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A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of U.S. Banks in 2001-2010

Author

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  • Malikov, Emir
  • Kumbhakar, Subal C.
  • Tsionas, Efthymios
Abstract
This paper offers a methodology to address the endogeneity of inputs in the directional technology distance function (DTDF) based formulation of banking technology which explicitly accommodates the presence of undesirable nonperforming loans --- an inherent characteristic of the bank's production due to its exposure to credit risk. Specifically, we model nonperforming loans as an undesirable output in the bank's production process. Since the stochastic DTDF describing banking technology is likely to suffer from the endogeneity of inputs, we propose addressing this problem by considering a system consisting of the DTDF and the first-order conditions from the bank's cost minimization problem. The first-order conditions also allow us to identify the "cost-optimal" directional vector for the banking DTDF, thus eliminating the uncertainty associated with an ad hoc choice of the direction. We apply our cost system approach to the data on large U.S. commercial banks for the 2001-2010 period, which we estimate via Bayesian MCMC methods subject to theoretical regularity conditions. We document dramatic distortions in banks' efficiency, productivity growth and scale elasticity estimates when the endogeneity of inputs is assumed away and/or the DTDF is fitted in an arbitrary direction.

Suggested Citation

  • Malikov, Emir & Kumbhakar, Subal C. & Tsionas, Efthymios, 2015. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of U.S. Banks in 2001-2010," MPRA Paper 66490, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:66490
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    References listed on IDEAS

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    1. Berger, Allen N. & Mester, Loretta J., 2003. "Explaining the dramatic changes in performance of US banks: technological change, deregulation, and dynamic changes in competition," Journal of Financial Intermediation, Elsevier, vol. 12(1), pages 57-95, January.
    2. William A. Barnett & Michael Wolfe, 2004. "Semi-nonparametric Bayesian Estimation of the Asymptotically Ideal Production Model1," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 303-349, Emerald Group Publishing Limited.
    3. Feng, Guohua & Serletis, Apostolos, 2010. "Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 127-138, January.
    4. Paolo Guarda & Abdelaziz Rouabah & Michael Vardanyan, 2013. "Identifying bank outputs and inputs with a directional technology distance function," Journal of Productivity Analysis, Springer, vol. 40(2), pages 185-195, October.
    5. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
    6. Zelenyuk, Valentin, 2013. "A scale elasticity measure for directional distance function and its dual: Theory and DEA estimation," European Journal of Operational Research, Elsevier, vol. 228(3), pages 592-600.
    7. George Assaf, A. & Matousek, Roman & Tsionas, Efthymios G., 2013. "Turkish bank efficiency: Bayesian estimation with undesirable outputs," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 506-517.
    8. Guohua Feng & Apostolos Serletis, 2009. "Efficiency and productivity of the US banking industry, 1998-2005: evidence from the Fourier cost function satisfying global regularity conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 105-138.
    9. Emir Malikov & Subal C. Kumbhakar & Efthymios G. Tsionas, 2015. "Bayesian Approach to Disentangling Technical and Environmental Productivity," Econometrics, MDPI, vol. 3(2), pages 1-23, June.
    10. Hughes, Joseph P. & Mester, Loretta J., 2013. "Who said large banks don’t experience scale economies? Evidence from a risk-return-driven cost function," Journal of Financial Intermediation, Elsevier, vol. 22(4), pages 559-585.
    11. Joseph P. Hughes & Loretta J. Mester, 1998. "Bank Capitalization And Cost: Evidence Of Scale Economies In Risk Management And Signaling," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 314-325, May.
    12. Berger, Allen N. & Demsetz, Rebecca S. & Strahan, Philip E., 1999. "The consolidation of the financial services industry: Causes, consequences, and implications for the future," Journal of Banking & Finance, Elsevier, vol. 23(2-4), pages 135-194, February.
    13. Berger, Allen N. & Mester, Loretta J., 1997. "Inside the black box: What explains differences in the efficiencies of financial institutions?," Journal of Banking & Finance, Elsevier, vol. 21(7), pages 895-947, July.
    14. Xavier Freixas & Jean-Charles Rochet, 2008. "Microeconomics of Banking, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262062704, April.
    15. Diego Restrepo-Tobón & Subal Kumbhakar, 2015. "Nonparametric estimation of returns to scale using input distance functions: an application to large U.S. banks," Empirical Economics, Springer, vol. 48(1), pages 143-168, February.
    16. Feng, Guohua & Zhang, Xiaohui, 2012. "Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1883-1895.
    17. Altunbas, Yener & Liu, Ming-Hau & Molyneux, Philip & Seth, Rama, 2000. "Efficiency and risk in Japanese banking," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1605-1628, October.
    18. William A. Barnett, 2004. "Tastes and Technology: Curvature Is Not Sufficient for Regularity," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 429-433, Emerald Group Publishing Limited.
    19. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464.
    20. Sealey, Calvin W, Jr & Lindley, James T, 1977. "Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions," Journal of Finance, American Finance Association, vol. 32(4), pages 1251-1266, September.
    21. Feng, Guohua & Serletis, Apostolos, 2014. "Undesirable outputs and a primal Divisia productivity index based on the directional output distance function," Journal of Econometrics, Elsevier, vol. 183(1), pages 135-146.
    22. Park, Kang H. & Weber, William L., 2006. "A note on efficiency and productivity growth in the Korean Banking Industry, 1992-2002," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2371-2386, August.
    23. Emir Malikov & Diego Restrepo-Tobón & Subal Kumbhakar, 2015. "Estimation of banking technology under credit uncertainty," Empirical Economics, Springer, vol. 49(1), pages 185-211, August.
    24. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    25. Koutsomanoli-Filippaki, Anastasia & Margaritis, Dimitris & Staikouras, Christos, 2009. "Efficiency and productivity growth in the banking industry of Central and Eastern Europe," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 557-567, March.
    26. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    27. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    28. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
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    More about this item

    Keywords

    Bad Outputs; Commercial Banks; Directional Distance Function; Endogeneity; MCMC; Nonperforming Loans; Productivity; Technical Change;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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