Accounting for short samples and heterogeneous experience in rating crop insurance
Abstract
Purpose
The purpose of this paper is to be an academic inquiry into rating issues confronted by the US Federal Crop Insurance program stemming from changes in participation rates as well as the weighting of data to reflect longer‐run weather patterns.
Design/methodology/approach
The authors investigate two specific approaches that differ from those adopted by the Risk Management Agency, building upon standard maximum likelihood and Bayesian estimation techniques that consider parametric densities for the loss‐cost ratio.
Findings
Both approaches indicate that incorporating weights into the priors for Bayesian estimation can inform the distribution.
Originality/value
In most cases, the authors' results indicate that including weighting into priors for Bayesian estimation implied lower premium rates than found using standard methods.
Keywords
Citation
Borman, J.I., Goodwin, B.K., Coble, K.H., Knight, T.O. and Rejesus, R. (2013), "Accounting for short samples and heterogeneous experience in rating crop insurance", Agricultural Finance Review, Vol. 73 No. 1, pp. 88-101. https://doi.org/10.1108/00021461311321339
Publisher
:Emerald Group Publishing Limited
Copyright © 2013, Emerald Group Publishing Limited