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Technical and allocative efficiency in European banking


  • Brissimis, Sophocles N.
  • Delis, Manthos D.
  • Tsionas, Efthymios G.


This paper specifies an empirical framework for estimating both technical and allocative efficiency using the translog cost-share system, thus providing a solution to the issue known in the literature as the Greene problem. The model is applied to a large panel of European banks and the results are compared with those of a model that does not include an allocative inefficiency term and also with those obtained by using a consistent Bayesian technique. Our results suggest that models which include only technical efficiency, significantly overestimate it, while parameter estimates from the model that includes both technical and allocative efficiency are very close to the ones obtained from the Bayesian approach, thus enhancing our confidence in the proposed methodology. Finally, the fact that allocative efficiency of banks in our sample improves more than technical efficiency underlines the importance of including an allocative inefficiency component in parametric efficiency models.

Suggested Citation

  • Brissimis, Sophocles N. & Delis, Manthos D. & Tsionas, Efthymios G., 2010. "Technical and allocative efficiency in European banking," European Journal of Operational Research, Elsevier, vol. 204(1), pages 153-163, July.
  • Handle: RePEc:eee:ejores:v:204:y:2010:i:1:p:153-163

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    References listed on IDEAS

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    Cited by:

    1. Gavilan, Jose M. & Ortega Irizo, Fco. Javier, 2015. "On the Ability to Disentangle the Two Errors in the Normal/Half-Normal Stochastic Frontier Model /Sobre la capacidad de separar los dos errores en el modelo de frontera estocástica normal/half-normal," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 33, pages 619-632, Mayo.
    2. George Furstenberg, 2008. "Assessing the Competitiveness of International Financial Services in Particular Locations: A Survey of Methods and Perspectives," Open Economies Review, Springer, vol. 19(4), pages 539-556, September.
    3. Tsionas, Efthymios G. & Assaf, A. George & Matousek, Roman, 2015. "Dynamic technical and allocative efficiencies in European banking," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 130-139.
    4. Manthos Delis & Anastasia Koutsomanoli-Fillipaki & Christos Staikouras & Gerogiannaki Katerina, 2009. "Evaluating cost and profit efficiency: a comparison of parametric and nonparametric methodologies," Applied Financial Economics, Taylor & Francis Journals, vol. 19(3), pages 191-202.
    5. Wanke, Peter & Maredza, Andrew & Gupta, Rangan, 2017. "Merger and acquisitions in South African banking: A network DEA model," Research in International Business and Finance, Elsevier, vol. 41(C), pages 362-376.
    6. Tsionas, Mike G., 2016. "Parameters measuring bank risk and their estimation," European Journal of Operational Research, Elsevier, vol. 250(1), pages 291-304.
    7. Alexandros E. Milionis, 2006. "An Alternative Definition of Market Efficiency and some Comments on its Empirical Testing," Working Papers 50, Bank of Greece.
    8. Tecles, Patricia Langsch & Tabak, Benjamin M., 2010. "Determinants of bank efficiency: The case of Brazil," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1587-1598, December.
    9. Assaf, A. George & Gillen, David & Tsionas, Efthymios G., 2014. "Understanding relative efficiency among airports: A general dynamic model for distinguishing technical and allocative efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 18-34.
    10. Georges Assaf, A. & Gillen, David, 2012. "Measuring the joint impact of governance form and economic regulation on airport efficiency," European Journal of Operational Research, Elsevier, vol. 220(1), pages 187-198.
    11. George M. von Furstenberg, 2007. "Aspects, Models and Measures for Assessing the Competitiveness of International Financial Services in a Particular Location," Working Papers 182007, Hong Kong Institute for Monetary Research.
    12. Degl'Innocenti, Marta & Kourtzidis, Stavros A. & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank productivity growth and convergence in the European Union during the financial crisis," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 184-199.
    13. Randrianarisoa, Laingo Manitra & Bolduc, Denis & Choo, Yap Yin & Oum, Tae Hoon & Yan, Jia, 2015. "Effects of corruption on efficiency of the European airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 79(C), pages 65-83.
    14. Subal Kumbhakar & Frank Asche & Ragnar Tveteras, 2013. "Estimation and decomposition of inefficiency when producers maximize return to the outlay: an application to Norwegian fishing trawlers," Journal of Productivity Analysis, Springer, vol. 40(3), pages 307-321, December.
    15. Maria-Eleni K. Agoraki & Manthos D. Delis & Panagiotis K. Staikouras, 2010. "The effect of board size and composition on bank efficiency," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 2(4), pages 357-386.
    16. Horst Gischer & Toni Richter, 2014. "Produktivitätsmessung von Banken: die Cost Income Ratio – ein belastbares Performancemaß?," FEMM Working Papers 140008, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    17. Luintel, Kul B. & Selim, Sheikh & Bajracharya, Pushkar, 2017. "Liberalization, bankers’ motivation and productivity: A simple model with an application," Economic Modelling, Elsevier, vol. 61(C), pages 102-112.
    18. Huang, Wei & Eling, Martin, 2013. "An efficiency comparison of the non-life insurance industry in the BRIC countries," European Journal of Operational Research, Elsevier, vol. 226(3), pages 577-591.
    19. Mihăiță-Cosmin M. POPOVICI, 2014. "Impact Of Financial Crisis On Banking Efficiency: Evidence From Romania," SEA - Practical Application of Science, Fundația Română pentru Inteligența Afacerii, Editorial Department, issue 3, pages 451-456, April.
    20. Matousek, Roman & Rughoo, Aarti & Sarantis, Nicholas & George Assaf, A., 2015. "Bank performance and convergence during the financial crisis: Evidence from the ‘old’ European Union and Eurozone," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 208-216.
    21. Wanke, Peter & Barros, Carlos P. & Faria, João R., 2015. "Financial distress drivers in Brazilian banks: A dynamic slacks approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 258-268.
    22. Kumbhakar, Subal C., 2011. "Estimation of production technology when the objective is to maximize return to the outlay," European Journal of Operational Research, Elsevier, vol. 208(2), pages 170-176, January.
    23. Fujii, Hidemichi & Managi, Shunsuke & Matousek, Roman & Rughoo, Aarti, 2017. "Bank Efficiency, Productivity and Convergence in EU countries: A Weighted Russell Directional Distance Model," MPRA Paper 77237, University Library of Munich, Germany.
    24. Peter Wanke & Carlos Barros & Nkanga Pedro João Macanda, 2016. "Predicting Efficiency in Angolan Banks: A Two-Stage TOPSIS and Neural Networks Approach," South African Journal of Economics, Economic Society of South Africa, vol. 84(3), pages 461-483, September.
    25. repec:eee:ejores:v:266:y:2018:i:2:p:746-760 is not listed on IDEAS

    More about this item


    Technical and allocative efficiency Translog cost function Maximum likelihood European banking;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior


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