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Profit and cost efficiency in the Italian banking industry (2006-2011)

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  • Francesco Aiello
  • Graziella Bonanno
Abstract
This study evaluates the cost and the profit efficiency of Italian banking sector over the period 2006-2011. Translog stochastic frontiers are used for this purpose. Following the intermediation approach, efficiency scores are computed from estimating a model with three inputs and three outputs. Results indicate that Italian banks perform well, given that the average levels of cost and profit efficiency are both around 90% and they are quite stable over time. However, there is high heterogeneity in results. Differences have been found when banks are classified by size (efficiency tends to decrease with size), legal type (cooperatives perform better than others) and area (the best performers are in the North East of the country).

Suggested Citation

  • Francesco Aiello & Graziella Bonanno, 2013. "Profit and cost efficiency in the Italian banking industry (2006-2011)," Economics and Business Letters, Oviedo University Press, vol. 2(4), pages 190-205.
    • Handle: RePEc:ove:journl:aid:10024
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    File URL: https://reunido.uniovi.es/index.php/EBL/article/view/10024
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    Cited by:

    1. Francesco Aiello & Graziella Bonanno, 2018. "On The Sources Of Heterogeneity In Banking Efficiency Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 32(1), pages 194-225, February.
    2. Abayomi Oredegbe, 2021. "Cost Efficiency Determinants: Evidence from the Canadian Banking Industry," International Journal of Business and Management, Canadian Center of Science and Education, vol. 15(1), pages 1-86, July.
    3. 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.
    4. Prakash, Navendu & Singh, Shveta & Sharma, Seema, 2021. "Technological diffusion, banking efficiency and Solow's paradox: A frontier-based parametric and non-parametric analysis," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 534-551.
    5. Cândida Ferreira, 2020. "Evaluating European Bank Efficiency Using Data Envelopment Analysis: Evidence in the Aftermath of the Recent Financial Crisis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 391-405, November.
    6. Graziella Bonanno, 2014. "The Efficiency of the Italian Banking System over 2006-2011. An Application of the Stochastic Frontier Approach," Rivista italiana degli economisti, Società editrice il Mulino, issue 2, pages 277-306.
    7. Francesco Aiello & Graziella Bonanno, 2016. "Efficiency in banking: a meta-regression analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(1), pages 112-149, January.
    8. Md. Hashibul Hassan & Mahmudul Hassan, 2018. "Cost efficiency of banking sector of Bangladesh: evidence using the stochastic frontier analysis," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 8(6), pages 208-224, June.
    9. Arbelo-Pérez, Marta & Arbelo, Antonio & Pérez-Gómez, Pilar, 2017. "Impact of quality on estimations of hotel efficiency," Tourism Management, Elsevier, vol. 61(C), pages 200-208.
    10. Brianzoni, Serena & Campisi, Giovanni & Colasante, Annarita, 2022. "Nonlinear banking duopoly model with capital regulation: The case of Italy," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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