Managing Weather Risk with a Neural Network-Based Index Insurance
Nanyang Business School Research Paper No. 20-28
78 Pages Posted: 24 Mar 2020 Last revised: 24 Aug 2021
Date Written: February 17, 2020
Weather risk affects economy, agricultural production in particular. Index insurance is a promising tool to hedge against weather risk, but current piecewise-linear index insurance contracts face large basis risk and low demand. We propose embedding a neural network-based optimization scheme into an expected utility maximization problem to design the index insurance contract. Neural networks capture highly nonlinear relationship between the high-dimensional weather variables and production losses. We endogenously solve for the optimal insurance premium and demand. This approach reduces basis risk, lowers insurance premium, and increases farmers' utility. Our approach can be generalized to design other financial products.
Keywords: weather risk; index insurance; basis risk; neural networks; machine learning
JEL Classification: C45, G11, G22, G52, O13, Q54
Suggested Citation: Suggested Citation