where y��� is the outcome measure of child _i_ in village _j_ at time _t._ T� is an indicator for whether the village is treatment or comparison, X��� are time varying covariates (child’s age, household size, household wealth index, and parenting score) and V�������� are time invariant covariates (child’s gender, whether the child’s mother completed primary education or less, and baseline measures of child development). The key coefficient of interest is the treatment effect, α� . Equation (1) is the specification for 2013, which examines the effect of the intervention on enrollment rates and EDI at age 5. Equation (2) estimates the impact in 2016, which examines the effect of the project on enrollment rates, EDI, and test scores at age 8.

Our key identifying assumption is that the time varying and invariant covariates in our regression model fully account for any differences between children in the treatment villages and children in the comparison villages that are not due to treatment assignment.

We also examine the heterogeneity of the treatment effect across household wealth and parenting practices. We re-run our regression model separately for children with baseline household wealth below the sample mean ( _poor_ ) and for children with baseline household wealth above the sample mean ( _non-poor_ ). Similarly, we re-run our regression model separately for children with baseline parenting scores below ( _low parenting score_ ) and above ( _high parenting score_ ) the sample mean.

In Table 1, for the younger cohort, we show the summary statistics of child and family characteristics in treatment and comparison villages at baseline (2009). Columns 1 and 2 separately present the means and standard deviation for villages that received the project early (batch 1) and those that received the project later (batch 2), and column 3 presents these statistics for a sample that combines all treated villages together. Column 4 reports these statistics for the comparison villages that never received the project but were chosen because of their similarity to treatment villages. Column 5 reports the differences between villages that received the project early or late while column 6 reports the differences between treatment and comparison villages. In both of these cases the estimates reported are the results of a regression with standard errors clustered at the village level.

Column 3 shows that at baseline, younger cohort children in the treatment villages were around 1.5 years old. On average, children lived in households with wealth z-scores and parenting z-scores slightly below the sample mean. About half of the cohort’s mothers had primary education or less and about half of the children were male. The mean body mass index (BMI) of the children in the younger cohort was 14.6 kg/m<sup>2</sup> and on a range of cognitive, fine motor, gross motor and language skills their scores were slightly below the sample mean.

Column 5 reports that there are no differences in these child and family characteristics between the two batches of treated villages. As a result, we examine batch 1 and batch 2 villages collectively as treatment villages in our regression specification in equations (1) and (2).

Column 6 shows that at baseline, treatment and comparison villages were generally similar in terms of various child and family characteristics. However, three variables showed statistically significant differences. On average, children in treatment villages lived in households with 0.259 fewer people than children in comparison villages. While this mean difference is statistically significant, the magnitude is small. We also find that children in treatment villages scored lower in measures of baseline cognitive skills (-0.143 S.D.) and gross motor skills (-0.153 S.D.). Thus, we control for these baseline differences in child development in our estimation of the treatment effect.

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