Social Impact Assessment of Microfinance Programmes - weman

The Difference in Differences (DID) impact model estimated for SAFWCO is
Y ij = X ij α + C ij β + M ij γ + T ij δ +v ij
Where Y ij is an outcome on which we measure impact for household i in locality j, X ij is
a vector of household characteristics * , C ij is a dummy equal to 1 for active borrowers and
their matched neighbours and 0 otherwise, M ij is a membership dummy variable equal to
1 if household i self-selects into the credit programme, and 0 otherwise; and T ij is a
variable to capture the treatment effects on households that self selected themselves into
the programme and are already accessing loans. T is also a dummy variable equal to 1 for
active borrowers and 0 otherwise. The coefficient δ on T ij is the main parameter of
interest and measures the average impact of the programme. A positive and significant δ
would indicate that microfinance is having a beneficial effect on the borrowers.
SAFWCO has been providing microcredit for sometime and in our sample we have
clients in loan cycles ranging from one to five. Therefore we do two separate sets of
regression on young and old borrowers. In our sample the mean number of loan cycles is
2.1, therefore we define young borrowers as those who have borrowed 2 times or less and
old borrowers who have borrowed more than 2 times.
A Single Difference equation is also estimated to assess impact between active borrowers
and the pipeline clients. This exercise was done for both young and old borrowers. The
form of the equation is as follows and the variables are defined as stated above.
Y ij = X ij α + T ij δ +v ij
The results from the estimation of δ are given in Table 1. One area where SAFWCO is
having a clear impact is women’s empowerment. Old borrowers perform significantly
better on all indices compared to other respondents. On the overall index old borrowers
score 10 points higher (p=0.018) than other respondents. Old borrowers also perform
better than pipeline clients in the single difference estimates on 3 indices of
empowerment. Furthermore, young borrowers also do significantly better on the income
empowerment index in both single and double difference estimates (DID: 1.5 pts;
p=0.019). In these regressions the member dummy is not significant and therefore we can
say that the higher score on empowerment is due to borrowing from SAFWCO, as the
insignificant member dummy implies that to begin with individuals who self-select into
the borrowing programme are not more empowered. The other result that is positive and
significant is savings for old borrowers compared to pipeline clients. On average, old
borrowers are saving Rs.300 more than pipeline clients (p=0.063).
The only other result that is significant is educational expenditure; however it is negative
implying that old borrowers are spending less than pipeline clients (-138; p=0.008). The
other variables that were generally significant in the regressions were rural and
* For SAFWCO four household characteristics were included in the regression out of 16 tested through
ANOVA.
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