control group. Pre-ruling summary statistics for treatment and control are provided in Appendix Table A1.

Figure 3 contains two panels; the top panel shows neonatal mortality averages from the full period, while the bottom panel uses data within a smaller, symmetric 15-year window (1980-1994) surrounding the Supreme Court verdicts. In both panels, the vertical distance between the treatment and control group means is smaller after the verdicts than before them. The smaller scale of Panel B allows for a closer look, which shows parallel decreasing pre-trends, a roughly-constant slope in the control group over the full period, and a drop in treatment-group mortality in the aftermath of the verdicts.

Figure 4 provides analogous results for river pollution, using a dummy for exceedance of the bathing quality standard (BOD>3) as the dependent variable. Since this specification requires pollution data, the full time period available to us is 1986-2004. The top panel utilizes the full period, while the bottom panel restricts the estimation sample to 1986-1994 – a “short-run” post-period. Here, the outcome variable is somewhat noisy in the treatment group. In the short pre-period available to us for pollution, however, treatment- and control-group trends are parallel. Meanwhile, the likelihood of BOD exceeding the 3-mg/l cutoff drops significantly for the treatment group in the post-period, indicating a large DD estimate of the impact of the ruling on water quality.

While in principle it is possible to compare our treatment group to a single nearby (but not downstream) control district, inherent noise in our infant mortality and pollution data makes such a comparison imprecise. We illustrate this in Appendix Figure 1 by plotting average mortality (Panel A) and pollution (Panel B) in the treatment group and in a single district (Kannauj) just upstream of Kanpur Nagar. 10These graphs document a large time-series variance in outcomes of interest. Using the entirety of the Ganga Basin in our control group allows us to smooth our counterfactual significantly.<sup>11</sup>

# **4.2 The impact of** **_Mehta vs. Union of India_ on infant health**

To obtain a point estimate of the Supreme Court verdicts’ impact on infant health, we estimate equation (1). Table 2 provides our first set of results from this estimation. In columns 1-3, we use the full 1971-2004 period, while in columns 4-6, we use the shorter 1980-1994 period. Within each of these triplets, the first column uses one-year (infant) mortality as the dependent variable, the second uses one-month (neonatal) mortality, and the third uses one-year mortality _conditional on survival past the first month_ . In all columns, we multiply RCH-2 sampling weights by the inverse size of the relevant age

> 10The district of Kannauj is immediately upstream of Kanpur Nagar. The two Kannauj pollution monitors in our data lay approximately 93 kilometers upstream of the tanneries.

> 11We also test the robustness of the graphical DD strategy to the definition of the treatment group, by graphing treatment- and control-group average outcomes after redefining the treatment group to only include Kanpur Nagar district itself. The results are depicted in Appendix Figure A2; they do not change in any qualitatively meaningful way.

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