On the ordering of credibility factors

Jae Youn Ahn, Himchan Jeong and Yang Lu

Insurance: Mathematics and Economics, 2021, vol. 101, issue PB, 626-638

Abstract: Traditional credibility analysis of risks in insurance is based on the random effects model, where the heterogeneity across the policyholders is assumed to be time-invariant. One popular extension is the dynamic random effects (or state-space) model. However, while the latter allows for time-varying heterogeneity, its application to the credibility analysis should be conducted with care due to the possibility of negative credibilities per period [see Pinquet (2020a)]. Another important but under-explored topic is the ordering of the credibility factors in a monotonous manner—recent claims ought to have larger weights than the old ones. This paper shows that the ordering of the covariance structure of the random effects in the dynamic random effects model does not necessarily imply that of the credibility factors. Subsequently, we show that the state-space model, with AR(1)-type autocorrelation function, guarantees the ordering of the credibility factors. Simulation experiments and a case study with a real dataset are conducted to show the relevance in insurance applications.

Keywords: Dependence; Posterior ratemaking; Credibility; Auto insurance; Time series; Dynamic random effects (search for similar items in EconPapers)
JEL-codes: C30 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:101:y:2021:i:pb:p:626-638

DOI: 10.1016/j.insmatheco.2021.10.005

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