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Multivariate zero-inflated INAR(1) model with an application in automobile insurance

Author

Listed:
  • Zhang, Pengcheng
  • Chen, Zezhun
  • Tzougas, George
  • Calderín–Ojeda, Enrique
  • Dassios, Angelos
  • Wu, Xueyuan

Abstract

The objective of this article is to propose a comprehensive solution for analyzing multidimensional non-life claim count data that exhibits time and cross-dependence, as well as zero inflation. To achieve this, we introduce a multivariate INAR(1) model, with the innovation term characterized by either a multivariate zero-inflated Poisson distribution or a multivariate zero-inflated hurdle Poisson distribution. Additionally, our modeling framework accounts for the impact of individual and coverage-specific covariates on the mean parameters of each model, thereby facilitating the computation of customized insurance premiums based on varying risk profiles. To estimate the model parameters, we employ a novel expectation-maximization (EM) algorithm. Our model demonstrates satisfactory performance in the analysis of European motor third-party liability claim count data.

Suggested Citation

  • Zhang, Pengcheng & Chen, Zezhun & Tzougas, George & Calderín–Ojeda, Enrique & Dassios, Angelos & Wu, Xueyuan, 2024. "Multivariate zero-inflated INAR(1) model with an application in automobile insurance," LSE Research Online Documents on Economics 124317, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:124317
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    References listed on IDEAS

    as
    1. Chai Fung, Tsz & Badescu, Andrei L. & Sheldon Lin, X., 2019. "A Class Of Mixture Of Experts Models For General Insurance: Application To Correlated Claim Frequencies," ASTIN Bulletin, Cambridge University Press, vol. 49(3), pages 647-688, September.
    2. Jean‐Philippe Boucher & Michel Denuit & Montserrat Guillen, 2009. "Number of Accidents or Number of Claims? An Approach with Zero‐Inflated Poisson Models for Panel Data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(4), pages 821-846, December.
    3. Bermúdez, Lluís & Guillén, Montserrat & Karlis, Dimitris, 2018. "Allowing for time and cross dependence assumptions between claim counts in ratemaking models," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 161-169.
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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