Weather risk, amplified by climate change, is posing an increasingly severe threat to agricultural production. Index insurance is a promising tool to hedge against weather risk, but traditional contracts face key limitations. Tapping into recent advances in machine learning, HKUST’s Zhanhui Chen and colleagues introduce a novel method of managing weather risk: integrating neural networks into the design of index insurance contracts.

Unpredictable weather conditions, such as floods and droughts, can have a devastating impact on farmers, who depend on weather conditions for agricultural production. Indeed, “70%–90% of agricultural production loss can be attributed to adverse weather,” note the researchers.

Currently, the best risk-management tool available to farmers is weather index insurance, whose payoff is based on prespecified weather parameters rather than actual losses. However, this approach suffers from high basis risk (“the risk that the underlying indices and actual losses are mismatched”) and consequently low demand among farmers. “This paper attempts to address the above issues to design better index insurance contracts,” say the authors.

To do so, they consider two key characteristics of crop production: its dependence on high-dimensional weather conditions and the nonlinear nature of this dependence. Using cutting-edge machine learning techniques, the authors develop an innovative index insurance design based on neural networks (NNs), which “help to capture high-dimensional, nonlinear, and complex interactions between weather indices and production losses.”

Testing their novel model in a real-life setting, corn production in Illinois, the authors find that it is indeed superior to traditional index insurance contracts. “The NN-based index insurance contract effectively reduces basis risk and greatly outperforms other contracts,” they report.

“Our framework can be easily extended to designing other weather risk management solutions,” the authors note. It thus has the potential to enhance farmers’ resilience in the face of unpredictable weather conditions, with important economic implications in today’s era of climate change.