estimate the number of food shocks experienced in a year as a function of temperature shocks in the previous year to account for timing of harvest and storage. We conduct this analysis for a full year as well as by agricultural growing season. We do not find evidence that the previous year temperature shocks we document in our data are leading to significant increase in current year food insecurity (Table 5). These results suggest that our results are unlikely to be driven by a nutrition channel.

# **6.3 Heterogeneity in Effects by Gender**

In our test score data, female students perform relatively poorly compared to male students, on average. Given these baseline differences, we explore whether the effects of temperature on test performance vary by gender. To do this, we add an interaction term between temperature bins and a female dummy to our main empirical specification.

Table 6 shows that coefficient of the interaction term between temperature and female dummy is predominantly positive. Moreover, these effects are positive and statistically significant for temperature bins above 30<sup>_◦_</sup> C across english, math, and the Total score. This indicates that the effects of heat matter less for female students compared to their male peers. Notably, female students appear able to fully offset the negative effects of temperature on their performance in math. This resilience displayed by female students, despite prevailing societal norms that place them at a disadvantage during weather shocks, is remarkable (Bj ̈orkman-Nyqvist, 2013).

There are many potential explanations for this including physiological differences in resilience to heat between females and males, and changes in societal norms that benefit females. However, we have limited data to rule out many of these possibilities. One hypothesis that we find particularly interesting is that these exams may be higher stakes for women as the consequence of going to college versus not may be greater for them. As a result, women may put in more effort relative to men, which may compensate for the negative impact of heat exposure.

While we cannot test for gendered differences in effort directly, we check whether female students were absent from school less compared to their male peers. Our data contains information on extended absences from school, but not the number of days of absence. That is, we know if a student was absent during the last semester for more than a week. We also have information on travel time to school, which may reflect the amount of effort that students are putting into attending school. We interact the travel time with female dummy to indirectly isolate gendered differences in effort.

Our results (Table 7) show that there are heterogeneous effects by gender on the probability of extended absence from school. Female students have a lower likelihood of extended absence from school compared to their male counterparts. There are also differential effects of travel time on absenteeism; female students have no effect of an additional minute of travel time to school on absence from school, whereas for male students, an additional minute of travel time increases the likelihood of extended school absence by experienced in the calendar year.

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