One issue that might affect the credibility of these estimates is that with nonrandom program placement, the assumption of parallel trends between treatment and control may not hold. To account for this, some studies have used an index by the Planning Commission that in some sense defines program eligibility by ranking districts by poverty. Using this index in a discontinuity framework suggests that NREGS has had limited impact on male wages and levels of employment but some effects on females, with wage impacts concentrated in the agricultural off-season (Zimmermann 2012). NSS consumption data from 2005 and 2008, used to construct a nationwide district panel (188 in phase 1 and 103 in phase 2), allows researchers to assess the program’s impact on poverty gaps and consumption patterns, suggesting effects on welfare, especially for scheduled castes and tribes, and nonfood spending (Klonner and Oldiges 2012).<sup>5</sup> As NSS data lack information on wages in agriculture, use of administrative data on gender-specific wages for agricultural and unskilled tasks (at the district level) could allow more direct inference of agricultural wage gaps, which are most relevant for the poor. Results from this analysis suggest that the program affects unskilled wages but leaves the gender wage gap unaffected (Berg et al. 2012).

Beyond possible general equilibrium effects, impacts on participating households can help identify ways in which benefits from NREGS participation materialize. Such effects can, in principle, be identified using panel data for households unable to participate initially. Relying on a small household panel dataset in one district in Andhra Pradesh, Ravi and Engler (2012) apply a pipeline to compare participants to households that were denied access and find that NREGS had large impacts on total, food, and nonfood per capita expenditure (found to have increased by 9.6 percent, 23 percent, and 17 percent, respectively). NREGS participation is estimated to have increased the likelihood of a household having a savings account by 21 percent and total savings by Rs. 19 (Ravi and Engler 2012). Because the baseline survey was conducted at a time when the program was already available, the credibility of the results depends on the fact that initial rationing of nonparticipants was indeed exogenous. Another study that relies on a large sample focuses on education and social outcomes instead and finds that higher female participation in NREGS (instrumented by _mandal_ -level rainfall shocks) increased girls’ time spent in school, grade progression, and female bargaining power (Afridi, Mukhopadhyay, and Sahoo 2012).

# **3. Data, Descriptive Evidence, and Approach**

To assess program impacts, we combine panel household survey data from before and after the program became available, together with administrative data on participation, using double and triple difference estimates together with propensity score matching. The phased introduction of the program allows us to distinguish short-term from medium-term effects, overall as well as for subgroups in the population.

> 5 Both the Planning Commission’s “backwardness” index and the intensity of implementation (as measured by the number of days actually worked) are used to control for this.

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