Abstract: Measuring the relative efficiency in insurance industry plays essential role for productivity improvement in insurance industry. In this paper, we present an empirical investigation to measure the relative efficiency of some insurance firms listed on Tehran Stock Exchange using data envelopment analysis (DEA) over the period 2011-2013. The proposed study of this paper uses four inputs namely; total assets, price to earnings ratio, beta and sigma and four outputs namely; net earnings, one-year, two-year and three-year returns. The study uses two methods of input and output oriented DEA to measures the relative efficiencies of 9 banks and the results indicate that most insurance firms perform well in terms of efficiency.
How to cite this paper
Mousavi, M & Jafari, S. (2015). Measuring the relative efficiency of insurance industry: Evidence from Tehran Stock Exchange.Management Science Letters , 5(11), 999-1004.
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis, Management Science, 39, 1261-1264.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis.Management science, 30(9), 1078-1092.
Banker, R. D., & Thrall, R. M. (1992). Estimation of returns to scale using data envelopment analysis. European Journal of Operational Research, 62(1), 74-84.
Barros, C. P., Nektarios, M., & Assaf, A. (2010). Efficiency in the Greek insurance industry. European Journal of Operational Research, 205(2), 431-436.
Brockett, P. L., Cooper, W. W., Golden, L. L., Rousseau, J. J., & Wang, Y. (1998). DEA evaluations of the efficiency of organizational forms and distribution systems in the US property and liability insurance industry.International Journal of Systems Science, 29(11), 1235-1247.
Brockett, P. L., Cooper, W. W., Golden, L. L., Rousseau, J. J., & Wang, Y. (2004). Evaluating solvency versus efficiency performance and different forms of organization and marketing in US property––liability insurance companies.European Journal of Operational Research, 154(2), 492-514.
Brockett, P. L., Cooper, W. W., Golden, L. L., Rousseau, J. J., & Wang, Y. (2005). Financial intermediary versus production approach to efficiency of marketing distribution systems and organizational structure of insurance companies. Journal of Risk and Insurance, 72(3), 393-412.
Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of the Operational Research, 2, 429–44.
Charnes, A., Cooper, W. W., Lewin, A., Seiford, L. M. (1994). Data envelopment analysis: theory, methodology and applications. Massachusetts: Kluwer Academic Publishers.
Chen, T. Y. (1998). Determining the comparative efficient units of insurance industries through DEA. Journal of Professional Services Marketing, 18(2), 105-118.
Cummins, J. D., & Zi, H. (1997). Measuring cost efficiency in the US life insurance industry: Econometric and mathematical programming approaches.Financial Institutions Center, The Wharton School Working Paper, University of Pennsylvania.
Cummins, J. D., Weiss, M. A., & Zi, H. (2003). Economies of scope in financial services: A DEA bootstrapping analysis of the US insurance industry.Unpublished manuscript, The Wharton School, Philadelphia, PA.
Cummins, J. D., & Weiss, M. A. (2013). Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods. InHandbook of insurance (pp. 795-861). Springer New York.
Diboky, F., & Ubl, E. (2007, September). Ownership and efficiency in the German life insurance market: A DEA bootstrap approach. In 34th Seminar of the European Group of Risk and Insurance Economists (EGRIE), June.
Hardwick, P., Adams, M. B., & Hong, Z. (2003). Corporate governance and cost efficiency in the United Kingdom life insurance industry. European Business Management School, University of Wales, Swansea.
Md Saad, N., Idris, H., & Edzalina, N. (2011). Efficiency of life insurance companies in Malaysia and Brunei: a comparative analysis. International Journal of Humanities and Social Science, 1(3), 111-122.
Kasman, S., & Turgutlu, E. (2007, January). A comparison of chance-constrained DEA and stochastic frontier analysis: An application to the Turkish life insurance industry. In 8 Congreso Turco de Econometr?a y Estad?stica, Malasia.
Klumpes, P. J. (2004). Performance benchmarking in financial services: Evidence from the UK life insurance industry. The Journal of Business, 77(2), 257-273.
Retzlaff-Roberts, D., & Puelz, R. (1996). Classification in automobile insurance using a DEA and discriminant analysis hybrid. Journal of Productivity Analysis,7(4), 417-427.
Saad, N. M., Majid, M. S. A., Yusof, R. M., Duasa, J., & Rahman, A. R. A. (2006). Measuring efficiency of insurance and Takaful companies in Malaysia using data envelopment analysis (DEA). Review of Islamic Economics, 10(2), 5.
Shujie, Y. A. O., Zhongwei, H., & Genfu, F. E. N. G. (2007). On technical efficiency of China & apos; s insurance industry after WTO accession. China Economic Review, 18(1), 66-86.
Sinha, D., Pratap, R., & Chatterjee, B. (2009). Are Indian life insurance companies cost efficient?. Biswajit, Are Indian Life Insurance Companies Cost Efficient.
Wei, H. (2009). Efficiency of insurance fund utilization in China & apos; s insurance companies: A resource-based two-stage DEA model. Economic Research Journal, 8, 37-49.