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Utilizing Topographic and Soil Features to Improve Rating for Farm‐Level Insurance Products
Author(s) -
Tsiboe Francis,
Tack Jesse
Publication year - 2022
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/ajae.12218
Subject(s) - crop insurance , yield (engineering) , agriculture , sorghum , agricultural economics , business , environmental science , agricultural science , agricultural engineering , economics , geography , forestry , engineering , materials science , archaeology , metallurgy
Previous studies have shown a strong correlation between topographic/soil features and agricultural production; however, linkages between these features and agricultural insurance products are scarce. Agricultural insurance is an ever‐growing means of governmental support for producers globally. However, failure to set insurance premiums that accurately reflect risk exposure can lead to low participation rates and/or adverse selection. The U.S. federal crop insurance program partly guards against this at the farm level by inducing pricing heterogeneity via a rate multiplier curve, which does not consider topographic/soil information. We develop a method for econometrically incorporating this information into existing rating procedures used by the Risk Management Agency (RMA). The empirical application leverages 149,267 farm‐level observations of Kansas producers across four dryland crops (corn, soybean, sorghum, and wheat), spanning forty‐six years, and matched to fine‐scale topographic/soil features. The results suggest that incorporating these features does improve the prediction accuracy of yield losses and can, in general, improve rating performance. However, these improvements are specific to farms with limited yield histories, as there are no improvements for farms with the commonly used yield history of ten years. This suggests substantial rating improvements for new farms or those with limited histories for a particular crop, but more general improvements for the program are not likely to occur given a large number of current participants with a full ten‐year yield history.