Redistributing the risk and repercussions of climate shocks through trade

The physical impacts of climate change on agriculture vary in unpredictable ways across both space and time, creating substantial risks for farmers, consumers, and governments. Those risks can be managed by changing what is planted, storing crops, and through trade. However, it is not well understood how those risk management strategies interact to jointly redistribute the risks and impacts of climate change on agriculture. To address that gap, the project develops a theory on how risk management affects trade policy and volumes, quantifies the persistence of trade patterns, and brings together satellite and administrative data to document the role of risk in planting decisions at scale. Further, the project pairs these results with climate models to refine projections of climate damages, informing climate, trade, and aid policy discussions. In addition, the project integrates the co-development of educational activities at the K-12 level. It advances the training of graduate and undergraduate students, emphasizing broadening participation among students from underrepresented groups. Local risk management tools and trade are likely to alter the distribution of climate damages jointly but are often investigated separately. This project (a) advances the integration of risk-aware behavior into general equilibrium trade models, (b) applies econometric tools to quantify how risk shapes trade persistence, trade policy intervention (e.g., export bans), and what farmers plant, and (c) couples those advances with climate models to improve predictions about when and where climate-induced agricultural losses will be felt. The resulting predictions inform ongoing negotiations about climate policy, finance, food security, and targeted interventions to assist people at the greatest risk. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.