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Multivariate longitudinal modeling of insurance company expenses

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  • Shi, Peng
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    Abstract

    Insurers, investors and regulators are interested in understanding the behavior of insurance company expenses, due to the high operating cost of the industry. Expense models can be used for prediction, to identify unusual behavior, and to measure firm efficiency. Current literature focuses on the study of total expenses that consist of three components: underwriting, investment and loss adjustment. A joint study of expenses by type is to deliver more information and is critical in understanding their relationship.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0167668711000928
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    Bibliographic Info

    Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

    Volume (Year): 51 (2012)
    Issue (Month): 1 ()
    Pages: 204-215

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    Handle: RePEc:eee:insuma:v:51:y:2012:i:1:p:204-215

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    Web page: http://www.elsevier.com/locate/inca/505554

    Related research

    Keywords: Multivariate longitudinal model; Long-tail regression; Elliptical copula; Asymmetric Laplace distribution;

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    References

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    1. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
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    3. Cornwell, Christopher & Schmidt, Peter & Wyhowski, Donald, 1992. "Simultaneous equations and panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 151-181.
    4. Christian Genest & Jean-François Quessy & Bruno Rémillard, 2006. "Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 33(2), pages 337-366.
    5. Scaillet, Olivier, 2007. "Kernel-based goodness-of-fit tests for copulas with fixed smoothing parameters," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 533-543, March.
    6. Sun, Jiafeng & Frees, Edward W. & Rosenberg, Marjorie A., 2008. "Heavy-tailed longitudinal data modeling using copulas," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 817-830, April.
    7. Frees, Edward W. & Valdez, Emiliano A., 2008. "Hierarchical Insurance Claims Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1457-1469.
    8. Cambanis, Stamatis & Huang, Steel & Simons, Gordon, 1981. "On the theory of elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 11(3), pages 368-385, September.
    9. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    10. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    11. Shi, Peng & Frees, Edward W., 2010. "Long-tail longitudinal modeling of insurance company expenses," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 303-314, December.
    12. Baltagi, Badi H., 1981. "Simultaneous equations with error components," Journal of Econometrics, Elsevier, vol. 17(2), pages 189-200, November.
    13. Prucha, Ingmar R, 1984. "On the Asymptotic Efficiency of Feasible Aitken Estimators for Seemingly Unrelated Regression Models with Error Components," Econometrica, Econometric Society, vol. 52(1), pages 203-07, January.
    14. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    15. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
    16. Balestra, Pietro & Varadharajan-Krishnakumar, Jayalakshmi, 1987. "Full Information Estimations of a System of Simultaneous Equations with Error Component Structure," Econometric Theory, Cambridge University Press, vol. 3(02), pages 223-246, April.
    17. Klugman, Stuart A. & Parsa, Rahul, 1999. "Fitting bivariate loss distributions with copulas," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 139-148, March.
    18. Prucha, Ingmar R, 1985. "Maximum Likelihood and Instrumental Variable Estimation in Simultaneous Equation Systems with Error Components," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(2), pages 491-506, June.
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    Cited by:
    1. Shi, Peng & Valdez, Emiliano A., 2014. "Multivariate negative binomial models for insurance claim counts," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 18-29.

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