimates of microfinance institutions (MFIs). In the first-stage, we use a metafrontier model combining with DEA bootstrapped procedure to obtain statistically robust and comparable efficiencies. In the second-stage, we employ a bootstrapped truncated regression to account for the impact of exogenous factors on both dimensions of efficiency. Results highlight the importance of model specification for MFIs operating in different geographical regions. Moreover, we find that although older MFIs perform better than younger ones in terms of achieving financial results, they are relatively inefficient in achieving outreach objectives. We also document that MFI size matters: larger MFIs tend to have higher financial and outreach efficiency

Essays in efficiency and productivity analysis of microfinance institutions

This dissertation consists of three essays, each exploring MFIs’ efficiency and productivity dynamics in presence of environment impacts. The first essay examines technical efficiency and its determinants of 36 microfinance institutions in Sri Lanka using a two-stage double bootstrap approach. Efficiency levels are explored in terms of MFIs’ dual objectives of financial sustainability and outreach. In the first stage, a bootstrap Data Envelopment Analysis (DEA) procedure is used to correct the bias and construct confidential intervals for the efficiency estimates. Then in the second stage, bias-corrected efficiency estimates are regressed on a set of environmental variables using a bootstrap regression approach. The results of the first stage analysis confirm the existence of financial and social inefficiency for the majority of MFIs in Sri Lanka. The second stage analysis suggests that such inefficiency is determined by a number of MFI characteristics such as its age, its organizational type (i.e. run as an Non-governmental Organization or not), its capitalization level, and its profitability. The second essay uses a non-parametric Malmquist method to investigate the changes in productivity of 20 Kenyan microfinance institutions over the period 2009-2012. Productivity change is decomposed into indices of technological change, pure efficiency change and scale efficiency change. A bootstrap procedure is employed to construct confidence intervals for the Malmquist indices. This procedure makes it possible to investigate whether such changes are significant in a statistical sense. Additionally, a second-stage bootstrap procedure is employed to ascertain the sources of productivity change measures. Results show that productivity growths are primarily attributable to technical improvements at an average of 7%. Moreover, second stage results suggest that matured MFIs tend to have a lower productivity compared to the younger counterparts. In the third essay, focus is shifted to investigate the relationship between efficiency and corporate governance in MFIs. Using a two-stage bootstrap procedure for a sample of 36 Sri Lankan MFIs, it explores the effect of several governance models (i.e. board size, proportion of women on the board, duality and presence/ absence of a female chief executive officer) on sustainability and outreach dimensions of efficiency estimates. Results suggest that financial efficiency improves with a small board and higher proportion of women on the board. Results also show that MFIs in which the same individual holds CEO and chairman of the board and MFIs in which a woman holds the position of CEO are less efficient in terms of reaching the lower strata of the rural poor

Does ownership structure affect firm performance? Evidence of Indian bank efficiency before and after the Global Financial Crisis

This paper investigates the relationship between bank ownership and efficiency before and after the 2008–2009 Global Financial Crisis. Using a sample of 58 Indian commercial banks from 2005 to 2017, we examine the interconnection between these factors in a dynamic data envelopment analysis (DEA) framework. We use an innovative modeling strategy based on a two-stage dynamic DEA framework. The first stage employs the Dynamic Slack-Based Measure model to measure bank efficiency, explicitly considering the effects of desirable and undesirable carry-overs between consecutive periods. In a second stage, we perform a regression of the efficiency scores on bank ownership types and several other contextual factors, while also accounting for the presence of endogenous relationships between the variables involved. Our results show that foreign banks outperform their domestic competitors, with bank size and profitability being the main drivers. We also find that while foreign and state-owned banks were more efficient than their rivals during the Global Financial Crisis, private banks recovered quickly, reaching the efficiency standards of state-owned banks by 2017. The latter faced a prolonged decrease in efficiency, gradually losing their initial advantage over their private domestic counterparts. Our results are robust to alternative regression specifications, especially those aimed at addressing potential endogeneity issues. The applied methodology and the findings of our research should be of interest to scholars, bank managers, and policymakers. The latter, in particular, should be concerned about the medium-term effects of reforms that unevenly affect banks with different ownership structures, especially in terms of bank resilience to aggregate shocks

Financial inclusion, deepening and efficiency in microfinance programs: evidence from Bangladesh

The economic literature provides evidence that growth is associated with positive performance of the financial sector. This aspect is particularly important for developing countries. This study aims to investigate whether, in an environment of growing competition and regulation, the maintenance of their social mission may have led microfinance institutions (MFIs) to compromise their performance, in terms of efficient production of credit services. To this purpose, we use a two-stage approach to analyze the relationship between outreach and efficiency of MFIs in Bangladesh. In the first stage, a dynamic data envelopment analysis is exploited to measure the efficiency of MFIs from 2009 to 2014. The results show that most of the MFIs are operationally inefficient over the period, suggesting a considerable potential for future improvement. In the second stage, the study examines the potential trade-off between MFIs’ commitment to financial inclusion and depth of outreach on the one hand and efficiency on the other hand, using a double bootstrapping methodology that helps in limiting the problems arising from the endogenous nature of the measures of outreach with respect to efficiency. The results show that financial inclusion is positively associated with MFIs’ efficiency, whereas the relationship between deepening and efficiency turns up negative, providing partial evidence in support of ‘mission drift’ in the Bangladesh microfinance industry. This may be indicative of the fact that MFIs with stronger commercial objectives have expanded their business and their margins of efficiency to compete with other intermediaries. In contrast, the MFIs with a more intense social strategy may have suffered a decrease in their operating efficiency in order to maintain their social mission. Policy implications point towards a greater degree of awareness on the part of the regulatory authorities of the consequences of imposing constraints on the operating mechanisms of the microfinance industry, such as interest rate caps. We also suggest that rules disciplining competition should not be uniform, but rather tailored to specific outreach indicators

Productivity change of microfinance institutions in Kenya: a bootstrap Malmquist approach

This paper uses a DEA (Data Envelopment Analysis) based Malmquist approach to investigate the changes in productivity of 20 Kenyan microfinance institutions (MFIs) over the period 2009-2012. A bootstrap procedure is employed to determine whether the changes in Malmquist index and its components are statistically significant. Results show that MFIs have experienced about 7% annual productivity progress on average, which is mainly attributable to technological advances. A second-stage bootstrapped regression analysis is employed to examine the impact of several environmental variables on productivity change measures. Results show that matured MFIs tend to have a lower productivity compared to their younger counterparts. Results also reveal that higher return-on-assets associates with the productivity gain and technological improvements

Financial and social sustainability in the European microfinance sector

This paper investigates the balance between social and fnancial sustainability goals in the European microfnance sector using an original dataset obtained from a survey conducted in 2016–2017 on 159 microfnance institutions (MFIs) operating in 38 European countries. Overall, our results show that MFIs that are more likely to comply with their social sustainability objectives are also doing well fnancially. The only aspect on which social sustainability does not seem to have a positive efect on fnancial sustainability is the fnancing of the poorest through the provision of small-scale loans. A phenomenon that seems peculiar to the European context is that larger MFIs operating in countries with stringent fnancial regulation tend to show a comparative advantage and better withstand competition from the traditional banking sector. However, a separate issue that deserves attention is the specifc regulation on interest rates, which seems to penalize the MFIs operating in countries imposing interest rate caps due to the impossibility to pass on the high unit costs of microlending to borrowers. Our results are robust to alternative measures of fnancial sustainability and to the use of the Generalized Method of Moments (GMM) and Instrumental Variable (IV) estimation techniques to overcome the problem of endogeneity