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Determinants of Nonperforming Loans: A Global Data Analysis

Author

Listed:
  • MBelen Salas

    (Universidad de Málaga)

  • Prosper Lamothe

    (Universidad autónoma de Madrid)

  • Enrique Delgado

    (Universidad autónoma de Madrid)

  • Angel L. Fernández-Miguélez

    (Universidad de Málaga)

  • Lucia Valcarce

    (Universidad de Málaga)

Abstract

This Study Analyzes the Factors that Explain the Evolution of banks´ Nonperforming loan Ratios Worldwide. We use a Sample of 1,631 Entities from 111 Countries Grouped into the Eight Central Regions in the World, with Information Corresponding to the Period 2007–2021. Applying Panel data Methods and an Extensive set of both Specific and Macroeconomic Variables, the Results show that Nonperforming loan Ratio is Determined by a Series of Specific Factors, Regardless of where or when they Operate. These Results may be Helpful to Minimize the cost of Building Models for the Nonperforming loan Analysis in the world´s most Critical Regions.

Suggested Citation

  • MBelen Salas & Prosper Lamothe & Enrique Delgado & Angel L. Fernández-Miguélez & Lucia Valcarce, 2024. "Determinants of Nonperforming Loans: A Global Data Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2695-2716, November.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:5:d:10.1007_s10614-023-10543-8
    DOI: 10.1007/s10614-023-10543-8
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    Keywords

    Nonperforming loan; Dynamic Panel data; Credit risk; Bank Industry; Global Economy;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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