Specifically, we estimate variations of the following base specification: where Depth _iyq_ is the inverse hyperbolic sine transformation of the average depth to groundwater in district _i_ , year _y_ , and season _q_ .<sup>12</sup> Larger numbers indicate that wells must be deeper, and therefore more expensive, to reach groundwater. Depth measurements are taken during the monsoon, at the end of the kharif season, during the rabi season, and prior to the start of the monsoon. Our variable of interest is the interaction of 1<sup>�</sup> NREGA _iy_ �, an indicator for MNREGA presence in a district, and 1<sup>�</sup> Star _i_ �, an indicator for whether the district lies within a Star state. We include a quadratic in the total precipitation the district receives in a year and control for the average temperature in the district during the year. We also include district ( _α_ ) and year ( _χ_ ) fixed effects and a quadratic state _×_ year ( _η_ ) trend. We cluster standard errors at the district level (Abadie et al., 2017).<sup>13</sup> Our primary outcome of interest is _β_ , which provides (approximately) the percent change in depth to groundwater in Star states compared to non-Star states after implementation of MNREGA. Note the district fixed effects absorb the Star indicator so we only specify the interaction in Equation 1. The key assumption in our approach is that the trends in depth to groundwater in Star and non-Star states were parallel prior to the implementation of MNREGA and that these trends would have continued to evolve similarly absent the implementation of MNREGA.<sup>14</sup> The event studies for each of our outcomes suggest that the assumption of parallel pre-trends is met. That these trends would have continued to evolve in parallel absent MNREGA is fundamentally untestable.

In our primary approach we estimate Equation 1 using the approach described in Callaway and Sant’Anna (2021) using their provided Stata packages. To test for pre-trends we estimate event studies using the approach described in Borusyak et al. (2024) using their provided Stata packages.<sup>15</sup> In Appendix A1 we estimate a traditional staggered difference-in-differences that uses the full roll-out of MNREGA and show our results are broadly robust to this approach as well.

To examine farmers’ response to any changes in groundwater levels due to MNREGA, we retain the right hand side of Equation 1 but replace the left hand side with the inverse hyperbolic sine of soil moisture and inverse hyperbolic sine of area irrigated from various different sources. We use the same specification to examine how the area of different crops that are irrigated changes after implementation of MNREGA. For these analyses we replace the left hand side with the inverse

> 12We use the IHS transformation to put our estimates in more easily interpretable percentage terms and limit the impact of outliers on our estimates. In results available upon request we show that all of our primary results are robust to using the un-transformed measures of depth to groundwater in meters or area irrigated in HA.

> 13As a very conservative test - because it reduces the number of clusters to only 21 - we can cluster errors at the state level instead of districts. Our results on kharif, rabi, and Pre-monsoon depth to groundwater remain robust to this clustering at the 5% level.

> 14Note that the difference-in-differences approach does not require balance on other observables between Star and non-Star states.

> 15In Appendix A4 we provide event studies estimated with the approach described in Callaway and Sant’Anna (2021) as a robustness check.

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