ABSTRACT
The rapid expansion of microcredit in recent years renders knowledge of its impact on poverty critical. Unfortunately, empirical investigations have been limited by endogeneity issues, and randomized controlled trials suffer from a lack of power. This article suggests a strategy for handling the endogeneity of microcredit borrowing without specifying instrumental variables, allowing for estimation using observational data. The model is identified by an assumption on the conditional second moments of the errors and estimated semiparametrically. I find that an increase in the amount borrowed from the Grameen Bank and similar institutions in Bangladesh has a positive and significant effect on per-capita household consumption. The estimated elasticity is in the range of 0.18 to 0.21. These estimates indicate that microcredit may be more effective than previously thought.
Acknowledgement
I thank Francis Vella for invaluable advice and guidance; Roger Klein, Garance Genicot and Shahe Emran for helpful comments; and participants at the Association for Economic and Development Studies on Bangladesh (AEDSB).
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1 See Ravallion (1992) for a discussion of consumption as a measure of poverty
2 Another example of a quasi-experimental design is Coleman (Citation1999), who identifies the average effect of a programme in Thailand by exploiting the fact that some households that had selected into borrowing groups had not yet received their loans. He does not find a significant average effect of treatment status on household income but notes that the population in Thailand is wealthier than that of countries such as Bangladesh, and access to other sources of credit is more widespread.
3 Other examples of identification by heteroscedasticity are estimators developed by Rigobon (Citation2003) and Lewbel (Citation2012), which have been applied by Emran and Hou (Citation2013), Emran and Shilpi (Citation2012), Gilchrist and Zakrajsek (Citation2013), and Rigobon and Rodrik (Citation2005).
4 While it would be desirable to isolate the effects of borrowing in different years, borrowing from year to year is too highly correlated to be able to make any definitive statements about each year separately.
5 This equation could also be estimated under these assumptions using the symmetrically trimmed least-squares estimator of Powell (Citation1986), without requiring the heteroscedasticity to be a function of the index. Using this technique resulted in a severe loss of precision, however, due to the amount of data that is thrown out by trimming the positive observations.