Reports Summarize Crop Insurance Findings from Virginia Polytechnic Institute and State University (Virginia Tech) (Linear Pooling of Potentially Related Density Forecasts In Crop Insurance): Agriculture – Crop Insurance

2023 JUL 04 (NewsRx) -- By a News Reporter-Staff News Editor at Agriculture Daily -- Data detailed on Agriculture - Crop Insurance have been presented. According to news reporting originating in Blacksburg, Virginia, by NewsRx journalists, research stated, “Accurate pricing of crop insurance policies relies on forecasts of probability densities of crop yields. Yield densities are dynamic, time series data on yields are often limited, and yield data are spatially correlated.”

The news reporters obtained a quote from the research from Virginia Polytechnic Institute and State University (Virginia Tech), “We examine linear pooling of potentially related, but almost surely misspecified, crop yield density forecasts. The pooled forecasts combine densities from other spatial units based on out-of-sample forecast performance. The pooled densities result in more accurate premium rates which can reduce incentives for adverse selection.”

According to the news reporters, the research concluded: “The approach is applicable to any insurance setting where the statistical model for the loss variable is likely to be misspecified and the underlying data-generating processes are potentially related.”

This research has been peer-reviewed.

For more information on this research see: Linear Pooling of Potentially Related Density Forecasts In Crop Insurance. Journal of Risk & Insurance, 2023. Journal of Risk & Insurance can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Risk & Insurance - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6975)

Our news correspondents report that additional information may be obtained by contacting A. Ford Ramsey, Virginia Polytechnic Institute, Dept. of Agricultural and Applied Economics, Blacksburg, VA, United States.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jori.12430. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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