Simultaneous borrowing of information across space and time for pricing insurance contracts : an application to rating crop insurance policies

Recurso electrónico / Electronic resource
MARC record
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008  210219e20210301usa|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎329
100  ‎$0‎MAPA20210003226‎$a‎Liu, Yong
24510‎$a‎Simultaneous borrowing of information across space and time for pricing insurance contracts‎$b‎: an application to rating crop insurance policies‎$c‎Yong Liu, Alan P. Ker
520  ‎$a‎Changing 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 datadriven 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.
650 4‎$0‎MAPA20080587857‎$a‎Seguro de cosechas
650 4‎$0‎MAPA20080586294‎$a‎Mercado de seguros
650 4‎$0‎MAPA20080548575‎$a‎Pérdidas
650 4‎$0‎MAPA20080584290‎$a‎Contrato de seguro
650 4‎$0‎MAPA20080578350‎$a‎Tarifa de primas
7001 ‎$0‎MAPA20210003745‎$a‎Ker, Alan P.
7730 ‎$w‎MAP20077000727‎$t‎The Journal of risk and insurance‎$d‎Nueva York : The American Risk and Insurance Association, 1964-‎$x‎0022-4367‎$g‎01/03/2021 Volumen 88 Número 1 - marzo 2021 , p. 231-257