households with at least one casual laborer, with potential spillover effects—in terms of asset accumulation, which may be explained by higher levels of investment in land improvement by program participants—to households with no casual laborers. This could be a channel for NREGS to trigger a sustained increase in labor demand, consistent with our rejection of the hypothesis that NREGS crowds out other types of informal employment or private land investment activities.

# **4.1 Estimates of Program Impacts**

Results from DID estimates with and without PSM for medium-term (in phase 1 districts) and short-term (in phase 2 and 3 districts) impacts are in the two top and bottom panels of Table 3. The 2006–2008 data provide an estimate of program impacts, while 2004–2006 data serve as a test for the assumption of parallel trends.<sup>13</sup> For the medium term, DID results from 2006-2008 data point toward a positive impact on consumption and formation of assets, while results from DID plus PSM suggest a significant impact on accumulation of nonfinancial assets only. For 2004–2006, DID and DID plus PSM reject the parallel trend assumption: both suggest that pre-program changes in consumption and nutritional intake were lower for participants than for nonparticipants, a finding that should not come as too much of a surprise, as participants self-selected into NREGS. As a result, DID may underestimate actual program impacts, motivating use of the DDD approach. In the short term (phase 2 and 3 districts in the bottom panels), DID and DID plus PSM suggest positive effects of NREGS participation on protein intake and fail to reject the parallel trend assumption, possibly due to lack of power.

The results from simple DDD and DDD plus PSM, as reported in the top panel of Table 4, point toward significant and positive medium-term impact of NREGS participation on consumption expenditure and asset accumulation. With an annual increase of 11 or 7 percentage points, or Rs. 1,261 or 943, for the two methods, respectively, estimated gains exceed the magnitude of NREGS-related cash transfers to participants in per capita term (Rs. 570 overall or Rs. 672 in 2008). The estimated NREGS-induced increase in asset accumulation of 35 to 40 percent is large as well. Evidence from phase 2 and 3 districts points toward significant NREGS impacts—of 11 percent and 12 percent—on energy and protein intake, respectively, supporting the notion that most immediate program impacts involve improving nutrition, as suggested by others (Jha, Bhattacharyya, and Gaiha 2011a), possibly followed by asset accumulation in the medium term.

To explore whether, as suggested by other studies and descriptive data, NREGS disproportionally benefits the marginalized, we repeat the above analysis for scheduled castes and tribes compared to others. We

> 13 Dependent variables include total value of consumption, caloric and energy intake, and nonfinancial assets in levels and logs, with the latter providing an estimate of the percentage change in the outcomes of interest. One advantage of the latter, in addition to being more robust to local inflation, is that it pulls in outliers and changes the distribution of outcomes so as to give poorer households greater weight.

12