PL EN


Journal
2013 | 1(39) | 144-151
Article title

Zero-inflated claim count modeling and testing – a case study

Content
Title variants
Languages of publication
EN
Abstracts
EN
In this paper the application of parametric count data models in claim counts modeling is investigated. Insurance portfolios have a very specific characteristic, i.e. for many policies there are no claims observed in the insurance history for a given period of time. As the zero-inflation and over-dispersion effects are a common situation in insurance portfolios, three models: zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB) and zeroinflated generalized Poisson regression (ZIGP) are tested against the classic Poisson model. The 4-step procedure for modeling zero-inflation effect is proposed. This procedure is applied in the case study. For all calculations the R CRAN software was used.
Keywords
EN
claim counts   ZIP   ZINB   ZIGP  
Journal
Year
Issue
Pages
144-151
Physical description
Dates
published
2013
Contributors
  • Uniwersytet Ekonomiczny w Katowicach
References
  • De Jong P., Heller G.Z. (2008), Generalized Linear Models for Insurance Data, Cambridge University Press, Cambridge.
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  • Vuong Q. (1989), Likelihood ratio tests for model selection and non-nested hypotheses, Econometrica 57: 307–33.
  • Wolny-Dominiak A. (2011), Zmodyfikowana regresja Poissona dla danych ubezpieczeniowych z dużą liczbą zer, [in:] Prognozowanie w zarządzaniu firmą, Prace Naukowe Uniwersytetu Ekonomicznego nr 185, pp. 21–30.
  • Yang Z., Hardin J.W., Addy Ch.L. (2009), Testing over-dispersion in the zero-inflated Poisson model, Journal of Statistical Planning and Inference 139: 3340–3353.
  • Yip K.C.H.,Yau K.K.W. (2005), On modeling claim frequency data in general insurance with extra zeros, Insurance: Mathematics and Economics 36: 153–163.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-6742d61b-1984-44a4-a114-3dc98d345295
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