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題名:台灣壽險業市場力量、最終控制權與效率關係之研究
作者:唐玉潔
作者(外文):Yu-Chieh Tang
校院名稱:淡江大學
系所名稱:管理科學研究所博士班
指導教授:莊忠柱
學位類別:博士
出版日期:2015
主題關鍵詞:市場力量效率隨機邊界法一般化極值法Clayton Copula公司治理最終控制權區間設限Tobit迴歸Market PowerEfficiencyStochastic Frontier ApproachGeneralized Extreme ValueClayton CopulaCorporate GovernanceUltimate Control RightsDoubly Censored Tobit Regression
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台灣壽險業在金融體系中扮演著重要地位。然而,在全面開放的壽險市場,追求最大市場力量與最大效率,質量並重的管理,一直是人壽保險業經營管理的重要議題之一。
本論文利用隨機邊界法估計效率值,再以一般化極值理論,探討壽險業市場領導者的最大市場力量與最大效率關係。實證發現台灣壽險業市場領導者之最大市場力量與最大效率關係,存在非對稱的相依關係,即擁有最大市場力量的壽險公司,不一定愈有效率。此外,本論文亦利用Clayton Coupla方法,探討市場力量與效率的相依關係。實證發現二者呈現相依關係,即指市場力量愈大,不一定有助於效率的提昇;反之,亦然。
良好的公司治理制度有助於平衡市場力量擴張與效率極大化。因此,本論文加入公司治理的最終控制權作為市場力量對效率影響的干擾變數,利用區間設限Tobit迴歸方法,探討對台灣壽險業的市場力量、最終控制權與效率的關係。實證發現台灣壽險公司的市場力量對效率有直接負向影響,再加入公司治理的最終控制權為干擾因素後,控制權會加強市場力量對效率的影響,而盈餘分配權會減少市場力量對效率的影響。本論文的研究結果提供台灣壽險業擬訂投入產出資源的配置、市場策略與公司治理政策的參考,以達壽險業質量並重的經營目標。
The life insurance industry plays a significant role in the financial system of Taiwan. Both market power and efficiency contribute to the viability of the insurer, making them essential to the management of life insurance companies. As the competition in the Taiwanese insurance industry intensifies, the insurance companies should look for expansion of market power and maximization of efficiency. Based on the translog cost function, this study first measured efficiency for using the stochastic frontier approach. We then investigated the relationship between leading market power and leading efficiency using the generalized extreme value theory. The results showed a strong nonlinear, asymmetric dependence between the market power and efficiency of the leading Taiwanese insurer. Companies with greater market power do not necessarily have greater efficiency. This study then investigated the dependence between market power and efficiency using the Clayton Copula model. The empirical results showed a dependence relationship between the two factors for Taiwanese insurers.
In addition, the doubly censored Tobit regression is used to investigate the relationships among market power, ultimate control rights, and efficiency. The empirical results showed that market power has a negative influence on the efficiency. When the ultimate control rights of corporate governance are used as moderator variables, the control right are observed to enhance the influence of market power on efficiency, while cash flow right reduce the effect of market power on efficiency. Thus, the findings of this study can provide a reference to Taiwanese life insurance companies for determining resource allocation, marketing strategy, and corporate governance policies.
1.Aigner, D., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21–37.
2.Ariss, R. T. (2010). On the implications of market power in banking: Evidence from developing countries. Journal of Banking & Finance, 34, 765–775.
3.Bajtelsmit, V. L., & Bouzouita, R. (1998). Market structure and performance in private passenger automobile insurance. Journal of Risk and Insurance, 65, 503–514.
4.Battese, G., & Coelli, T. J. (1988). Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. Journal of Econometrics, 38, 387–399.
5.Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20, 325–333.
6.Benston, G. J., Hanweck, G. A., & Humphrey, D. B. (1982). Scale economies in banking: A restructuring and reassessment. Journal of Money, Credit and Banking, 14, 435–456.
7.Berger, A. N. (1995). The profit-structure relationship in banking: Tests of market-power and efficient-structure hypotheses. Journal of Money, Credit and Banking, 27, 404–431.
8.Berger, A. N., Cummins, J. D., & Weiss, M. A. (1997). The coexistence of multiple distribution systems for financial services: The case of property-liability insurance. Journal of Business, 70, 515–546.
9.Berger, A. N., Cummins, J. D., Weiss, M. A., & Zi, H. (2000). Conglomeration versus strategic focus: Evidence from the insurance industry. Journal of Financial Intermediaries, 9, 323–362.
10.Berger, A. N., & Hannan, T. (1997). Using efficiency measures to distinguish among alternative explanations of the structure-performance relationship in banking. Managerial Finance, 23, 6–31.
11.Berger, A. N., Hasan, I., & Zhou, M. (2009). Bank ownership and efficiency in China: What will happen in the world’s largest nation? Journal of Banking & Finance, 33, 113–130.
12.Berger, A. N., & Humphrey, D. B. (1991). The dominance of inefficiencies over scale and product mix economies in banking. Journal of Monetary Economics, 28,117–148.
13.Bogaerts, K., & Lesaffre, E. (2008). Modeling the association of bivariate interval-censored data using the copula approach. Statistics in Medicine, 27, 6379–6392.
14.Bouye, E. (2002). Multivariate extremes at work for portfolio risk management. Finance, 23, 125–144.
15.Carbo, S., Gardener, E. P. M., & Williams, J. (2003). A note on technical change in banking: The case of European savings banks. Applied Economics, 35, 705–719.
16.Cherubrini, U., Luciano, E., & Vecchiato, W. (2004). Copula methods in finance. England: John Wiley & Sons, Ltd.
17.Choi, B. P., & Weiss, M. A. (2005). An empirical investigation of market structure, efficiency, and performance in property-liability insurance. Journal of Risk and Insurance, 72, 635–673.
18.Chuang, C. C., & Tang, Y. C. (2014). Asymmetric dependence between efficiency and market power: Longitudinal perspective of the Taiwan life insurance industry. International Journal of Applied Mathematics and Statistics, 52, 144–151.
19.Claessens, S., Djankov, S., Fan, J. P. H., & Lang, L. H. P. (2002). Disentangling the incentive and entrenchment effects of large shareholdings. Journal of Finance, 57, 2741–2771.
20.Claessens, S., Djankov S., & Lang, L. H. P. (2000). The separation of ownership and control in East Asian corporation. Journal of Financial Economics, 58, 81–112.
21.Clayton, D. G. (1978). A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika, 65, 141–151.
22.Coles, S. G. (2001). An introduction to statistical modeling of extreme values (Springer Series in Statistics). London: Springer-Verlag.
23.Coles, S. G., Heffernan, J., & Tawn, J. (1999). Dependence measures for extreme value analyses. Extremes, 2, 339–365.
24.Coles, S. G., & Tawn, J. (1991). Modeling extreme multivariate events. Journal of the Royal Statistical Society: Series B, 53, 377–392.
25.Coles, S. G., & Tawn, J. (1994). Statistical methods for multivariate extremes: An application to structural design. Applied Statistics, 43, 1–48.
26.Cummins, J. D., & Weiss, M. A. (1993). Measuring cost efficiency in the property-liability insurance industry. Journal of Banking & Finance, 17, 463–481.
27.Cummins, J. D., & Zi, H. (1998). Comparison of frontier efficiency methods: An application to the U.S. life insurance industry. Journal of Productivity Analysis, 10, 131–152.
28.De Andres, P., & Vallelado, E. (2008). Corporate governance in banking: The role of the board of directors. Journal of Banking & Finance, 32, 2570–2580.
29.De Borger, B., & Kerstens, K. (1996). Cost efficiency of Belgian local governments: A comparative analysis of FDH, DEA, and econometric approaches. Regional Science and Urban Economics, 26, 145–170.
30.De Jonghe, O., & Vennet, R. V. (2008). Competition versus efficiency: What drives franchise values in European banking? Journal of Banking & Finance, 32, 1820–1835.
31.Delhausse, B., Fecher, F., & Pestieau, P. (1995). Measuring productive performance in the non-life insurance industry: The case of French and Belgian markets. Tijdschrift voor Economie en Management, 40, 47–69.
32.Demsetz, H. (1973). Industry structure, market rivalry, and public policy. Journal of Law and Economics, 16, 1–9.
33.DeYoung, R. (1997). A diagnostic test for the distribution-free efficiency estimator:An example using US commercial bank data. European Journal of Operational Research, 98, 243–249.new window
34.Eling, M., & Luhen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison. Journal of Banking & Finance, 34, 1497–1509.
35.Embrechts, P. C. (2000). Extreme value theory: Potential and limitations as an integrated risk management tool. Derivatives Use, Trading & Regulation, 6, 449–456.
36.Embrechts, P. C., Kluppelberg C., & Mikosch, T. (1997). Modelling extremal events for insurance and finance. Berlin: Springer-Verlag
37.Fama, E., & Jensen, M. (1983). Separation of ownership and control. Journal of Law and Economics, 26, 301–325.
38.Fecher, F., Kessler, D., Perelman, S., & Pestieau, P. (1993). Productive performance of the French insurance industry. Journal of Productivity Analysis, 4, 77–93.
39.Fenn, P., Vencappa, D., Diacon, S., Klumpes, P., & O’Brien C. (2008). Market structure and the efficiency of European insurance companies: A stochastic frontier analysis. Journal of Banking & Finance, 32, 86–100.
40.Filatotchev, I., Lien, Y. C., & Piesse, J. (2005). Corporate governance and performance in publicly listed, family-controlled firms: Evidence from Taiwan. Asia Pacific Journal of Management, 22, 257–283.
41.Fisher, R. A., & Tippett, L. H. C. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Mathematical Proceedings of the Cambridge Philosophical Society, 24, 180–190.
42.Fu, X., & Heffernan, S. (2009). The effects of reform on China’s bank structure and performance. Journal of Banking & Finance, 33, 39–52.
43.Gadhoum, Y. (2006). Power of ultimate controlling owners: A survey of Canadian landscape. Journal of Management & Governance, 10, 179–204.
44.Gallant, A. R. (1981). On the bias in flexible functional forms and an essentially unbiased form: The fourier flexible form. Journal of Econometrics, 15, 211–245.
45.Gallant, A. R. (1982). Unbiased determination of production technologies. Journal of Econometrics, 20, 285–323.
46.Gardner, L. A., & Grace, M. F. (1993). X-efficiency in the US life insurance industry. Journal of Banking & Finance, 17, 497–510.
47.Ghoudi, K., Khoudraji, A., & Rivest, L. (1998). Proprietes statistiques des copules de valeurs extremes bidimensionnelles. Canadian Journal of Statistics, 26, 187–197.
48.Greene, W. H., & Segal, D. (2004). Profitability and efficiency in the US life insurance industry. Journal of Productivity Analysis, 21, 229–247.
49.Hauner, D. (2008). Credit to government and banking sector performance. Journal of Banking & Finance, 32, 1499–1507.
50.Hendry, K., & Kiel, G. C. (2004). The role of the board in firm strategy: Integrating agency and organisational control perspectives. Corporate Governance: An international Review, 12, 500–520.
51.Hu, M., & Gui, W. (2014). Time truncated double acceptance sampling plans for inverse Rayleigh distribution. International Journal of Applied Mathematics & Statistics, 52, 128–136.
52.Hu, R., & Shieh, C. J. (2013). High-tech industries overseas investment performance evaluation: Application of data envelopment analysis. South African Journal of Economic and Management Sciences, 16, 67–73.
53.Huang, T. H. (2000). Estimation X-efficiency in Taiwanese banking using a translog shadow profit function. Journal of Productivity Analysis, 14, 225–245.
54.Huang, T. H., Liao, Y. T., & Chiang, L. C. (2010). An examination on the cost efficiency of the banking industry under multiple output prices’ uncertainty. Applied Economics, 42, 1169–1182.
55.Huang, T. H., & Wang, M. H. (2001). Estimating scale and scope economies with fourier flexible functional form- Evidence from Taiwan’s banking industry. Australian Economic Papers, 40, 213–231.
56.Hussels, S., & Ward, D. R. (2006). The impact of deregulation on the German and UK life insurance markets: An analysis of efficiency and productivity between 1991-2002, (Working Paper, Cranfield Management Research Paper Series). 4.
57.Hwang, S. N., & Kao, T. L. (2008). Using two-stage DEA to measure managerial efficiency change of non-life insurance companies in Taiwan. International Journal of Management and Decision Making, 9, 377–401.
58.Joe, H. (1997). Multivariate models and dependence concepts. London: Chapman & Hall.
59.Joe, H., Smith, R. L., & Weissman, I. (1992). Bivariate threshold models for extremes. Journal of the Royal Statistical Society: Series B, 54, 171–183.
60.Kumbhakar, S. C. (1991). The measurement and decomposition of cost-inefficiency: The translog cost system. Oxford Economic Papers, 43, 667–683.
61.La Porta, R., Lopez-De-Silanes, F., & Shleifer, A. (1999). Corporate ownership around the world. Journal of Finance, 54, 471–517.
62.La Porta, R., Lopez-De-Silanes, F., Shleifer, A., & Vishny, R. (2002). Investor protection and corporate valuation. Journal of Finance, 57, 1147–1170.
63.Larcker, D. F., Richardson, S. A., & Tuna, A. I. (2007). Corporate governance, accounting outcomes, and organizational performance. Accounting Review, 82, 963–1008.
64.Liu, J. S., & Yang, C. (2008). Corporate governance reform in Taiwan: Could the independent director system be an effective remedy? Asian Survey, 48, 816–838.
65.Longin, F. M. (2000). From value at risk to stress testing: The extreme value approach. Journal of Banking & Finance, 24, 1097–1130.
66.McNeil, A., & Frey, R. (2000). Estimation of tail-related risk measures for heteroscedastic financial time series: An extreme value approach. Journal of Empirical Finance, 7, 271–300.
67.Meador, J. W., Harley E. R., & Schellhorn C. D. (2000). Product focus versus diversification: Estimates of x-efficiency for the U.S. life insurance industry. In P. T. Harker & S. A. Zenios (Eds.), Performance of financial institutions: Efficiency, innovation, regulation (175–198). New York: Cambridge University Press.
68.Meeusen, W., & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435–444.
69.Mester, L. J. (1996). A study of bank efficiency taking into account risk-preferences. Journal of Banking & Finance, 20, 1025–1045.
70.Mester, L. J. (1997). Measuring efficiency at U.S. banks: Accounting for heterogeneity is important. European Journal of Operational Research, 98, 230–242.
71.Nelsen, R. B. (2006). An introduction to copulas. New York: Springer.
72.Shleifer, A., & Vishny, R. W. (1997). A survey of corporate governance. Journal of Finance, 52, 737–783.
73.Sklar, A. (1959). Fonctions de repartition an dimensions et leurs marges. Publications de l’Institut de Statistique de l’Universite’ de Paris 8: 229–231.
74.Smirlock, M., Gilligan, T., & Marshall, W. (1984). Tobin’s q and the structure-performance relationship. American Economic Review, 74, 1051–1060.
75.Stephenson, A. (2003). Simulating multivariate extreme value distributions of logistic type. Extremes, 6, 49–59.
76.Sun, J. (2005). Interval censoring. In P. Armitage & T. Colton (Eds.), Encyclopedia of biostatistics (2603–2609). New York: Wiley.
77.Sun, L., Wang, L., & Sun, J. (2006). Estimation of the association for bivariate interval-censored failure time data. Scandinavian Journal of Statistics, 33, 637–649.
78.Tawn, J. A. (1988). Bivariate extreme value theory: Models and estimation. Biometrika, 75, 397–415.
79.Thanatawee, Y. (2014). Ownership structure and dividend policy: Evidence from China. International Journal of Economics and Finance, 6, 197–204.
80.Tobin, J. (1958). Estimation of relationship for limited dependent variables. Econometrica, 26, 24–36.
81.Valverde, S. C., Humphrey, D. B., & del Paso, R. L. (2007). Opening the black box: Finding the source of cost inefficiency. Journal of Productivity Analysis, 27, 209–220.
82.Wang, J. L., Jeng, V., & Peng, J. L. (2007). The impact of corporate governance structure on the efficiency performance of insurance companies in Taiwan. The Geneva Papers on Risk and Insurance - Issues and Practice, 32, 264–282.
83.Wang, W., & Ding, A. A. (2000). On assessing the association for bivariate current status data. Biometrika, 87, 879–893.
84.Weiss, M. A., & Choi, B. P. (2008). State regulation and the structure, conduct, efficiency and performance of US auto insurers. Journal of Banking & Finance, 32, 134–156.
85.White, H. (1980). Using least squares to approximate unknown regression functions. International Economic Review, 21, 149–170.
86.Yeh, Y. H., Lee, T. S., & Shu, P. G. (2008). The agency problems embedded in firm’s equity investment. Journal of Business Ethics, 79, 151–166.
87.Yuengert, A. M. (1993). The measurement of efficiency in life insurance: Estimates of a mixed normal-gamma error model. Journal of Banking & Finance, 17, 483–496.

 
 
 
 
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