assistance had no direct impact on any of our food consumption measures. Households with access to the school feeding program had lower food expenditures, but with no subsequent impact on calories or food consumption scores, indicating that households substituted school feeding for home provision of calories and food consumption scores. On the other hand, having access to wages from MASAF led to increased food expenditures similar to those with access to school feeding, it appears that households were able to use the wages to maintain calories and food quality.

Finally, our interaction terms show that having access to food assistance increased food consumption scores for households in both medium- and high-affected areas, vis-à-vis those located in low-affected areas. On the other hand, access to school feeding led to improvements in all three of our consumption measures, but only for those found in medium affected areas. Similarly, access to MASAF led to higher food expenditures and calories consumed, but only for those in medium affected areas.

The evidence suggests that only food aid was an important safety net for households in high-affected areas, whereas all three safety nets led to improved consumption outcomes for those located in mediumaffected areas. At the same time, it is worth noting that the proportion of households with access to food aid and MASAF actually decreased between 2013 and 2015. Access to school feeding increased between 2013 and 2015, but access to school feeding only improved outcomes for those in medium-affected areas. Overall, the evidence suggests that safety nets do improve consumption outcomes, but there is room to improve the reach of these programs into areas that suffer severe weather events.

In Table 6, we present the results from the IV estimations, in which we instrument for the logarithmic transformation of real household value of crop production per capita. We present only the results for the instruments in the first stage, and the value of crop production per capita in the second stage.<sup>22</sup> We note that the number of observations does not match in Table 5 and Table 6. This is due to the necessary exclusion of the few households that did not produce any crops from the analysis in 2015. Our instruments are fairly strong, with F-statistics just below 10 in all three equations, and the p-values associated with the Hansen’s J statistic are over .1 in all three equations, in support of the exclusion restriction. We document that while food expenditures are positively correlated with the value of crop production per capita, the estimated elasticity is just 6.7 percent, implying very limited transmission from production to consumption.<sup>23</sup> Higher values of crop production per capita are also estimated to lead to higher food consumption scores, though not necessarily to higher calories per capita.

> 22 The full set of results from the IV estimations are available upon request.

> 23 In line with this finding, World Bank (2016) also finds that all else being equal, a 1 percent increase in maize yields in Malawi leads only to an estimated 0.13 percent increase in consumption per capita and an estimated 0.06 percent increase in caloric intake per capita.

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