percent level across Tables 1 and 2, and only two differences are statistically significant at the 10 percent level, which is what would be expected by chance.

Second, further corroborating the conditions required for _γ_ to represent the arguably causal impacts of the earthquake, the identification strategy is able to uncover a pattern independently reported by humanitarian agencies using other data sources at the time of the earthquake- a growing food security crisis arising from the disaster that was worst felt in the Southern Highlands and Hela provinces. The DHS collected the Food Insecurity Experience Scale in the household survey, which is composed of both subjective and objective questions on food access.

Using an identical identification strategy as described in (1) but using the household survey information on food security as the dependent variable, Figure 3 reports the difference-in-differences estimate of the change in food security relative to the rest of the country. As expected by the sampling strategy that reaches more rural and remote households in later phases of the survey, there was a worsening of food access for all households following the earthquake in the fourth phase of the survey across the country. However, there was a substantially larger increase in the share of households reporting poor food access in the regions worst affected by the disaster. There was between a 6 and 15 larger percentage point increase in the share of poor food access in disasteraffected regions for the three objective food security measures (skip meals, run out of food, and going a whole day without food), which represents between 16 and 45 percent of the pre-disaster share of households that reported poor food access across the entire country.<sup>28</sup> Third, it is possible that the disaster led to changes in survey quality or in the willingness of individuals to respond to the IPV module in earthquake-affected regions, and this change might be driving some of the results and not an actual change the prevalence of IPV. Even though the low rates of non-response reported in the Data section suggest that this is likely not a significant problem, it is possible that the few instances of non-response were concentrated in disaster-affected regions after the earthquake. However, Figure 4 reports estimates of specification (2) using an indicator equaling one if a woman did not respond to the IPV question and illustrates that this is not likely to be the case. All of the estimates are small in magnitude, vary in sign, and are unable to rule out the possibility that there is no difference in the change in non-response in disaster-affected regions

> 28Although subjective questions on food security add information about how individuals felt about their experiences with food insecurity, the questions are difficult to interpret given different individuals use different thresholds and different criteria by which to report their subjective experiences, and those experiences might have little to do with actual food consumption (e.g., Stiglitz et al. 2009; Krueger and Stone 2014; Tandon 2024; etc.). Figure 3 illustrates that there was little difference in the change in subjective food security questions in disaster-affected regions relative to the rest of the country, with the magnitude of the difference-in-differences being close to zero and imprecisely estimated.

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