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The effect of NPLs management in the PIIGS banking efficiency: an approach using non-parametric partial order-m frontiers

Author

Listed:
  • Emmanouil G. Chalampalakis
  • Ioannis Dokas
  • Eleftherios Spyromitros

Abstract

Purpose - This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from 2009 to 2018. Design/methodology/approach - A conditional robust nonparametric frontier analysis (order-m estimators) is used to measure banking efficiency combined with variables highlighting the effects of Non-Performing Loans. Next, a truncated regression is used to examine if institutional, macroeconomic, and financial variables affect bank performance differently. Unlike earlier studies, we use the Corruption Perception Index (CPI) as an institutional variable that affects banking sector efficiency. Findings - This research shows that the PIIGS crisis affects each bank/country differently due to their various efficiency levels. Most of the study variables — CPI, government debt to GDP ratio, inflation, bank size — significantly affect banking efficiency measures. Originality/value - The contribution of this article to the relevant banking literature is two-fold. First, it analyses the efficiency of the PIIGS banking system from 2009 to 2018, focusing on NPLs. Second, this is the first empirical study to use probabilistic frontier analysis (order-m estimators) to evaluate PIIGS banking systems.

Suggested Citation

  • Emmanouil G. Chalampalakis & Ioannis Dokas & Eleftherios Spyromitros, 2023. "The effect of NPLs management in the PIIGS banking efficiency: an approach using non-parametric partial order-m frontiers," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(3), pages 692-711, August.
  • Handle: RePEc:eme:jespps:jes-12-2022-0678
    DOI: 10.1108/JES-12-2022-0678
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    More about this item

    Keywords

    Bank efficiency; PIIGS; NPLs; LLPs; Partial frontiers; m-order estimator; Truncated regression; Corruption perception index; E10; M41; G21; C67; C80;
    All these keywords.

    JEL classification:

    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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