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Identifying bank outputs and inputs with a directional technology distance function

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  • Paolo Guarda
  • Abdelaziz Rouabah
  • Michael Vardanyan

Abstract

The bank efficiency literature lacks an agreed definition of bank outputs and inputs. This is problematic given the long-standing controversy concerning the status of deposits, but also because bank efficiency estimates are known to be affected by the inclusion of additional outputs such as non-traditional (fee-based) activities or risk measures. This paper proposes a data-driven identification of bank outputs and inputs using the directional technology distance function. While previous applications of this tool used symmetric expansion or contraction directions, we focus on a set of orthogonal directions, each corresponding to an assumption on the input/output status of an individual variable. These directions correspond to a set of different specifications, whose estimated coefficients can be used to determine the input or output status of all variables except the regressand. Our empirical analysis revealed a very consistent pattern across the alternative specifications estimated. There is strong evidence that customer deposits are an input, and that non-performing loans are an important undesirable output. Finally, the orthogonal expansions/contractions we consider avoid the simultaneity problem raised by the “convenient normalization” commonly used to impose linear homogeneity in stochastic frontier estimation. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • 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.
  • Handle: RePEc:kap:jproda:v:40:y:2013:i:2:p:185-195
    DOI: 10.1007/s11123-012-0326-7
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    4. Simone Pieralli, 2019. "Bumper crop or dearth: An economic methodology to identify the disruptive effects of climatic variables on French agriculture [Récolte exceptionnelle ou pénurie : une méthodologie économique pour i," Working Papers hal-02786610, HAL.
    5. Emir Malikov & Subal C. Kumbhakar & Mike G. Tsionas, 2016. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1407-1429, November.
    6. Ferreira, Cândida, 2021. "Efficiency of European Banks in the Aftermath of the Financial Crisis: A Panel Stochastic Frontier Approach," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 36(1), pages 103-124.
    7. Walter Briec & Laurent Cavaignac & Kristiaan Kerstens, 2020. "Input Efficiency Measures: A Generalized, Encompassing Formulation," Operations Research, INFORMS, vol. 68(6), pages 1836-1849, November.
    8. Sunil Mohanty & Hong-Jen Lin, 2021. "Efficiency in China’s Banking Sector: A Comparative Analysis of Pre- and Post-Basel II Eras," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-29, June.
    9. Shirong Zhao, 2020. "Shadow Prices of Non-performing Loans for Chinese Banks in the Post-Crisis Era," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(6), pages 1-8.
    10. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang & Vardanyan, Michael & Zhu, Ning, 2019. "Decomposing banking performance into economic and credit risk efficiencies," European Journal of Operational Research, Elsevier, vol. 277(2), pages 719-726.
    11. Pieralli, Simone & Hüttel, Silke & Odening, Martin, 2014. "Abandonment of milk production under uncertainty and inefficiency: The case of West German farms," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170236, Agricultural and Applied Economics Association.
    12. 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.

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    More about this item

    Keywords

    Distance functions; Efficiency; Banking; Parameterization; C13; D24; G21;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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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