Smoke and mirrors: evidence of microfinance impact from an evaluation of SEWA bank in India

Microfinance has been on the development agenda for more than 30 years, heralded as the wondrous tool that reduces poverty and empowers women (Hulme and Mosley, 1996; Rutherford, 2001; Morduch and Haley, 2002; Khandker, 1998). Doubts, however, have recently been raised about the success of microfinance (Dichter and Harper, 2007; Banerjee et al, 2009; Roodman and Morduch, 2009; Karlan and Zinman, 2009; Bateman and Chang, 2009). Given this context, this paper re-examines the microfinance impact evaluation of SEWA Bank conducted by the United States Agency for International Development (USAID) in India in 1998 and 2000. The USAID panel and a new cross-section data set are analysed using propensity score matching (PSM) and panel data techniques to address selection bias. Sensitivity analysis of the matching results is used to explore their reliability. Various sub-group comparisons between borrowers, savers and controls are also conducted to shed some light on the impact of savings versus credit. The paper concludes that doubts remain about the quality of the impact estimates obtained through advanced econometric techniques. Direct observation and the outcome of sensitivity analysis of the PSM analysis suggest that the application of PSM and differences-in-differences (DID) to these observational data were probably unable to account for selection on unobservables

High Noon for Microfinance Impact Evaluations: Re-investigating the Evidence from Bangladesh

Recently, microfinance has come under increasing criticism raising questions of the validity of iconic studies which have justified the microfinance phenomenon. This paper applies propensity score matching (PSM), which has become widely used for the analysis of observational data, to the study by Pitt and Khandker (1998) which has been labelled the most rigorous evidence supporting claims that microfinance benefits the poorest especially when targeted on women. After carefully reconstructing the data we differentiate outcomes by gender of borrower, take account of borrowing from several formal and informal sources, and find that the mainly positive impacts of microfinance that we observe are shown by sensitivity analysis to be highly vulnerable to selection on unobservables, and we are therefore not convinced that the relationships between microfinance and outcomes are causal.Microfinance; impact evaluation; Bangladesh; propensity score matching; sensitivity analysis

Smoke and Mirrors: Evidence of Microfinance Impact from an Evaluation of SEWA Bank in India

Microfinance has been on the development agenda for more than 30 years, heralded as the wondrous tool that reduces poverty and empowers women (Hulme and Mosley, 1996; Rutherford, 2001; Morduch and Haley, 2002; Khandker, 1998). Doubts, however, have recently been raised about the success of microfinance (Dichter and Harper, 2007; Banerjee et al, 2009; Roodman and Morduch, 2009; Karlan and Zinman, 2009; Bateman and Chang, 2009). Given this context, this paper re-examines the microfinance impact evaluation of SEWA Bank conducted by the United States Agency for International Development (USAID) in India in 1998 and 2000. The USAID panel and a new cross-section data set are analysed using propensity score matching (PSM) and panel data techniques to address selection bias. Sensitivity analysis of the matching results is used to explore their reliability. Various sub-group comparisons between borrowers, savers and controls are also conducted to shed some light on the impact of savings versus credit. The paper concludes that doubts remain about the quality of the impact estimates obtained through advanced econometric techniques. Direct observation and the outcome of sensitivity analysis of the PSM analysis suggest that the application of PSM and differences-in-differences (DID) to these observational data were probably unable to account for selection on unobservables.Impact evaluation, evaluation methods, selection bias, microfinance, India

What Is Meant by “Replication” and Why Does It Encounter Resistance in Economics?

This paper discusses recent trends in the use of replications in economics. We include the results of recent replication studies that have attempted to identify replication rates within the discipline. These studies generally find that replication rates are relatively low. We then consider obstacles to undertaking replication studies and highlight replication initiatives in psychology and political science, behind which economics appears to lag

Responding to the Multi-Faceted COVID-19 Crisis: The Case of Mumbai, India

COVID-19 has severely impacted the society not only in terms of health but also in terms of economic survival of individuals. Unless adequate support is provided, the pandemic will have long-lasting effects, especially on the lives of the most vulnerable, often working in the informal sector. In this article, we present a case study drawing on systems thinking and complexity theory, outlining how the city of Mumbai has responded to COVID-19. We find a multifaceted scenario where non-profit organizations, businesses and citizen volunteers operate alongside government bodies to support Mumbai’s population to overcome this pandemic. We provide broader policy lessons, as well as more specific lessons in relation to particular actors, from the first wave of the pandemic stressing the importance of becoming ‘systems thinkers’ and highlighting the importance of forming new partnerships and exploring new modes of knowledge sharing to effectively respond to crises

What Is Meant by “Replication” and Why Does It Encounter Resistance in Economics?

This paper discusses recent trends in the use of replications in economics. We include the results of recent replication studies that have attempted to identify replication rates within the discipline. These studies generally find that replication rates are relatively low. We then consider obstacles to undertaking replication studies and highlight replication initiatives in psychology and political science, behind which economics appears to lag

What is the evidence of the impact of microfinance on the well-being of poor people?

The concept of microcredit was first introduced in Bangladesh by Nobel Peace Prize winner Muhammad Yunus. Professor Yunus started Grameen Bank (GB) more than 30 years ago with the aim of reducing poverty by providing small loans to the country’s rural poor (Yunus 1999). Microcredit has evolved over the years and does not only provide credit to the poor, but also now spans a myriad of other services including savings, insurance, remittances and non-financial services such as financial literacy training and skills development programmes; microcredit is now referred to as microfinance (Armendáriz de Aghion and Morduch 2005, 2010). A key feature of microfinance has been the targeting of women on the grounds that, compared to men, they perform better as clients of microfinance institutions and that their participation has more desirable development outcomes (Pitt and Khandker 1998). Despite the apparent success and popularity of microfinance, no clear evidence yet exists that microfinance programmes have positive impacts (Armendáriz de Aghion and Morduch 2005, 2010; and many others). There have been four major reviews examining impacts of microfinance (Sebstad and Chen, 1996; Gaile and Foster 1996, Goldberg 2005, Odell 2010, see also Orso 2011). These reviews concluded that, while anecdotes and other inspiring stories (such as Todd 1996) purported to show that microfinance can make a real difference in the lives of those served, rigorous quantitative evidence on the nature, magnitude and balance of microfinance impact is still scarce and inconclusive (Armendáriz de Aghion and Morduch 2005, 2010). Overall, it is widely acknowledged that no well-known study robustly shows any strong impacts of microfinance (Armendáriz de Aghion and Morduch 2005, p199-230). Because of the growth of the microfinance industry and the attention the sector has received from policy makers, donors and private investors in recent years, existing microfinance impact evaluations need to be re-investigated; the robustness of claims that microfinance successfully alleviates poverty and empowers women must be scrutinised more carefully. Hence, this review revisits the evidence of microfinance evaluations focusing on the technical challenges of conducting rigorous microfinance impact evaluations