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An Application to Model Uncertainty in Modelling Non-Performing Loans

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  • Mehmet Selman Colak
  • Yavuz Kilic
  • Huseyin Ozturk
  • Mehmet Emre Samci

Abstract

[EN] The asset quality of a banking system has the utmost importance not only for the soundness of the banking sector, but also for other major components of an economy. The lack of consensus on a certain set of variables for modeling asset quality leads to a problem, which is also known as “model uncertainty”. In this study, we investigate how non-performing loans in the Turkish banking system respond to changes in macroeconomic and bank-specific variables. To address model uncertainty, we employ a model averaging approach. Our results confirm the main findings in the literature with regards to the nexus between asset quality and macroeconomic and bank-specific variables. In addition, parameter estimates obtained from 1,023 models using combinations of 10 variables suggest that even under extreme shocks, the NPL ratio of the Turkish banking sector remains within reasonable limits. [TR] Bankacilik sisteminin aktif kalitesi, sadece bankacilik sektorunun saglamligi acisindan degil, ekonominin diger temel bilesenleri acisindan da buyuk onem arz etmektedir. Aktif kalitesinin modellenmesinde belirli bir dizi degisken uzerinde fikir birliginin bulunmamasi, “model belirsizligi” olarak da bilinen bir soruna yol acmaktadir. Bu calismada, Turk bankacilik sistemindeki takipteki kredilerin makroekonomik ve bankaya ozgu degiskenlerdeki degisimlere nasil tepki verdigi incelenmektedir. Model belirsizligi sorununu gidermek icin model ortalamasi yaklasimi kullanilmaktadir. Sonuclarimiz, aktif kalitesi ile makroekonomik ve bankaya ozgu degiskenler arasindaki baglantiya iliskin literaturdeki ana bulgulari dogrulamaktadir. Ayrica, 10 degiskenin kombinasyonu kullanilarak 1023 modelden elde edilen katsayi tahminleri, asiri soklarda bile takipteki kredi oraninin makul sinirlar icinde kaldigini ortaya koymaktadir.

Suggested Citation

  • Mehmet Selman Colak & Yavuz Kilic & Huseyin Ozturk & Mehmet Emre Samci, 2024. "An Application to Model Uncertainty in Modelling Non-Performing Loans," CBT Research Notes in Economics 2404, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  • Handle: RePEc:tcb:econot:2404
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    References listed on IDEAS

    as
    1. Tölö, Eero & Virén, Matti, 2021. "How much do non-performing loans hinder loan growth in Europe?," European Economic Review, Elsevier, vol. 136(C).
    2. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
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    4. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    5. Ari, Anil & Chen, Sophia & Ratnovski, Lev, 2021. "The dynamics of non-performing loans during banking crises: A new database with post-COVID-19 implications," Journal of Banking & Finance, Elsevier, vol. 133(C).
    6. Kryzanowski, Lawrence & Liu, Jinjing & Zhang, Jie, 2023. "Effect of COVID-19 on non-performing loans in China," Finance Research Letters, Elsevier, vol. 52(C).
    7. Vuslat Us, 2016. "Determinants of Non-Performing Loans in the Turkish Banking Sector : What Has Changed After the Global Crisis?," CBT Research Notes in Economics 1627, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    8. William R. Keeton, 1999. "Does faster loan growth lead to higher loan losses?," Economic Review, Federal Reserve Bank of Kansas City, vol. 84(Q II), pages 57-75.
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