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Unravelling the Determinants of Banking Efficiency in Argentina: a two-stage Analysis of the Argentine Banking Sector

Author

Listed:
  • Facundo Costa de Arguibel

    (Universidad Nacional de Misiones)

  • Juan Antonio Dip

    (Universidad Nacional de Misiones)

  • Gerardo Stvass

    (Universidad Nacional de Misiones)

Abstract

In this paper, we apply a two-stage data envelopment analysis to study the effect of the interrelation between banking activities, the ownership structure, and the technical efficiency of Argentine banks (2012-2019). The first stage involves a Bootstrapped DEA to estimate the banks’ technical efficiency with and without service revenues. The second stage estimates a truncated regression with Bootstrap to examine the effect of non-traditional activities and the origin of assets on the technical efficiency of banks. Besides, we control for differences in the entities’ financial risk and the influence of environmental variables. Our robust results show that non-traditional activities are positively related to bank efficiency. Those banks that have a greater presence in non-traditional activities are more efficient. On the other hand, foreign banks with a greater weight in non-traditional activities are more efficient than their local peers. Foreign banks better exploit the advantages of diversification of activities compared to/over their local peers. Finally, public banks are more inefficient than private ones. The results are robust to changes in the selection and specification of certain variables.

Suggested Citation

  • Facundo Costa de Arguibel & Juan Antonio Dip & Gerardo Stvass, 2024. "Unravelling the Determinants of Banking Efficiency in Argentina: a two-stage Analysis of the Argentine Banking Sector," Working Papers 326, Red Nacional de Investigadores en Economía (RedNIE).
    • Handle: RePEc:aoz:wpaper:326
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    File URL: https://rednie.eco.unc.edu.ar/files/DT/326.pdf
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    References listed on IDEAS

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    Keywords

    Banking diversification; Non-traditional activities; Efficiency; Double Bootstrap Regression DEA; Argentina;
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