East Asian mathematical journal

  • 제38권5호
  • /
  • Pages.617-641
  • /
  • 2022
  • /
  • 1226-6973(pISSN)
  • /
  • 2287-2833(eISSN)
영남수학회 (The Youngnam Mathematical Society)
권호 표지
DOI QR코드

DOI QR Code

AN INVESTIGATION OF THE KOREAN GENERAL INSURANCE INDUSTRY: EVIDENCE OF STRUCTURAL CHANGES AND IMPACT OF MACRO-ECONOMIC FACTORS ON LOSS RATIOS

  • Thompson, Ephraim Kwashie (Department of Business Administration, Seoul National University of Science and Technology) ;
  • Kim, So-Yeun (Department of Business Administration, Seoul National University of Science and Technology)
  • 투고 : 2022.04.25
  • 심사 : 2022.07.21
  • 발행 : 2022.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this study, we first present a brief overview of the Korean general insurance market. We then explore the characteristics of the loss ratios of the Korean general insurance industry and apply Markov regime-switching methodology to model the loss ratios of these insurance companies by line of business based on changes in economic regimes. This study applies a number of confirmatory tests such as Zivot-Andrews test (2002), the Chow (1960) test and the Bai and Perron (1998) to confirm the presence of structural breaks in the time series of the loss ratios by line of business. Then, we employ Markov regime-switching methodology to model these loss ratios. We find empirical evidence that the loss ratios reported by insurance companies in Korea is characterized by two distinct regimes; a regime with high volatility and a regime with low volatility, except for vehicle insurance. Our analyses suggest that macro-economic conditions have significant explanatory effect on loss ratios but the direction of effect differs based on the line of business and the regime. Unlike previous studies that have applied linear regressions or divided the samples into different periods and then apply linear regressions to model loss ratios, we argue for the application of Markov regime-switching methodology, which are able to automatically distinguish the different regimes that may be associated with the movements of loss ratios based on differing economic conditions and regulatory upheavals. This study provides a more in depth understanding of loss ratios in the general insurance industry and will be of value to insurance practitioners in modelling the loss ratios associated with their businesses to aid in their decision making. The results may also provide a basis for further studies in other markets apart from Korea as well as for shaping policy decisions related to loss ratios.

키워드

과제정보

This study was financially supported by Seoul National University of Science and Technology.

참고문헌

  1. Cutler, D. R. and P. M. Ellis, A simple model to predict loss ratios in the domestic stock property-liability insurance industry, Quarterly Journal of Business and Economics, 44(3/4) (2005) : 129-139.
  2. Chidambaran, N. K., Pugel, T. A. and A. Saunders, An investigation of the performance of the US property-liability insurance industry, Journal of Risk and Insurance, 64(2) (1997) : 371-382. https://doi.org/10.2307/253735
  3. Eckles, D. L. and M. Halek, Insurer reserve error and executive compensation, Journal of Risk and Insurance, 77(2) (2010) : 329-346. https://doi.org/10.1111/j.1539-6975.2009.01328.x
  4. Gaver, J. J. and J. S. Paterson, Managing insurance company financial statements to meet regulatory and tax reporting goals, . Contemporary Accounting Research, 16(2) (1999) : 207-241. https://doi.org/10.1111/j.1911-3846.1999.tb00579.x
  5. Veprauskaite, E. and M. B. Adams, Leverage and reinsurance effects on loss reserves in the United Kingdom's property-casualty insurance industry, Accounting and Business Research, 48(4) (2018) : 373-399. https://doi.org/10.1080/00014788.2017.1404440
  6. Haley, J. D., A cointegration analysis of the relationship between underwriting margins and interest rates: 1930-1989, Journal of Risk and Insurance, 60(3) (1993) : 480-493. https://doi.org/10.2307/253039
  7. Grace, M. F. and J. L. Hotchkiss, External impacts on the property-liability insurance cycle, Journal of Risk and Insurance 62(4) (1995) : 738-754. https://doi.org/10.2307/253593
  8. Hamilton, J. D., A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica: Journal of the Econometric Society, 57(2) (1989) : 357-384. https://doi.org/10.2307/1912559
  9. Dey, M.K., Turnover and return in global stock markets, Emerging Markets Review, 6 (2005) : 45-67. https://doi.org/10.1016/j.ememar.2004.09.003
  10. Bruner, R. F., Conroy, R. M., Estrada, J., Kritzman, M. and W. Li, Introduction to 'valuation in emerging markets, Emerging Markets Review, 3(4) (2002) : 310-324. https://doi.org/10.1016/S1566-0141(02)00039-0
  11. Smith, M. L., Investment returns and yields to holders of insurance, Journal of Business, 62(1) (1989) : 81-98. https://doi.org/10.1086/296452
  12. Ellis, P. M., The nature of the loss ratio in property-casualty insurance, Journal of Insurance Issues, 21(1) (1998) : 46-62.
  13. Taha, T., Forecasting Fire Insurance Loss Ratio in Misr Insurance Company, El-Bahith Review, 7 (2017) : 31-39.
  14. Myers, S. C., and R. A. Cohn, A discounted cash flow approach to property-liability insurance rate regulation, In Fair Rate of Return in Property-Liability Insurance (1978) : 55-78. Springer, Dordrecht.
  15. D'Arcy, S. and A. Au, A two-factor approach to loss reserve variability, http://www.business.uiuc.edu/s-darcy/.
  16. Doumpos, M., Gaganis, C. and F. Pasiouras, Estimating and explaining the financial performance of property and casualty insurers: A two-stage analysis, Journal of CENTRUM Cathedra. The Business and Economics Research Journal, 5(2) (2012) : 155-170. https://doi.org/10.7835/jcc-berj-2012-0072
  17. Lai, L. H., Chen, C. H. and T. C. Chang, The Impact of Macroeconomic Factors on Environmental Loss Ratio: Evidence from Taiwanese Insurance Data, Review of Pacific Basin Financial Markets and Policies, 21(3) (2018) : 1850020. https://doi.org/10.1142/s0219091518500200
  18. Lee, W. J. and H. K. Kim, Time series analysis for Loss Ratios of Automobile Insurance, Korean Journal of Insurance, 71 (2005) : 23-48.
  19. Sanchez-Espigares, J.A. and A. Lopez-Moreno, MSwM Examples, https://cran.rproject.org/web/packages/MSwM/vignettes/examples.pdf (accessed on 25 March 2020).
  20. Hur, Y., On the Impact of the Changes of Deductible System to the Loss Ratios of Auto Insurance Market in Korea, Korean Journal of Insurance, 105 (2016) : 57-80. https://doi.org/10.17342/KIJ.2016.105.3
  21. Kim, S. and Y. J. Shin, Effects of the Non-life insurance Industry on the Korean Economy, Korean Journal of Insurance, 102 (2015) : 1-38. https://doi.org/10.17342/KIJ.2015.102.1
  22. Jeong, J. Y. and J. C. Kang, A study on the loss ratios of the automobile insurance, . Journal of the Korean Data Analysis Society, 8(6) (2006) : 2445-2456.
  23. Zivot, E. and D. W. K. Andrews, Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis, Journal of Business and Economic statistics, 20(1) (2002) : 25-44. https://doi.org/10.1198/073500102753410372
  24. Zeileis, A., Leisch, F., Hornik, K. and C. Kleiber, Strucchange: An r package for testing for structural change in linear regression models, Journal of Statistical Software, 7(2) (2002) : 1-38.
  25. Zeileis, A., Kleiber, C., Kramer, W. and K. Hornik, Testing and dating of structural changes in practice, Computational Statistics and Data Analysis, 44(1/2) (2003) : 109-123. https://doi.org/10.1016/S0167-9473(03)00030-6
  26. Hansen, B. E., Testing for parameter instability in linear models, Journal of Policy Modeling, 14(4) (1992) : 517-533. https://doi.org/10.1016/0161-8938(92)90019-9
  27. Andrews, D. W., Tests for parameter instability and structural change with unknown change point, Econometrica: J. of the Econometric Society, 61(4) (1993) : 821-856. https://doi.org/10.2307/2951764
  28. Andrews, D. W. and W. Ploberger, Optimal tests when a nuisance parameter is present only under the alternative, Econometrica: Journal of the Econometric Society, 62(6) (1994) : 1383-1414. https://doi.org/10.2307/2951753
  29. Kuan, C. M. and K. Hornik, The generalized fluctuation test: A unifying view, Econometric Reviews, 14(2) (1995) : 135-161. https://doi.org/10.1080/07474939508800311
  30. Chow, G. C., Tests of equality between sets of coefficients in two linear regressions, Econometrica: Journal of the Econometric Society, 28(3) (1960) : 591-605. https://doi.org/10.2307/1910133
  31. Bai, J. and P. Perron, Estimating and testing linear models with multiple structural changes, Econometrica, 66(1) (1998) : 47-78. https://doi.org/10.2307/2998540
  32. Cummins, J. D., Statistical and financial models of insurance pricing and the insurance firm, The Journal of Risk and Insurance, 58(2) (1991) : 261-302. https://doi.org/10.2307/253237
  33. Dickey, D. A. and W. A. Fuller, Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association, 74(366) (1979) : 427-431. https://doi.org/10.2307/2286348