Natural disasters cause significant economic losses and death tolls worldwide. In the United States alone, weather-related disasters have cost over $2.5 trillion in the past four decades, with increasing severity over time. Governments implement disaster risk reduction policies to mitigate these impacts by promoting avoidance behaviors, reducing exposure, and minimizing damage to people, crops, and property. However, critical questions remain understudied: Do these policies effectively reduce weather-related impacts? How can their efficacy be evaluated? What drives governments to terminate ineffective policies? This dissertation addresses these questions and provides insights for policymakers.The first chapter, “Tropical Cyclone Day-Off Orders, Warnings, and Avoidance Behavior,” examines Taiwan's day-off policy during tropical cyclones, which allows residents to avoid exposure to strong winds, landslides, and flooding. Using transportation data as a proxy for avoidance behavior, the analysis reveals that while mandatory day-off orders reduce exposure, people may take similar actions even without them. Comparing Taiwan with Miami-Dade County, Florida, the study finds similar avoidance patterns in areas without mandatory orders. These findings suggest that providing reliable information may allow individuals to make informed decisions, reducing unnecessary disruptions. The second chapter, “Efficacy Analysis of Cloud Seeding Programs in Kansas Agriculture,” evaluates cloud seeding as a hail suppression strategy for protecting crops in Kansas, a state prone to severe hailstorms. The findings show that cloud seeding reduces hailstorm intensity but does not significantly lower crop loss ratios, as hailstones remain large enough to cause damage. Additionally, cloud seeding unintentionally increases flood-related crop losses and exhibits spillover effects, reducing downwind counties’ sorghum productivity. Despite a positive net present value overall, these spillover effects lead to negative net present value in downwind counties, complicating the program's cost-benefit profile. The third chapter, “Factors Influencing Policy Termination,” investigates the determinants of policy termination using Kansas' cloud seeding program as a case study. Analysis reveals that counties experiencing higher hail-induced crop losses are more likely to terminate the program, reflecting its perceived inefficacy. Furthermore, neighboring counties' termination decisions delay the termination process, aligning with diffusion theory, which posits that governments learn from neighbors’ experiences. This study highlights the role of inefficacy and policy diffusion in driving termination decisions. In conclusion, this dissertation explores the effectiveness and sustainability of disaster risk reduction policies through the lens of two case studies: Taiwan’s tropical cyclone day-off orders and Kansas’ cloud seeding program. The findings emphasize the importance of rigorous evaluation to improve policy design and highlight the need for continued research into innovative risk reduction strategies to enhance resilience against natural disasters.
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