Conference Agenda

We explore the hypothesis that individuals who experience multiple natural disasters over consecutive years may become discouraged from continuing economic activity in their country of origin, prompting them to migrate internationally to secure their income. To test this hypothesis, we analyze data on international migration alongside data on droughts and storms from 2000 to 2020. Specifically, we find that migration is more likely to increase following droughts, whereas storm events have a dampening effect on migration. The distinct nature of these events—droughts being slow-onset and progressively reducing income, and storms being sudden and causing immediate damage that leads to liquidity constraints—results in different adaptation strategies. Moreover, by accounting for the heterogeneity of disaster types and the specific characteristics of countries, we identify several patterns of climate-induced migration. These effects are particularly pronounced in migration flows involving low- and high-income countries. Furthermore, when accounting for country size, small low- and middle-income countries, as well as large low- and high-income countries, are the most affected by droughts.

As global temperatures rise and extreme weather events intensify, local power distribution systems face significant reliability challenges. Using a novel dataset of daily municipal-level unplanned outages, we show that temperature extremes substantially increase outage incidence, beyond the known effects of hurricanes and storms. This vulnerability primarily arises from technical failures, such as equipment faults and overloads, rather than environmental factors like high winds or lightning. Large deviations from moderate temperatures sharply elevate the risk of technical outages, with overload-related outages increasing from below 2% at mild temperatures to nearly 35% at temperatures exceeding 39 °C. Moreover, heat-induced outages increase with greater air conditioning adoption, exacerbating grid stress precisely when cooling is most needed. These findings reveal an overlooked climate risk for developing regions, where rising temperatures and growing reliance on air conditioning may strain distribution networks. Our results underscore the urgency of targeted policy interventions and infrastructure investments to enhance grid resilience amid intensifying heatwaves.

Access to safe and reliable drinking water is essential for well-being, yet in many rural settings, water infrastructure is frequently unreliable. This paper examines the household-level consequences of well failure using a novel measure of predicted well functionality in Ethiopia. Leveraging a machine learning model trained on hydro-environmental variables, I construct an exogenous proxy for well failures and link it to detailed household survey data. I document a series of behavioral responses to those water access disruptions. Households adjust by switching away from groundwater toward more proximate, but potentially lower-quality sources such as surface water. Consistent with this shift, reported time spent collecting water declines, especially among adults. However, this reduction masks a reallocation of responsibility: more children are mobilized to fetch water, and this increased burden has downstream effects. Children in affected households are significantly more likely to miss school and are increasingly engaged in farming and casual work. These findings reveal the cascading effects of water access disruptions on household labor dynamics and children's time use, underscoring how environmental shocks can shape human capital accumulation and economic behavior.

This study analyzes the impact of climate change on the profitability of Vietnamese farms and evaluates the effectiveness of their adaptation strategies while accounting for neighborhood effects. By combining climate data with Vietnam’s household survey data, we examine two adaptation strategies: adjusting the share of cultivated land allocated to specific crops (crop selection) and increasing machinery investments (mechanization). To assess these effects, we employ a two-stage estimation approach. In the first stage, we analyze farms’ crop selection and mechanization using quasi-maximum likelihood (QML) estimation and Tobit estimation, respectively. In the second stage, we examine the impact of climate variables on profitability while accounting for adaptation under neighborhood influence. Our results indicate that rising temperatures and increased rainfall negatively affect farm profitability. Additionally, we identify a significant neighborhood effect, where a crop switching behavior indirectly influences individual farms through spillover effects. Regarding adaptation, we find that increasing the share of specialty crops and fruits (relative to rice) and investing in machinery enhance profitability. Using these estimation results, we simulate profitability changes under future climate projections. We find that climate change exerts a negative impact on farm profitability; however, adaptation strategies help mitigate this effect.