Abstract: Predictions guide important adaptation responses--from treating patients in hospitals to pretreating roads before snow storm. Advances in machine learning and artificial intelligence are accelerating improvements in prediction accuracy. However, it is unclear how prediction improvements should shape optimal adaptation. I develop a theoretical model for prediction-based prevention and provide three key insights. First, better predictions lead to more intense, yet less frequent, adaptation response. Second, risk preferences matter less as improved predictions resolve more uncertainty. Third, the average adaptation declines for highly risk-averse decision-makers but may rise for less risk-averse ones. These findings highlight the need to align adaptation planning with prediction skill, especially given varying levels of trust in prediction technologies.

Abstract: Improvements in forecasting technologies provide an opportunity to take anticipatory actions before disasters occur. However, traditional ex-post financing and lack of operational capacity often discourage countries from taking early actions. This paper examines anticipatory index insurance, focusing on a pilot by African Risk Capacity in Malawi and Zambia for drought risk. The product offers early-action capacity development and provides forecast-contingent financing for predetermined actions. However, its benefits are unclear due to the trade-off between acting early on uncertain forecasts and providing relief after certain losses. Since imperfect forecasts increase basis risk, anticipatory index-insurance can significantly exacerbate this trade-off. Using a stylized economic model and numerical analysis, we unpack the sources of value from anticipatory insurance and identify the range of economic conditions under which the product is beneficial. The primary benefit of anticipatory insurance comes from developing a country’s operational capacity to take forecast-based actions. However, the insurance mechanism's incremental benefit may not always outweigh premium costs due to basis risk when forecasts are imperfect. Our results can guide aid agencies and governments in designing the optimal financing plan for forecast-based anticipatory actions.