CHAPTER 13: Poverty Monitoring and Evaluation
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Box 13.2 continued
Outcome
Eligible Program nonprogram households (D) households (C)
Current contraceptive use rate (currently married women, 14–50) Household weekly per capita consumption (taka)
Noneligible households (A U B U E)
All households
41.9
35.9
35.6
36.9
86.4
78.2
124.8
95.7
Source: Khandker 2000.
The problem with this comparison is that there is likely to be selection bias; it appears, for instance, that those who are eligible for microfinance but do not participate say that they are concerned about their ability to repay, suggesting that they are more risk averse, or perhaps less motivated, than borrowers. If landowning is exogenous, then one could compare the outcomes of households C and D on the one hand with households E on the other. This assumes, however, that program and nonprogram villages are the same. An even better approach would be to use a double difference, by comparing Y{C U D} – YA with YE – YB, where Y is the impact of interest (consumption or income per capita, school enrollment rates, and the like). Morduch (1998) used a similar approach and found that the microfinance programs appeared to improve the outcomes of interest. However, on further examination, he found that the programs were seriously mistargeted, with 20–30 percent of the borrowers owning more than the half-acre maximum. When these borrowers were excluded, the microfinance programs had essentially no discernible effects, except perhaps for lowering the variance of consumption and income for participants. On the other hand, it is possible that the comparison households may not have lacked access to microfinance, in which case Morduch’s conclusion would be unsurprising. A serious problem with Morduch’s simple difference-in-difference analysis is that program participation is exogenous or randomly given. Because of sample selection bias that is inherently present with such nonrandom distribution of borrowers and nonborrowers, Pitt and Khandker (1998) used an instrumental variable method to estimate the program effect. The instrument is based on the exogenous land-based eligibility conditions. They found that program participation matters a lot when sample selection bias is corrected. However, the results are sensitive to the assumption of the land-based exogenous eligibility condition. A follow-up panel survey was undertaken in 1998–99 to measure the effects of microfinance. Khandker (2005) estimated a number of regressions, using both instrumental variables and fixed effects (at the level of villages and households). A selection of results for
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