Discrete distributions when modeling the disability severity score of motor victims

Jean Philippe Boucher () and Miguel Santolino ()
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Jean Philippe Boucher: Université du Québec à Montréal
Miguel Santolino: Faculty of Economics, University of Barcelona

No 201005, IREA Working Papers from University of Barcelona, Research Institute of Applied Economics

Abstract: Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

Keywords: Hurdle discrete data models; zero-inflated distribution; generalized method of moments; personal injuries; disability rating scale. JEL classification:- (search for similar items in EconPapers)
Pages: 35 pages
Date: 2010-02, Revised 2010-02
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:ira:wpaper:201005

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