# **Summary of results:**

Table 3.4 below shows the results. We present the coefficient on the LEAP variable (divided by 10, to ease interpretation). As the dependent variable is in log form, we can read the coefficients as “a 10% worsening of the LEAP crop loss leads to an X% reduction in consumption per adult”. For example, the baseline result shows that for every 10% worsening of LEAP, consumption falls on average by 1.5%. We computed bootstrapped standard errors across all of the statistical learning components (see next section) and therefore also present a 95% confidence interval for the point estimate based on the bootstrapping results. The LEAP drought variable is significant in all specifications. In the following columns, interaction terms are included, so the point estimate is interpreted as the drought impact for households that are not defined by any of the characteristics included. So, for column 2, we include female headed, psnp, and schooling. The coefficient of 2.0% represents the impact of a 10% increase in the LEAP drought on consumption of male headed households with no schooling and no access to the PSNP. There is a zero coefficient on schooling and female headed, so we do not see any difference in the impact for those groups. However PSNP access mitigates the drought impact by 0.5% = therefore households with PSNP access would experience a 1.5% decrease in consumption (rather than a 2% decrease with no access).

Reading across the columns we see no differential impact in any of the specifications for female headed households, educated household heads, head not in agriculture, distance to town, dependency ratio.

We do find significantly different impact for households with access to the PSNP, with cattle, and financial access: these characteristics are seen to be mitigating the impact of the drought. However, households that suffered other crop damage experienced a heavier impact of the drought.

Noting above the potential concern that financial access and shocks such as crop damage are self‐ reported.

**Table 3.4 Main regression results**

||Baseline|Specparsi|Spec2|Spec4|Spec3|
|---|---|---|---|---|---|
|(Intercept)<br>Drought shock|7.794<sup>~~∗∗∗~~</sup><br>(0.018)<br>−0.015<sup>∗∗∗</sup><br>(0.002)|7.800<sup>~~∗∗∗~~</sup><br>(0.018)<br>−0.020<sup>∗∗∗</sup><br>(0.003)|7.815<sup>~~∗∗∗~~</sup><br>(0.020)<br>−0.028<sup>∗∗∗</sup><br>(0.006)|7.821<sup>~~∗∗∗~~</sup><br>(0.020)<br>−0.033<sup>∗∗∗</sup><br>(0.007)|7.815<sup>~~∗∗∗~~</sup><br>(0.020)<br>−0.058<sup>∗∗∗</sup><br>(0.007)|
|boot.se|0.0025|0.0028|0.0066|0.0067|0.0078|
|boot.ci|(‐0.020,‐0.0104)|(‐0.0242, ‐0.0130)|(‐0.0408, ‐0.0148)|(‐0.0463, ‐0.0202)|(‐0.0728, ‐0.0425)|
|Drought*Head school||0.000<br>(0.001)|0.000<br>(0.001)|0.000<br>(0.001)|0.000<br>(0.001)|
|Drought*Femalehead||0.000<br>(0.000)||||
|Drought*PSNP||0.005<sup>∗∗∗</sup>|0.005<sup>∗∗∗</sup>|0.005<sup>∗∗∗</sup>|0.005<sup>∗∗∗</sup>|
|||(0.001)|(0.001)|(0.001)|(0.001)|
|Drought*non‐agri hh|||0.000|0.000|−0.000|
||||(0.001)|(0.001)|(0.001)|
|Drought*dist. market|||−0.000|0.000|0.000<sup>∗∗∗</sup>|
||||(0.000)|(0.000)|(0.000)|
|Drought*dependency|||0.001|0.001|0.001|
||||(0.001)|(0.001)|(0.001)|
|Drought* anycattle|||0.014<sup>∗∗</sup>|0.014<sup>∗∗</sup>|0.018<sup>∗∗∗</sup>|
||||(0.004)|(0.004)|(0.004)|
|Drought*Fin. access||||0.001<sup>∗∗</sup>|0.001<sup>∗∗</sup>|
|||||(0.000)|(0.000)|
|Drought* Illness||||0.000|0.000|
|||||(0.001)|(0.001)|
|Drought* Cropdamage||||−0.001<sup>∗</sup><br>(0.001)|−0.001<sup>∗</sup><br>(0.001)|
|Drought*livestock||||−0.000|−0.000|
|shock||||(0.001)|(0.001)|

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