Combing Spatial and Time Series Information to Rate Crop Insurance

Yuan Zhang and B Brorsen

No 361061, 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO from Agricultural and Applied Economics Association

Abstract: This study estimated crop yield distribution using Bayesian spatial-temporal models for Oklahoma hay and Iowa corn, focusing on the influence of historical data spans on model performance. Both data sets had strong spatial patterns with yields increasing from south-to-north for Iowa corn and increasing from west-to-east for Oklahoma hay. The out-of-sample fit for the spatial models did not exceed the models that ignored spatial information. For the spatial-temporal models, time spans at or near the longest available provided the best fit. When trend was modeled separately, time spans of fifteen years provided the best fit. The results show that spatial information did not serve as a substitute for long time-series of data in modeling crop yield distributions.

Keywords: Production; Economics (search for similar items in EconPapers)
Pages: 40
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea25:361061

DOI: 10.22004/ag.econ.361061

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