 Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policiesYong Liu and Alan P. Ker Journal of Risk & Insurance, 2021, vol. 88, issue 1, 231-257 Abstract: Changing climate and technology can often lead to nonstationary losses across both time and space for a variety of insurance lines including property, catastrophe, health, and life. As a result, naive estimation of premium rates using past losses will tend to be biased. We present three successively flexible data‐driven methodologies to nonparametrically smooth across both space and time simultaneously, thereby appropriately incorporating possibly nonidentically distributed data into the rating process. We apply these methodologies in estimating U.S. crop insurance premium rates. Crop insurance, with global premiums totaling $4.1 trillion in 2018, is an interesting application as losses exhibit both temporal and spatial nonstationarity. We find significant borrowing of information across both time and space. We also find all three methodologies improve both the stability and accuracy of crop insurance premium rates. The proposed methods may be of relevance for other lines of insurance characterized by spatial and/or temporal nonstationary losses. Date: 2021 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jrinsu:v:88:y:2021:i:1:p:231-257 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Risk & Insurance is currently edited by Joan T. Schmit More articles in Journal of Risk & Insurance from The American Risk and Insurance Association Contact information at EDIRC. |
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