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Premium Rating by Geographic Area Using Spatial Models

Author

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  • Boskov, M.
  • Verrall, R. J.

Abstract

This paper gives a method for premium rating by postcode area. The method is based on spatial models in a Bayesian framework and uses the Gibbs sampler for estimation. A summary of the theory of Bayesian spatial methods is given and the data which was analysed by Taylor (1989) is reanalysed. An indication is given of the wide range of models within this class which would be suitable for insurance data. The aim of the paper is to introduce the models and to show how they can be utilised in an insurance setting.

Suggested Citation

  • Boskov, M. & Verrall, R. J., 1994. "Premium Rating by Geographic Area Using Spatial Models," ASTIN Bulletin, Cambridge University Press, vol. 24(1), pages 131-143, May.
    • Handle: RePEc:cup:astinb:v:24:y:1994:i:01:p:131-143_00
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    Cited by:

    1. Denuit, Michel & Lang, Stefan, 2004. "Non-life rate-making with Bayesian GAMs," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 627-647, December.
    2. Yves L. Grize, 2015. "Applications of Statistics in the Field of General Insurance: An Overview," International Statistical Review, International Statistical Institute, vol. 83(1), pages 135-159, April.
    3. Kamil Gala, 2018. "The a priori risk classification with spatial autocorrelation in automobile insurance," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 51, pages 147-168.

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