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Using quantile regression for rate-making

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  • Kudryavtsev, Andrey A.

Abstract

Regression models are popular tools for rate-making in the framework of heterogeneous insurance portfolios; however, the traditional regression methods have some disadvantages particularly their sensitivity to the assumptions which significantly restrict the area of their applications. This paper is devoted to an alternative approach-quantile regression. It is free of some disadvantages of the traditional models. The quality of estimators for the approach described is approximately the same as or sometimes better than that for the traditional regression methods. Moreover, the quantile regression is consistent with the idea of using the distribution quantile for rate-making. This paper provides detailed comparisons between the approaches and it gives the practical example of using the new methodology.

Suggested Citation

  • Kudryavtsev, Andrey A., 2009. "Using quantile regression for rate-making," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 296-304, October.
    • Handle: RePEc:eee:insuma:v:45:y:2009:i:2:p:296-304
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    References listed on IDEAS

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    Cited by:

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    8. Liang Yang & Zhengxiao Li & Shengwang Meng, 2020. "Risk Loadings in Classification Ratemaking," Papers 2002.01798, arXiv.org, revised Jan 2022.
    9. Idrissa Ouedraogo & Issa Dianda & Pegdwende Patrik Roland Ouedraogo & Tiraogo Rodrigue Ouedraogo & Bassirou Konfe, 2025. "The Effects of Taxation on Income Inequality in Sub-Saharan Africa," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 67(1), pages 84-149, March.
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