Exploring the weather-yield nexus with artificial neural networks

Lorenz Schmidt, Martin Odening, Johann Schlanstein and Matthias Ritter

Agricultural Systems, 2022, vol. 196, issue C

Abstract: Weather is a pivotal factor for crop production as it is highly volatile and can hardly be controlled by farm management practices. Since there is a tendency towards increased weather extremes in the future, understanding weather-related yield factors becomes increasingly important not only for yield prediction, but also for the design of insurance products. Although insurance products mitigate financial losses for farmers, they suffer from considerable basis risk, i.e., a discrepancy between losses and the indemnity payment.

Keywords: Yield prediction; Machine learning; Weather risk; Index insurance; Basis risk (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:196:y:2022:i:c:s0308521x21002985

DOI: 10.1016/j.agsy.2021.103345

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