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Exploring the weather-yield nexus with artificial neural networks

Author

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  • Schmidt, Lorenz
  • Odening, Martin
  • Schlanstein, Johann
  • Ritter, Matthias

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.

Suggested Citation

  • Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:agisys:v:196:y:2022:i:c:s0308521x21002985
    DOI: 10.1016/j.agsy.2021.103345
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    References listed on IDEAS

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    1. Nordmeyer, Eike Florenz & Danne, Michael & Musshoff, Oliver, 2023. "Can satellite-retrieved data increase farmers' willingness to insure against drought? – Insights from Germany," Agricultural Systems, Elsevier, vol. 211(C).

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