On the ordering of credibility factors
- 주제(키워드) Dependence , Posterior ratemaking , Credibility , Auto insurance , Time series , Dynamic random effects
- 주제(기타) Economics
- 주제(기타) Mathematics, Interdisciplinary Applications
- 주제(기타) Social Sciences, Mathematical Methods
- 주제(기타) Statistics & Probability
- 설명문(일반) [Ahn, Jae Youn] Ewha Womans Univ, Dept Stat, Seoul, South Korea; [Jeong, Himchan] Simon Fraser Univ, Dept Stat & Actuarial Sci, Burnaby, BC, Canada; [Lu, Yang] Concordia Univ, Dept Math & Stat, Montreal, PQ, Canada
- 등재 SCIE, SSCI, SCOPUS
- OA유형 Green Submitted
- 발행기관 ELSEVIER
- 발행년도 2021
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000191075
- 본문언어 영어
- Published As https://doi.org/10.1016/j.insmatheco.2021.10.005
초록/요약
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. (C) 2021 Elsevier B.V. All rights reserved.
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