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Estimation and Testing for Functional Form in Pure Premium Regression Models

Published online by Cambridge University Press:  29 August 2014

Scott E. Harrington
Scott E. Harrington*
Affiliation:
University of Pennsylvania
*
Insurance Department, Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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Abstract

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Estimation of pure premiums for alternative rate classes using regression methods requires the choice of a functional form for the statistical model. Common choices include linear and log-linear models. This paper considers maximum likelihood estimation and testing for functional form using the power transformation suggested by Box and Cox. The linear and log-linear models are special cases of this transformation. Application of the procedure is illustrated using auto insurance claims data from the state of Massachusetts and from the United Kingdom. The predictive accuracy of the method compares favorably to that for the linear and log-linear models for both data sets.

Keywords

Pure premium regression modelsfunctional formmaximum likelihood estimationpower transformation
Type
Astin Competition 1985: Prize-Winning Papers and Other Selected Papers
Information
ASTIN Bulletin: The Journal of the IAA , Volume 16 , Issue S1 , April 1986 , pp. S31 - S43
Copyright
Copyright © International Actuarial Association 1986

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