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Long-tail longitudinal modeling of insurance company expenses

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  • Shi, Peng
  • Frees, Edward W.
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    Abstract

    The insurance industry is known to have high operating expenses in the financial services sector. Insurers, investors and regulators are interested in models to understand the behavior of expenses. However, the current practice ignores skewness, occasional negative values as well as their temporal dependence. Addressing these three features, this paper develops a longitudinal model of insurance company expenses that can be used for prediction, to identify unusual behavior, and to measure firm efficiency. Specifically, we use a three-parameter asymmetric Laplace density for the marginal distribution of insurers' expenses in each year. Copula functions are employed to accommodate their temporal dependence. As a function of explanatory variables, the location parameter allows us to analyze an insurer's expenses in light of the firm's characteristics. Our model can be interpreted as a longitudinal quantile regression. The analysis is performed using property-casualty insurance company data from the National Association of Insurance Commissioners of years 2001-2006. Due to the long-tailed nature of insurers' expenses, two alternative approaches are proposed to improve the performance of the longitudinal quantile regression model: rescaling and transformation. Predictive densities are derived that allow one to compare the predictions for individual insurers in a hold-out-sample. Both predictive models are shown to be reasonable with the rescaling method outperforming the transformation method. Compared with standard longitudinal models, our model is shown to be superior in identifying insurers' unusual behavior.

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    Bibliographic Info

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

    Volume (Year): 47 (2010)
    Issue (Month): 3 (December)
    Pages: 303-314

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    Handle: RePEc:eee:insuma:v:47:y:2010:i:3:p:303-314

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

    Related research

    Keywords: IM01 IM20 Long-tail regression Copulas Quantile regression Asymmetric Laplace distribution Transformation;

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    References

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    1. Yin, Guosheng & Zeng, Donglin & Li, Hui, 2008. "Power-Transformed Linear Quantile Regression With Censored Data," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1214-1224.
    2. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, April.
    3. Roger Koenker & Zhijie Xiao, 2004. "Unit Root Quantile Autoregression Inference," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 775-787, January.
    4. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    5. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    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. 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.
    8. Fenn, Paul & Vencappa, Dev & Diacon, Stephen & Klumpes, Paul & O'Brien, Chris, 2008. "Market structure and the efficiency of European insurance companies: A stochastic frontier analysis," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 86-100, January.
    9. Mu, Yunming & He, Xuming, 2007. "Power Transformation Toward a Linear Regression Quantile," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 269-279, March.
    10. F. Fecher & D. Kessler & S. Perelman & P. Pestieau, 1993. "Productive performance of the French insurance industry," Journal of Productivity Analysis, Springer, vol. 4(1), pages 77-93, June.
    11. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    12. Roger Koenker & Zhijie Xiao, 2002. "Inference on the Quantile Regression Process," Econometrica, Econometric Society, vol. 70(4), pages 1583-1612, July.
    13. Gardner, Lisa A. & Grace, Martin F., 1993. "X-Efficiency in the US life insurance industry," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 497-510, April.
    14. Cummins, J. David & Weiss, Mary A., 1993. "Measuring cost efficiency in the property-liability insurance industry," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 463-481, April.
    15. 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.
    16. Toivanen, Otto, 1997. "Economies of scale and scope in the Finnish non-life insurance industry," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 759-779, June.
    17. Lindsey, J.K. & Lindsey, P.J., 2006. "Multivariate distributions with correlation matrices for nonlinear repeated measurements," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 720-732, February.
    18. Bali, Turan G., 2003. "The generalized extreme value distribution," Economics Letters, Elsevier, vol. 79(3), pages 423-427, June.
    19. J. David Cummins & Mary A. Weiss, 1998. "Analyzing Firm Performance in the Insurance Industry Using Frontier Efficiency Methods," Center for Financial Institutions Working Papers 98-22, Wharton School Center for Financial Institutions, University of Pennsylvania.
    20. Turan G. Bali & Panayiotis Theodossiou, 2008. "Risk Measurement Performance of Alternative Distribution Functions," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(2), pages 411-437.
    21. Frees, Edward W. & Wang, Ping, 2006. "Copula credibility for aggregate loss models," Insurance: Mathematics and Economics, Elsevier, vol. 38(2), pages 360-373, April.
    22. Zimmer, David M. & Trivedi, Pravin K., 2006. "Using Trivariate Copulas to Model Sample Selection and Treatment Effects: Application to Family Health Care Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 63-76, January.
    23. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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    Cited by:
    1. Shi, Peng, 2012. "Multivariate longitudinal modeling of insurance company expenses," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 204-215.
    2. 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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