showing the descriptive trends in Figure 2 where firm outcomes are plotted against annual standardized rainfall using a binned scatterplot. We use two rounds of the NSS survey data on unincorporated enterprises for this exercise, conducted in 2010-11 and 2015-16, and restrict our sample to 13,010 enterprises located in rural areas. Based on the unconditional correlations, we discern a strong positive effect of higher annual rainfall incidences on enterprise revenues and value-addition, and weak negative effects on machinery and tools, credit (along the extensive margin) and wage per worker.

We next rigorously examine these descriptive trends using specification (3). All specifications apply enterprise weights and include district and firm level covariates. Standard errors are clustered by district. Table 3 shows our baseline results. Consistent with the results seen in Figure 2, we see that a positive rainfall shock has a large and statistically significant impact on enterprise revenues and value addition, and a limited effect on produc– tive capital (machinery and tools). The coefficients are economically significant compared to average enterprise revenue and value addition when there is neither a positive or negative shock (the reference case), a positive rainfall shock increases monthly enterprise revenues (value-addition ) by an additional INR 9,000 (INR 3,038).<sup>8</sup> The lack of an impact on enter– prise capital is expected precipitation shocks are temporal fluctuations while investments in machinery and tools are lumpy investments which yield returns over the medium and long-term.

Columns (5)-(7) of Table 3 investigate whether positive rainfall shocks affect hiring, wages or wage per worker.<sup>9</sup> We find no effect on either of these outcomes. If anything, there is a negative impact on total workers, which could occur if these enterprises are competing with the farm sector for labor, and positive rainfall shocks increase the demand for farm labor (see Colmer (2019)).

Table 4 shows the impact of precipitation shocks on qualitative measures of enterprise performance and credit usage. The NSS survey asks enterprises whether they are expanding, stagnating or shrinking, and whether the enterprise is registered with state or local authorities. We combine stagnation and shrinkage into a single category and run linear probability models to identify the impact of rainfall shocks on these binary outcome measures. As seen from columns (1)-(3), a positive rainfall shock has a significant positive impact on the likelihood of enterprises registering with a local or state body, and a weak negative impact on their probability of stagnating or shrinking. We however find no impact of precipitation shocks on enterprise expansion.

Columns (4)-(9) of Table 4 identifies the impact of rainfall shocks on enterprise credit. Our survey captures credit both along extensive and intensive margins, and also identifies – the source of credit bank, or non-bank. Across both the extensive and intensive margins, we find little impact of a positive rainfall shock on access to credit. While the coefficient on non-bank credit along the extensive margin is positive, the confidence intervals are too large to draw any meaningful conclusions.

> 8 This mean enterprise revenue (value addition) when enterprises are faced with a zero shock is INR 35514 (INR 10028). Based on the coefficients from Table 3, this implies an increase of INR 0.257*35514 (INR 0.303*10028) on enterprise revenues (value-addition).

> 9 The observations in the last three columns are smaller as we exclude own-account enterprises from these regressions as these enterprises by definition do not hire any workers.

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