Date of Award


Document Type


Degree Name

Master of Science (MS)



Committee Chair/Advisor

Dr. Matthew Lewis

Committee Member

Dr. Babur de Los Santos

Committee Member

Dr. Anastasia Thayer


Weather index-based crop insurance has promised to be a lifeline for low-income farmers in developing countries. However, high-basis risk, high administration costs, and low willingness to pay have caused the demise of many pilot programs. Building onto the principles of index insurance we propose Climate Insurance, a new form of insurance based on predictive crop models that overcomes most of the primary objections of index insurance while achieving its goals of low administration costs, greatly reduced adverse selection, and the elimination of moral hazard. The crop model presented herein utilizes an artificial neural network to predict county- level yield per acre given only weather data for a growing season and the previous high yield. This model was developed using 93 years of historical NOAA weather and USDA corn yield data for 53 counties in Iowa, though we believe it to be fully transferrable to other locations and crops. It has an RMSE of only 12.47 for 2022 weather data and an RRMSE of 6.4%.

Available for download on Saturday, May 31, 2025