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Journals / MANAS Sosyal Araştırmalar Dergisi / 2021 / Cilt: 10 - Sayı: 2

The Macro Economic Drivers of Non-Performing Loans (NPL): Evidence from Selected Countries with Heterogeneous Panel Analysis

Takipteki Kredilerin Makroekonomik Belirleyicileri: Heterojen Panel Analizi Ile Seçilmiş Ülkelerden Elde Edilen Kanıtlar

Fatih AYHAN
Mustafa Tevfik KARTAL
Pages
986–999
Publication Date
2021-04-19
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The empirical findings reveal that (i) credits, gross domestic products (GDP), and savings have statistically significant negative effect whereas foreign exchange rates (FER) have a statistically insignificant positive effect on NPL for the overall panel; (ii) 1% increase in credits reduces NPL by approximately 2%; (iii); FER have statistically significant effects in some countries at the country base; (iv) negative coefficients for credits, savings, and GDP are consistent in both overall panel and country base.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:NPL could be treated as a critical issue in the financial systems of countries of which have bank-based infrastructures since NPL restrict the credit providing capacity of banks.
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Key Findings & Data:In this context, the study aims to research the drivers of NPL in selected 23 countries. 4 independent drivers and yearly data between 2006 and 2018 are analyzed by using heterogeneous panel analysis.
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Conclusion & Impact:The empirical findings reveal that (i) credits, gross domestic products (GDP), and savings have statistically significant negative effect whereas foreign exchange rates (FER) have a statistically insignificant positive effect on NPL for the overall panel; (ii) 1% increase in credits reduces NPL by approximately 2%; (iii); FER have statistically significant effects in some countries at the country base; (iv) negative coefficients for credits, savings, and GDP are consistent in both overall panel and country base.
🔬Design:Research Article
📍Scope:2006 Verileri
⚙️Variables:Takipteki Krediler · Heterojen Panel Analiz · NPL'nin Belirleyicileri

Abstract

NPL could be treated as a critical issue in the financial systems of countries of which have bank-based infrastructures since NPL restrict the credit providing capacity of banks. Hence, necessary financing sources for economic growth and development could not be provided. In this context, the study aims to research the drivers of NPL in selected 23 countries. 4 independent drivers and yearly data between 2006 and 2018 are analyzed by using heterogeneous panel analysis. The empirical findings reveal that (i) credits, gross domestic products (GDP), and savings have statistically significant negative effect whereas foreign exchange rates (FER) have a statistically insignificant positive effect on NPL for the overall panel; (ii) 1% increase in credits reduces NPL by approximately 2%; (iii); FER have statistically significant effects in some countries at the country base; (iv) negative coefficients for credits, savings, and GDP are consistent in both overall panel and country base.

Özet

Takipteki Krediler (NPL), bankaların kredi sağlama kapasitesini kısıtladığından, banka tabanlı altyapısı olan ülkelerin finansal sistemlerinde kritik bir konu olarak ele alınabilmektedir. Dolayısıyla bu durum ekonomik büyüme ve kalkınma için gerekli finansman kaynakları sağlanamamasına neden olmaktadır. Bu bağlamda, çalışma seçilmiş 23 ülkede NPL’nin belirleyicilerini araştırmayı amaçlamaktadır. 4 bağımsız belirleyici 2006-2018 arasındaki yıllık verileri ile heterojen panel analizi kullanılarak analiz edilmiştir. Ampirik bulgular, (i) krediler, gayri safi yurtiçi hasıla (GSYİH) ve tasarrufların istatistiksel olarak anlamlı negatif etkiye sahip olduğunu, buna karşılık döviz kurlarının (FER) NPL üzerinde istatistiksel olarak anlamlı olmayan pozitif bir etkiye sahip olduğunu ortaya koymaktadır; (ii) Kredilerdeki % 1'lik artış NPL’yi yaklaşık % 2 oranında azaltmakta; (iii); FER'in bazı ülkelerde ülke bazında istatistiksel olarak önemli etkileri vardır; (iv) krediler, tasarruflar ve GSYİH için negatif katsayılar hem genel panel hem de ülke bazında tutarlıdır.

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Cite This Article

AYHAN, F., KARTAL, M. T. (2021). The Macro Economic Drivers of Non-Performing Loans (NPL): Evidence from Selected Countries with Heterogeneous Panel Analysis. MANAS Sosyal Araştırmalar Dergisi, Cilt: 10 - Sayı: 2, 986–999. https://ajindex.com/articles/132153

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References (10)

  1. Alandejani, M., & Asutay, M. (2017). Nonperforming Loans in the GCC Banking Sectors: Does the Islamic Finance Matter? Research in International Business and Finance, (42), 832-854. doı: 10.1016/j.ribaf.2017.07.02 Baltagi, B. (2008). Econometric Analysis of Panel Data (4th ed.). Hoboken, NJ: John Wiley & Sons. Baltagi, B. H., Feng, Q., & Kao, C. (2012). A Lagrange Multiplier Test for Cross-Sectional Dependence in a Fixed Effects Panel Data Model. Journal of Econometrics, 170(1), 164-177. doi: https://doi.org/10.1016/j.jeconom.2012.04.004
  2. Barseghyan, L. (2010).
  3. Non-Performing Loans, Prospective Bailouts, and Japan's Slowdown. Journal of Monetary Economics, 57(7), 873-890.https://doi.org/10.1016/j.jmoneco.2010.08.002
  4. Beck, R., Jakubik, P., & Piloui, A. (2013). Non-Performing Loans What Matters in Addition to the Economic Cycle? ECB Working Paper, No. 1515. Frankfurt am Main, Germany: European Central Bank. ISSN 1725-2806 (online) Breusch, T., & Pagan, A. (1980). The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics. Review of Economic Studies, 47(1), 239-253. Stable URL: https://www.jstor.org/stable/2297111
  5. Bilgin, M. H., Gözgör, G., Lau, C. K. M., & Sheng, X. (2018). The Effects of Uncertainty Measures on the Price of Gold. International Review of Financial Analysis, 58, 1-7. Doi: https://doi.org/10.1016/j.irfa.2018.03.009
  6. Boudriga, A., Taktak, N. B., & Jellouli, S. (2010).
  7. Bank Specific, Business and Institutional Environment Determinants of Banks Nonperforming Loans: Evidence from MENA Countries. Dokki, Cairo Egypt: The Economic Research Forum (ERF), Economic Research Forum Working Paper Nu: 547. Buncic, D., & Melecky, M. (2013). Macroprudential Stress Testing of Credit Risk: A Practical Approach for Policy Makers. Journal of Financial Stability, 9(3), 347-370. Doi: https://doi.org/10.1016/j.jfs.2012.11.003
  8. Das, A., & Ghosh, S. (2007). Determinants of Credit Risk in Indian State-Owned Banks: An Empirical Investigation. Published in: Economic Issues, 12(2), 48-66.
  9. De Bock, R., & Demyanets, A. (2012). Bank Asset Quality in Emerging Markets: Determinants and Spillovers. IMF Working Paper, No. 12/71. Dimitrios, A., Helen, L., & Mike, T. (2016). Determinants of Non-Performing Loans: Evidence from Euro-Area Countries. Finance Research Letters, (18), 116-119. Doi: https://doi.org/10.1016/j.frl.2016.04.008
  10. Distinguin, I., Roulet, C., & Tarazi, A. (2013). Bank Regulatory Capital and Liquidity: Evidence from US and European Publicl