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Semi‐Parametric Specification Tests for Discrete Probability Models

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  • Yue Fang

Abstract

Loss functions play an important role in analyzing insurance portfolios. A fundamental issue in the study of loss functions involves the selection of probability models for claim frequencies. In this article, we propose a semi‐parametric approach based on the generalized method of moments (GMM) to solve the specification problems concerning claim frequency distributions. The GMM‐based testing procedure provides a general framework that encompasses many specification problems of interest in actuarial applications. As an alternative approach to the Pearson χ2 and other goodness‐of‐fit tests, it is easy to implement and should be of practical use in applications involving selecting and validating probability models with complex characteristics.

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  • Yue Fang, 2003. "Semi‐Parametric Specification Tests for Discrete Probability Models," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(1), pages 73-84, March.
    • Handle: RePEc:bla:jrinsu:v:70:y:2003:i:1:p:73-84
    DOI: 10.1111/1539-6975.00048
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    1. Fang, Yue, 2008. "Semi-parametric specification tests for mixing distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2829-2839, January.

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