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Decomposing the change in profit of Taiwanese banks: incorporating risk

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  • Jia-Ching Juo

Abstract

This study follows the structure of Grifell-Tatjé and Lovell (Manag Sci 45:1177–1193, 1999 ) and uses the non-parametric approach to decompose the change in profit of Taiwanese banks into various drivers. However, risk was never considered in the papers based on profit decomposition. Without considering risk, the empirical results will be biased while decomposing the change in profit. In fact, risk is a joint but undesirable output which cannot be freely disposed of by various regulations. The non-performing loan (NPL) is employed as a risk indicator for decomposing the change in profit in this study. This study also performs a three-way comparison among (1) the original Grifell-Tatjé and Lovell (Manag Sci 45:1177–1193, 1999 ) analysis (OGLA) model that ignores NPL, (2) the extended Grifell-Tatjé and Lovell (Manag Sci 45:1177–1193, 1999 ) analysis (EGLA) model that is based on the OGLA model and incorporates NPL, and (3) the directional distance function (DDF) model that is based on Juo et al. (Omega 40:550–561, 2012 ) and incorporates NPLs to see if incorporating the undesirable output matters. The decomposition of the change in profit in the above three models is then illustrated using Taiwanese banks over the period 2006–2010. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Jia-Ching Juo, 2014. "Decomposing the change in profit of Taiwanese banks: incorporating risk," Journal of Productivity Analysis, Springer, vol. 41(2), pages 247-262, April.
    • Handle: RePEc:kap:jproda:v:41:y:2014:i:2:p:247-262
    DOI: 10.1007/s11123-012-0330-y
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    Cited by:

    1. Juo, Jia-Ching & Fu, Tsu-Tan & Yu, Ming-Miin & Lin, Yu-Hui, 2016. "Non-radial profit performance: An application to Taiwanese banks," Omega, Elsevier, vol. 65(C), pages 111-121.
    2. Zhu, Ning & Wu, Yanrui & Wang, Bing & Yu, Zhiqian, 2019. "Risk preference and efficiency in Chinese banking," China Economic Review, Elsevier, vol. 53(C), pages 324-341.
    3. Juo, Jia-Ching & Fu, Tsu-Tan & Yu, Ming-Miin & Lin, Yu-Hui, 2015. "Profit-oriented productivity change," Omega, Elsevier, vol. 57(PB), pages 176-187.
    4. Ying Li & Yung‐ho Chiu & Ying Yu Chen & Lihua Wang & Yi‐Nuo Lin & Su‐Wan Wang, 2022. "The impact of market share on efficiency of commercial banks: Resampling slacks‐based measure data envelopment analyses model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1621-1634, July.
    5. Huang, Tai-Hsin & Chiang, Dien-Lin & Lin, Chung-I, 2017. "A new approach to estimating a profit frontier using the censored stochastic frontier model," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 68-77.
    6. Lin, Yu-Hui & Fu, Tsu-Tan & Chen, Chia-Li & Juo, Jia-Ching, 2017. "Non-radial cost Luenberger productivity indicator," European Journal of Operational Research, Elsevier, vol. 256(2), pages 629-639.
    7. Fu, Tsu-Tan & Juo, Jia-Ching & Chiang, Han-Chin & Yu, Ming-Miin & Huang, Mei-ying, 2016. "Risk-based decompositions of the meta profit efficiency of Taiwanese and Chinese banks," Omega, Elsevier, vol. 62(C), pages 34-46.
    8. Yang Li & Yi-Kai Chen & Feng Sheng Chien & Wen Chih Lee & Yi Ching Hsu, 2016. "Study of optimal capital adequacy ratios," Journal of Productivity Analysis, Springer, vol. 45(3), pages 261-274, June.
    9. Li, Yang, 2020. "Analyzing efficiencies of city commercial banks in China: An application of the bootstrapped DEA approach," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).

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    More about this item

    Keywords

    Profit change; Decomposition; Data envelopment analysis (DEA); Directional distance function (DDF); Risk; Undesirable outputs; C23; C61; D22; G21;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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