column 1 show that the coefficient of ‘new’ membership in MFIs has a negative sign and is statistically significant at the 1 percent level regardless of the ways comparison groups are defined. The magnitude of the coefficient is larger when drop-outs are taken as the comparison group compared with the case where “never members” are the comparison group. These DID-FE estimates suggest a significant decline (0.040.06) in the propensity to borrow from informal sources by the new MFI members.

To check the sensitivity of the DID-FE estimates when we allow for time-varying effects of household and region characteristics, we estimate the specification in equation (6). Column (2) reports the results when household characteristics in 2000 are added and column (3) when both household and region characteristics in 2000 are included as explanatory variables. The household level variables included are log of household head’s age, a dummy indicating whether the head has above primary level education, total owned and total cultivable land, number of household members self-employed in agriculture, and household size. To control for region-specific effect, we include a dummy indicating the poorer region in the country (three divisions in the north-west and south). We perform t-tests of differences in means of these characteristics between treatment group and different comparison groups. The results (not reported here) indicate that ‘never member’ comparison group consists of households whose head are older and which are more agricultural (more land, more members employed in agriculture). There is no significant difference in education, household size or religion between these two groups. In the case of ‘drop-out’ comparison group, there is statistically significant difference in mean only for household head’s age and to some extent for the number of members self-employed in agriculture. If household-level heterogeneity has time-varying effects, then one would expect DID-FE estimates to change significantly when household level controls (pretreatment) are added to the regression. The estimates in column (2) show a slight increase in the magnitude of the treatment coefficients for “never member” and “both drop-out and never member” comparison groups, and a slight decline for “drop-out” comparison group. We find changes in the same directions when region dummy is added in the set of controls (column (3)). However, none of the estimates are statistically or numerically significantly different from those reported in column 1. This can be interpreted as suggestive evidence that probably the most important sources of selection bias in our application are in fact time-invariant.

To probe the issue of time-varying omitted variables bias in more depth, we report estimates that combine the DID-FE with two alternative matching estimators. The results from the MDID-FE estimator suggested by Heckman et al (1998) are reported in column (4) of Table 4. Matching is done using pretreatment (in other words 2000 survey) household and region characteristics discussed earlier.<sup>31</sup> The estimate in the case of drop-out control (column (4), middle panel) is slightly smaller in absolute

> 31 We emphasize here that the central conclusions of this paper do not depend on the exact set of variables used as controls or for matching.

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