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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/77184
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/77184


    Title: 金融監理制度對商業銀行利潤效率之影響--亞洲12國之實證分析
    Effects of Financial Supervision Regimes on Commercial Banks’ Profit Efficiency in 12 Asian Countries
    Authors: 黃國睿
    Huang, Kuo Jui
    Contributors: 廖四郎
    Liao, Szu Lang
    黃國睿
    Huang, Kuo Jui
    Keywords: 金融監理
    隨機共同利潤邊界
    兩階段估計法
    環境變數
    已開發國家群組
    開發中國家群組
    技術缺口比率
    共同邊界技術效率
    金融監理單位整合程度
    中央銀行獨立程度
    financial supervision
    stochastic meta-profit frontier
    two-stage estimation procedure
    environmental variables
    developed countries
    developing countries
    technology gap ratios
    meta-profit efficiencies
    unification of supervisory authority
    independence
    Date: 2015
    Issue Date: 2015-08-03 13:22:04 (UTC+8)
    Abstract: 金融監理制度影響一國商業銀行經營績效的相關議題,一直受到學者與政府當局的重視,為瞭解亞洲地區銀行業在中央銀行與監理單位不同管理下的利潤效率,找出最適的制度設計,本研究根據Huang、Huang與Liu(2014)提出之隨機共同利潤邊界(stochastic meta-profit frontier),採用兩階段估計法,蒐集中國大陸、香港、印度、日本、韓國、馬來西亞、巴基斯坦、菲律賓、新加坡、斯里蘭卡、泰國以及阿拉伯聯合大公國等十二國商業銀行資料,分成開發中和已開發國家兩個群組,將環境變數納入無效率模型中,進行實證分析,比較不同群組的利潤效率差異,發掘影響效率的主要變數與方向,從而獲得重要政策意涵。
    根據實證分析結果,中央銀行介入銀行監理程度越高,商業銀行利潤效率越低;金融監理單位整合程度越高,商業銀行利潤效率越高;中央銀行獨立程度越高,商業銀行利潤效率越低;已開發國家群組的平均技術缺口比率與共同邊界技術效率值皆高於開發中國家群組,符合預期。共同利潤效率最高的是日本,最低的是韓國。平均而言,各國若在共同利潤邊界上從事生產,能提升41.9%至75%的利潤。
    The effects of degrees of financial supervision on performance of commercial banks have long been important issues and drawn much attention to academic researchers and government authorities. This study applies the stochastic meta-profit frontier, recently developed by Huang, Huang, and Liu (2014), to estimate and compare profit efficiencies of commercial banks from 12 Asian countries, i.e., Mainland China, Hong Kong, India, Japan, South Korea, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Thailand, and United Arab Emirates. We divide the sample countries into two groups, i.e., developing and developed countries. This enables us to further investigate the effects of different supervisory systems, enforced by central banks (CB) and supervisory authorities, on commercial banks’ profit efficiencies, as well as to make a suggestion about the optimal supervision regimes in the area. Note that a set of supervisory indices are considered as environmental variables that explain profit inefficiency.
    Using the two-stage estimation procedure, the empirical results are summarized as follows. First, it is found that bank’s profit efficiency decreases with the increase in a CB’s supervision sectors. Second, the unification of supervisory authority has positive effect on bank’s profit efficiency. Third, the more independent is the CB, the less profit efficient the commercial bank is. Fourth, banks in the group of developed countries are found to have higher technology gap ratios and meta-profit efficiencies than those in the group of developing countries, as expected. Fifth and finally, Japan and South Korea has the highest and the lowest level of meta-profit efficiency, respectively. Evidence is found that if an average commercial bank were adopting the best technology, it can earn roughly 41.9% to 75% more profits than otherwise.
    Reference: 鄭政秉、梁連文、許智偉,2010。「差異化管理對台灣與日本銀行業成本效率之影響」,『2009生產力與效率特刊』,頁145-189。中興大學應用經濟系。

    謝人俊,2009。「第七章 美國金融監理制度改革方案」,147-166。刊於中央銀行編,『全球金融危機專輯』。臺北市:中央銀行。

    Aigner, Dennis, C. A. Knox Lovell, and Peter Schmidt, 1977. “Formulation and Estimation of Stochastic Frontier Production Function Models,” Journal of Econometrics. 6(1): 21-37.

    Akhigbe, Aigbe and James E. McNulty, 2003. “The Profit Efficiency of Small US Commercial Banks,” Journal of Banking & Finance. 27(2): 307-325.

    Arnone, Marco, Bernard J. Laurens, Jean-François Segalotto, and Martin Sommer, 2007. “Central Bank Autonomy: Lessons from Global Trends,” IMF Working Paper, No. 07/88. Washington, D.C.: International Monetary Fund (IMF).

    Barth, James R., Luis G. Dopico, Daniel E. Nolle, and James A. Wilcox, 2002. “Bank Safety and Soundness and the Structure of Bank Supervision: A Cross-Country Analysis,” International Review of Finance. 3(3-4): 163-188.

    Barth, James R., Daniel E. Nolle, Triphon Phumiwasana, and Glenn Yago, 2003. “A Cross-Country Analysis of the Bank Supervisory Framework and Bank Performance,” Financial Markets, Institutions & Instruments. 12(2): 67-120.

    Barth, James R., Gerard Caprio, Jr., and Ross Levine, 2008. “Bank Regulations are Changing: For Better or Worse?” Policy Research Working Paper, No. 4646. Washington, D.C.: World Bank (WB).

    Battese, G. E. and T. J. Coelli, 1988. “Prediction of Firm-Level Technical Efficiencies with a Generalized Frontier Production Function and Panel Data,” Journal of Econometrics. 38(3): 387-399.

    Battese, G. E. and T. J. Coelli, 1992. “Frontier Production Functions, Technical Efficiency, and Panel Data: With Application to Paddy Farmers in India,” Journal of Productivity Analysis. 3(1-2): 153-169.

    Battese, G. E. and T. J. Coelli, 1995. “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data,” Empirical Economics. 20(2): 325-332.

    Battese, G. E. and D. S. Prasada Rao, 2002. “Technology Gap, Efficiency, and a Stochastic Metafrontier Function,” International Journal of Business and Economics. 1(2): 87-93.

    Battese, G. E., D. S. Prasada Rao, and Christopher J. O’Donnell, 2004. “A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating under Different Technologies,” Journal of Productivity Analysis. 21(1): 91-103.

    Belotti, Federico, Silvio Daidone, Giuseppe Ilardi, and Vincenzo Atella, 2013. “Stochastic Frontier Analysis Using Stata,” The Stata Journal. 13(4): 1-39.

    Berger, Allen N. and David B. Humphrey, 1991. “The Dominance of Inefficiencies over Scale and Product Mix Economies in Banking,” Journal of Monetary Economics. 28(1): 117-148.

    Berger, Allen N., John H. Leusner, and John J. Mingo, 1997. “The Efficiency of Bank Branches,” Journal of Monetary Economics. 40(1): 141-162.

    Berger, Allen N. and Loretta J. Mester, 1997. “Inside the Black Box: What Explains Differences in the Efficiencies of Financial Institutions?” Journal of Banking & Finance. 21(7): 895-947.

    Berger, Allen N. and Emilia Bonaccorsi di Patti, 2006. “Capital Structure and Firm Performance: A New Approach to Testing Agency Theory and an Application to the Banking Industry,” Journal of Banking & Finance. 30(4): 1065-1102.

    Boskin, Michael J. and Lawrence J. Lau, 1992. “International and Intertemporal Comparison of Productive Efficiency: An Application of the Meta-Production Function Approach to the Group-of-Five (G-5) Countries,” The Economic Studies Quarterly. 43(4): 298-312.

    Coelli, T. J., D. S. Prasada Rao, Christopher J. O’Donnell, and G. E. Battese, 2005. An Introduction to Efficiency and Productivity Analysis. New York, N.Y.: Springer Science + Media.

    Cornwell, Christopher, Peter Schmidt, and Robin C. Sickles, 1990. “Production Frontiers with Cross-Sectional and Time-Series Variation in Efficiency Levels,” Journal of Econometrics. 46(1-2): 185-200.

    Gaganis, Chrysovalantis and Fotios Pasiouras, 2013. “Financial Supervision Regimes and Bank Efficiency: International Evidence,” Journal of Banking & Finance. 37(12): 5463-5475.

    Greene, William, 2005. “Fixed and Random Effects in Stochastic Frontier Models,” Journal of Productivity Analysis. 23(1): 7-32.

    Grilli, Vittorio, Donato Masciandaro, and Guido Tabellini, 1991. “Political and Monetary Institutions and Public Financial Policies in the Industrial Countries,” Economic Policy. 6(13): 341-392.

    Gunaratne, Lokugam H. P. and PingSun Leung, 2001. “Asian Black Tiger Shrimp Industry: A Productivity Analysis,” in Economics and Management of Shrimp and Carp Farming in Asia: A Collection of Research Papers Based on the ADB/NACA Farm Performance Survey, pp. 55-68. Edited by PingSun Leung and Khem R. Sharma. Bangkok, Thailand: Network of Aquaculture Centers in Asia-Pacific (NACA).

    Hayami, Yujiro, 1969. “Sources of Agricultural Productivity Gap among Selected Countries,” American Journal of Agricultural Economics. 51(3): 564-575.

    Hayami, Yujiro and V. W. Ruttan, 1970. “Agricultural Productivity Differences among Countries,” The American Economic Review. 60(5): 895-911.

    Hayami, Yujiro and V. W. Ruttan, 1971. Agricultural Development: An International Perspective. Baltimore, M.D.: John Hopkins University Press.

    Huang, Cliff J. and Jin-Tan Liu, 1994. “Estimation of a Non-Neutral Stochastic Frontier Production Function,” Journal of Productivity Analysis. 5(2): 171-180.

    Huang, Cliff J., Tai-Hsin Huang, and Nan-Hung Liu, 2014. “A New Approach to Estimating the Metafrontier Production Function Based on a Stochastic Frontier Framework,” Journal of Productivity Analysis. 42(3): 241-254.

    Huang, Tai-Hsin, 2000. “Estimating X-Efficiency in Taiwanese Banking Using a Translog Shadow Profit Function,” Journal of Productivity Analysis. 14(3): 225-245.

    Hughes, Joseph and Loretta J. Mester, 1993. “A Quality and Risk-Adjusted Cost Function for Banks: Evidence on the ‘Too-Big-To-Fail’ Doctrine,” Journal of Productivity Analysis. 4(3): 293-315.

    International Monetary Fund (IMF), 2015. World Economic Outlook, April 2015. Washington, D.C.: International Monetary Fund (IMF).

    Kim, Jong Il and Lawrence J. Lau, 1994. “The Sources of Economic Growth of the East Asian Newly Industrialized Countries,” Journal of the Japanese and International Economies. 8(3): 235-271.

    Kumbhakar, Subal C., 1990. “Production Frontiers, Panel Data, and Time-Varying Technical Inefficiency,” Journal of Econometrics. 46(1-2): 201-211.

    Kumbhakar, Subal C., 1996. “A Parametric Approach to Efficiency Measurement Using a Flexible Profit Function,” Southern Economic Journal. 63(2): 473-487.

    Kumbhakar, Subal C., Hung-Jen Wang, and Alan P. Horncastle, 2015. A Practitioner’s Guide to Stochastic Frontier Analysis Using Stata. New York, N.Y.: Cambridge University Press.

    Lau, Lawrence J. and Pan A. Yotopoulos, 1989. “The Meta-Production Function Approach to Technological Change in World Agriculture,” Journal of Development Economics. 31(2): 241-269.

    Lee, Young Hoon and Peter Schmidt, 1993. “A Production Frontier Model with Flexible Temporal Variation in Technical Inefficiency,” in The Measurement of Productive Efficiency: Techniques and Applications, pp. 237-255. Edited by Harold O. Fried, C. A. Knox Lovell, and Shelton S. Schmidt. New York, N.Y.: Oxford University Press.

    Masciandaro, D., 2009. “Politicians and Financial Supervision Unification Outside the Central Bank: Why do they do it?” Journal of Financial Stability. 5(2): 124-146.

    Meeusen, Wim and Julien van den Broeck, 1977. “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error,” International Economic Review. 18(2): 435-444.

    Mundlak, Yair and René Hellinghausen, 1982. “The Intercountry Agricultural Production Function: Another View,” American Journal of Agricultural Economics. 64(4): 664-672.

    O’Donnell, Christopher J., D. S. Prasada Rao, and G. E. Battese, 2008. “Metafrontier Frameworks for the Study of Firm-Level Efficiencies and Technology Ratios,” Empirical Economics. 34(2): 231-255.

    Pitt, Mark M. and Lung-Fei Lee, 1981. “The Measurement and Sources of Technical Inefficiency in the Indonesian Weaving Industry,” Journal of Development Economics. 9(1): 43-64.

    Schmidt, Peter and Robin C. Sickles, 1984. “Production Frontiers and Panel Data,” Journal of Business and Economic Statistics. 2(4): 367-374.

    Sharma, Khem R. and PingSun Leung, 2000. “Technical Efficiency of Carp Pond Culture in South Asia: An Application of Stochastic Meta-Production Frontier Model,” Aquaculture Economics and Management. 4(3-4): 169-189.

    Stevenson, Rodney E., 1980. “Likelihood Functions for Generalized Stochastic Frontier Estimation,” Journal of Econometrics. 13(1): 57-66.

    Sun, Jianjun, Kozo Harimaya, and Nobuyoshi Yamori, 2013. “Regional Economic Development, Strategic Investors, and Efficiency of Chinese City Commercial Banks,” Journal of Banking & Finance. 37(5): 1602-1611.

    White, Halbert, 1982. “Maximum Likelihood Estimation of Misspecified Models,” Econometrica. 50(1): 1-25.
    Description: 碩士
    國立政治大學
    金融研究所
    102352008
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102352008
    Data Type: thesis
    Appears in Collections:[金融學系] 學位論文

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