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Multivariate Zero-Inflated INAR(1) Model with an Application in Automobile Insurance

Author

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

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

  • Pengcheng Zhang & Zezhun Chen & George Tzougas & Enrique Calderín–Ojeda & Angelos Dassios & Xueyuan Wu, 2025. "Multivariate Zero-Inflated INAR(1) Model with an Application in Automobile Insurance," North American Actuarial Journal, Taylor & Francis Journals, vol. 29(2), pages 310-328, April.
    • Handle: RePEc:taf:uaajxx:v:29:y:2025:i:2:p:310-328
    DOI: 10.1080/10920277.2024.2381726
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