columns (3) and (4) in Table 3. The OLS and KV estimates contradict each other, and both the estimates are not significant at the 10 percent level. The second comparison group consists of the first and second quartiles, implying that the comparison group is same as that in the empirical analysis reported earlier in Tables 1 and 2. The OLS and KV estimates are reported in columns (5) and (6) in Table 3 respectively. The diagnostic test shows that heteroskedasticity in the residuals of the treatment equation is not strong, which leads to low explanatory power of the instrument (the Angrist-Pischke F is 8.29, much lower than the ones reported in Tables (1) and (2). It is also smaller than the rule of thumb cut-off 10). This raises concerns that the estimates from this specification may not be reliable. To avoid weak instrument bias, we thus report results from an alternative specification that includes the full set of control variables as sources of heteroskedasticity; the estimation results are reported in column (7). The LR test of the null of homoskedastcity in this case is rejected resoundingly, and the instrument is also not weak (the AngristPischke F statistic is 81.65). However, the conclusion does not depend on the specification; the results in columns (6) and (7) both show no statistically significant effect of higher MFI coverage on moneylender interest rate. The results on the third quartile as the treatment group suggest that the positive effects of MFI penetration on moneylender interest rates reported earlier in Tables (1) and (2) are likely to be driven by the fact that a perceptible effect on the informal interest rate is observed only when MFI activities cover a large enough proportion of the households in a village. This plausible conjecture is validated by the results reported in the last two columns of Table 3.

For the estimates reported in the last two columns (Columns (8) and (9)), we again take the first and second quartiles as the comparison group, but the fourth quartile is the treatment group. The effects of MFI coverage are positive and large in magnitudes in both the OLS and KV regressions. The coefficients are statistically significant at the 1 percent level. Both of these estimates are larger than those reported in Tables 1 (column 4) and Table 2 (column 4). The KV estimate indicates a large effect of higher MFI coverage on moneylender interest rate.

# **3. MFI MEMBERSHIP AND HOUSEHOLD BORROWING FROM INFORMAL SOURCES**

As discussed in detail before, a higher moneylender interest rate following the spread of MFI programs in a village credit market is consistent with alternative hypotheses regarding the household borrowing. To distinguish between these alternative explanations, in this section we provide an analysis of household borrowing from informal sources including moneylenders. The focus of the analysis is on the question whether MFI membership in fact increases the probability that a household borrows from informal sources, even though it did not borrow from them before, as argued by the critics of microcredit. We take advantage of household level panel data for the empirical analysis. We also shed light on the average informal loan size of the MFI members compared with non-MFI members 19