Get in the Zone: The Risk-Adjusted Welfare Effects of Machine Learning to Define Index Insurance Zones
Elinor Benami, Virginia Polytechnic Institute and State University, Agricultural and Applied Economics, Blacksburg, United States, Andrew Hobbs, University of San Francisco, San Francisco, CA, United States, Michael Carter, University of California Davis, Agricultural and Resource Economics, Davis, CA, United States and Zhenong Jin, University of Minnesota Twin Cities, Department of Bioproducts and Biosystems Engineering, Saint Paul, United States
