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Determinants of Non-performing Loans: A Panel Data Approach

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Abstract

This paper considers a panel of 80 countries across all continents, over the period 1999–2019, and uses panel generalized method of moments system estimations with data from the World Bank Global Financial Development database, to explain the evolution of the bank non-performing-loans-to-total-loans ratio. The results obtained provide clear evidence that banks with high profitability, benefiting from market stability and located in countries with increasing economic growth are not expected to have high values of the non-performing-loans-to-total-loans ratio. On the other hand, high values of this ratio are robustly associated with an increase of the bank-cost-to-income ratio, market concentration, and bank regulation. The paper also contributes to the literature by assessing the relevance of the level of each country’s income and economic integration. Overall, the results obtained reveal few differences between high-income and non-high-income countries and between Organization for Economic Cooperation and Development (OECD) countries and non-OECD countries. However, considering only the years after the onset of the global financial crisis (2009–2019), there is robust evidence that bank regulation contributed to a decrease in the non-performing-loans-to-total-loans ratio, but only in non-high-income countries and non-OECD countries. Finally, the results for all considered panels, clearly show that the promotion of economic growth is always the best way to assure a decrease in the non-performing-loans-to-total-loans ratio, reducing the likelihood of banking losses as well as potential financial crisis.

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Notes

  1. The specification of the countries included in each panel is provided in Online Supplemental Appendix Table 2.

  2. Online Supplemental Appendix Table 3 presents descriptive statistics and correlation matrices for all panels over the period 1999–2019. Online Supplemental Appendix Table 4 presents the descriptive statistics and correlation matrices for all panels for the years after the global financial crisis (2009–2019).

  3. The results for the model including all independent variables (Model 1) are not reported herein, but are available upon request.

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Acknowledgements

The author thanks the participants at the 93rd International Atlantic Economic Conference, 30 March 2022-2 April 2022, as well as to the Editor-in-Chief and an anonymous Referee, for their most helpful comments, critics, and suggestions. The usual disclaimer remains. The author also acknowledges financial support from Fundação para a Ciência e Tecnologia (Portugal), national funding through research grant UIDB/05069/2020.

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  1. UECE -Research Unit in Complexity and Economics, REM – Research in Economics and Mathematics, ISEG, UL – Lisbon School of Economics and Management of the Universidade de Lisboa, Lisbon, Portugal

    Cândida Ferreira

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Ferreira, C. Determinants of Non-performing Loans: A Panel Data Approach. Int Adv Econ Res 28, 133–153 (2022). https://doi.org/10.1007/s11294-022-09860-9

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