Risk Measuring Model on Public Liability Fire and Empirical Study in China

Guo-Xue Gu; Shang-Mei Zhao

doi:10.20965/jdr.2014.p0035

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JDR Vol.9 No.1 pp. 35-41

(2014)

doi: 10.20965/jdr.2014.p0035

Paper:

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Risk Measuring Model on Public Liability Fire and Empirical Study in China

Guo-Xue Gu and Shang-Mei Zhao

School of Economics and Management, Beijing University of Aeronautics and Astronautics, Xueyuan road 37, Haidian District, Beijing 100191, P.R.China

Received:

September 17, 2013

Accepted:

January 13, 2014

Published:

February 1, 2014

Keywords:

public liability fires risk, bandwidth, GLM, gaussian kernel

Abstract

Public fire insurance has recently appeared in China. The basis for calculating the premium is the accurate measurement of Publicliability risk in fire. The generalized linear model (GLM) is widely used for measuring this risk in practice, but the GLM often cannot be satisfied, especially in fat-tailed distribution. A nonparametric Gaussian kernel linear model used to improve the GLM is applied to measure publicliability risk in fire, yielding a favorable effect. Results show three major risk factors that were measured precisely – the nature of the industry, the scale of public places and the level of fire precaution.

Cite this article as:

G. Gu and S. Zhao, “Risk Measuring Model on Public Liability Fire and Empirical Study in China,” J. Disaster Res., Vol.9 No.1, pp. 35-41, 2014.

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References

[1] Q. C. Huang and X. P. Liu, “Imposing the public liability insurance of fires,” People’s Daily, October 28, 2008.
[2] J. C. Tang, “the public fire liability insurance participating in social management,” Chinese Insurance, Issue 2, pp. 39-42, 2012.
[3] S. M. Zhao and G. X. Gu, “Research on Risk Security Mechanism of the Public Liability Insurance of Fires,” Insurance Research, Issue 9, pp. 92-97, 2012.
[4] Y. C. Wang, “the analysis report about Chinese property insurance in disaster accident,” China Financial and Economic Publish House, 2008.
[5] Z. Gu, H. K. Jiang and B. J. Chu, “Wavelet-nonparametric estimation method in the premium rating of agricultural insurance,” Systems Engineering, Issue 8, pp. 39-43, 2008.
[6] S. J. Mildenhall, “A systematic relationship between minimum bias and generalized linear models,” Proc. of the Casualty Actuarial Society, Vol.86, pp. 393-487, 1999.
[7] L. Yan and S. W. Meng, “Comparative study of non-life classification rate marking models and their application,” Applications of Statistics and Management, Vol.30, Issue 1, pp. 162-168, 2011.
[8] S. W. Meng, “An application of generalized linear model to auto motor insurance pricing,” Applications of Statistics and Management, Vol.26, Issue 1, pp. 24-29, 2007.
[9] A. P. Ker and B. K. Goodwin, “Nonparametric estimation of crop insurance rates revisited,” American Journal of Agricultural Economics, Vol.83, pp. 463-478, 2000.
[10] S. Feldblum and J. E. Brosius, “The minimum bias procedure: A practitioner’s guide,” Proc. of the casualty Actuarial society, Vol.90, pp. 196-273, 2003.
[11] H. Z. Gao, “Analysis of the rate level in traffic insurance,” Statistics and Decision, Issue 7, pp. 12-14, 2008.
[12] K. Du, G. Liu and G. D. Gu, “A class of control variates for pricing Asian options under stochastic volatility models,” IAENG Int. Journal of Applied Mathematics, Vol.43, Issue 2, pp. 45-53, 2013.
[13] D. R. Brillinger, “A Generalized Linear Model with Gaussian Regressor Variables,” Probability and Statistics, pp. 589-606, 2012.
[14] E. Ufuah and T. H. Tashok, “behaviour of stiffened steel plates subjected to accidental loadings,” Engineering Letters, Vol.21, Issue 2, 2013.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] Q. C. Huang and X. P. Liu, “Imposing the public liability insurance of fires,” People’s Daily, October 28, 2008.

[2] [2] J. C. Tang, “the public fire liability insurance participating in social management,” Chinese Insurance, Issue 2, pp. 39-42, 2012.

[3] [3] S. M. Zhao and G. X. Gu, “Research on Risk Security Mechanism of the Public Liability Insurance of Fires,” Insurance Research, Issue 9, pp. 92-97, 2012.

[4] [4] Y. C. Wang, “the analysis report about Chinese property insurance in disaster accident,” China Financial and Economic Publish House, 2008.

[5] [5] Z. Gu, H. K. Jiang and B. J. Chu, “Wavelet-nonparametric estimation method in the premium rating of agricultural insurance,” Systems Engineering, Issue 8, pp. 39-43, 2008.

[6] [6] S. J. Mildenhall, “A systematic relationship between minimum bias and generalized linear models,” Proc. of the Casualty Actuarial Society, Vol.86, pp. 393-487, 1999.

[7] [7] L. Yan and S. W. Meng, “Comparative study of non-life classification rate marking models and their application,” Applications of Statistics and Management, Vol.30, Issue 1, pp. 162-168, 2011.

[8] [8] S. W. Meng, “An application of generalized linear model to auto motor insurance pricing,” Applications of Statistics and Management, Vol.26, Issue 1, pp. 24-29, 2007.

[9] [9] A. P. Ker and B. K. Goodwin, “Nonparametric estimation of crop insurance rates revisited,” American Journal of Agricultural Economics, Vol.83, pp. 463-478, 2000.

[10] [10] S. Feldblum and J. E. Brosius, “The minimum bias procedure: A practitioner’s guide,” Proc. of the casualty Actuarial society, Vol.90, pp. 196-273, 2003.

[11] [11] H. Z. Gao, “Analysis of the rate level in traffic insurance,” Statistics and Decision, Issue 7, pp. 12-14, 2008.

[12] [12] K. Du, G. Liu and G. D. Gu, “A class of control variates for pricing Asian options under stochastic volatility models,” IAENG Int. Journal of Applied Mathematics, Vol.43, Issue 2, pp. 45-53, 2013.

[13] [13] D. R. Brillinger, “A Generalized Linear Model with Gaussian Regressor Variables,” Probability and Statistics, pp. 589-606, 2012.

[14] [14] E. Ufuah and T. H. Tashok, “behaviour of stiffened steel plates subjected to accidental loadings,” Engineering Letters, Vol.21, Issue 2, 2013.