Table 8 implies that the difference between new and non-participants in calorie and protein intake was significant. Consistent with village level findings, our results point towards statistically and economically significant program impacts on mean per capita spending for new participants but not for converted participants or those who did not join SHGs. The estimated ATET is about 1,000 R or 17 points for the new participants.<sup>18</sup> Although the program explicitly aims to increase participants’ income and assets, we find no significant differences between treated and controls in these variables for either new or converted participants. This result, which is in line with village-level evidence, implies that, by 2003, the program had not led to a significant increase in incomes or assets of either group of participants. We can think of a number of ways of reconciling this with the evidence of significant impacts on consumption. A first possibility is that the result is due to a short-lived consumption caused by participants consuming the one-time capital injection by the program. Our data which point towards high levels of repayment on project loans, a path of asset accumulation by most groups, and the fact that extrapolating the estimated increase in consumption over the whole project area leads figures that are larger than the net inflow of project resources implies that, although it is a possibility for individual groups that were then disbanded, this is unlikely to be the reason at an aggregate level.<sup>19</sup> A second possible explanation is that, at the time of the survey, exogenous shocks may have prevented participants from realizing their potential. Given that, as noted earlier, two of the three agricultural seasons preceding the survey were droughts characterized by large crop failures, and as program areas are more dependent on agriculture and less diversified than control areas, this explanation has some plausibility.<sup>20</sup> In addition, noise in income data could bias results towards zero and thus make it impossible to detect program effects on these variables at standard levels of confidence.<sup>21</sup> A third possibility is that, in view of the target group, a key objective of the project is to help smooth consumption while income effects may be expected to materialize in the future. If this were the case, data from a later stage in the program would be needed to assess whether income effects did materialize or not.

# **5. Conclusion and policy implications**

Rather than repeating our results, we conclude by highlighting how this paper adds to the literature and point out the scope for follow-up efforts to provide additional insights. By considering outcomes beyond narrowly defined economic variables, we show that community driven development programs can have

> 18 Note that the slightly lower significance level (of 10% as compared to 5%) for new participants could be due to the smaller sample size.

> 19 During the period covered by our survey (i.e. June 2003 to June 2006), the average annual net loan receipt per household for program SHG participants was about R 330, which is significantly lower than the estimated increase in consumption.

> 20 This is supported by the fact that 1,123 of agricultural households out of the total 2,516 households in the DPIP areas reported zero agricultural income in either of the two seasons.

> 21 In our case, the income aggregate has to be constructed using 116 variables rather than only 84 as in the case of consumption.

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