Determinants of Bank Stability: A Financial Statement Analysis of Turkish Banks

Year 2018, Volume: 26 Issue: 38, 87 - 103, 31.10.2018

Gamze Danışman

https://doi.org/10.17233/sosyoekonomi.2018.04.06

Cited By: 11

Abstract

This paper attempts a financial statement analysis of Turkish banks and explores the determinants of bank stability, as proxied by non-performing loans ratio, using annual data on 27 Turkish banks for the years 2007-2015. We employ dynamic panel data estimation techniques by using the system GMM estimation techniques. Our results indicate that the significant determinants of NPLs that are able to explain the credit risk of Turkish banks include return on assets (ROA), loans to asset ratio, inefficiency index, non-interest income share and loan loss provisions share. We contribute to the literature by properly accounting for endogeneity with adequate specification and validation tests.

Keywords

Credit Risk, Determinants, Bank Stability, Non-performing Loans, System-GMM

Banka İstikrarının Belirleyicileri: Türkiye’deki Bankaların Mali Tabloları Üzerinde Bir İnceleme

Abstract

Bu çalışmada, Türk bankalarının mali tablo analizi ve takipteki kredilerin belirleyicileri incelenmektedir. 2007-2015 yılları için 27 adet Türk bankasının yıllık verileri kullanılmıştır. Sistem GMM yöntemiyle dinamik panel veri analizi metodolojisi kullanılmıştır. Bulgulara göre, bankalara özgü belirleyiciler aktif kârlılık, krediler-varlık toplamı oranı, verimsizlik endeksi, faiz dışı gelir oranı ve kredi zararı karşılıkları oranı olarak belirlenmiştir. Bu çalışma ile endojenite spesifikasyon ve doğrulama testleri uygun bir şekilde kontrol edilerek literatüre katkıda bulunmak amaçlanmaktadır.

Keywords

Banka İstikrarı, Kredi Riski, Takipteki Krediler, Belirleyiciler, Sistem-GMM

References

• Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. The Review of Economic Studies, 58(2), 277–297.
• Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51.
• Beck, R., Jakubik, P., & Piloiu, A. (2013). Non-performing loans: what matters in addition to the economic cycle? (Working Paper Series No. 1515). European Central Bank.
• Berger, A.N. & DeYoung, R. (1997). Problem loans and cost efficiency in commercial banks. Journal of Banking & Finance, 21(6), 849-870.
• Bernanke, B., & Gertler, M. (1989). Agency Costs, Net Worth, and Business Fluctuations. The American Economic Review, 79(1), 14–31.
• Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.
• Blundell, R., Bond, S., & Windmeijer, F. (2000). Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator (IFS Working Paper No. W00/12). Institute for Fiscal Studies.
• Bond, S. (2002). Dynamic panel data models: a guide to microdata methods and practice (CeMMAP working paper No. CWP09/02). Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Bond, S., Windmeijer, F., 2002. Finite sample inference for GMM estimators in linear panel data models. CeMMAP working papers no. CWP04/02. Centre for Microdata Methods and Practice, Institute for Fiscal Studies, London, UK.
• Boudriga, A., Taktak, N. B., & Jellouli, S. (2009). Banking supervision and nonperforming loans: a cross‐country analysis. Journal of Financial Economic Policy, 1(4), 286–318.
• Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI. Economic Modelling, 31, 672–683.
• CBRT (2013). Financial Stability Report, May, available at http://www.tcmb.gov.tr/wps/wcm/connect/1e6711f8-5dc8-463d-bd22-bad590904c8a/foreword16.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-1e6711f8-5dc8-463d-bd22-bad590904c8a-m3fw7tk
• CBRT (2017). Financial Stability Report, November, available at http://www.tcmb.gov.tr/wps/wcm/connect/37d4a3c3-f8f9-4973-aa85-93a5ce138c50/foreword25.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-37d4a3c3-f8f9-4973-aa85-93a5ce138c50-m52fcfI
• Espinoza, R., & Prasad, A. (2010). Nonperforming Loans in the GCC Banking System and their Macroeconomic Effects (IMF Working Paper No. 10/224). International Monetary Fund.
• García-Marco, T. & Robles-Fernández, M. D. (2008). Risk-taking behavior and ownership in the banking industry: The Spanish evidence. Journal of Economics and Business, 60(4), 332-354.
• Ghosh, A. (2015). Banking-industry specific and regional economic determinants of non-performing loans: Evidence from US states. Journal of Financial Stability, 20, 93–104.
• Gonzalez, F. (2005). Bank regulation and risk-taking incentives: An international comparison of bank risk. Journal of Banking & Finance, 29(5), 1153–1184.
• Hansen, L. P. (1982). Large Sample Properties of Generalized Method of Moments Estimators. Econometrica, 50(4), 1029–1054.
• Hasan, I. & Wall, L. D. (2004). Determinants of the Loan Loss Allowance: Some Cross‐Country Comparisons. Financial Review, 39(1), 129–152.
• Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating Vector Autoregressions with Panel Data. Econometrica, 56(6), 1371–1395.
• Hu Jin‐Li, Li Yang, & Chiu Yung‐Ho. (2007). Ownership and nonperforming loans: evidence from taiwan’s banks. The Developing Economies, 42(3), 405–420.
• Isik, O. & Bolat, S. (2016). Determinants of nonperforming loans of deposit banks in Turkey. Journal of Business, Economics and Finance, 5(4), 341-350.
• Jakubík, P., & Reininger, T. (2013). Determinants of Nonperforming Loans in Central, Eastern and Southeastern Europe. Focus on European Economic Integration, (3), 48–66.
• Judson, R. A., & Owen, A. (1999). Estimating dynamic panel data models: a guide for macroeconomists. Economics Letters, 65(1), 9–15.
• Keeton, W. & Morris, C. (1987). Why Do Banks’ Loan Losses Differ? Federal Reserve Bank of Kansas City Economic Review, May, 3–21.
• Khemraj, T., & Pasha, S. (2009). The determinants of non-performing loans: an econometric case study of Guyana (MPRA Paper No. 53128). University Library of Munich, Germany.
• Kiyotaki, N., & Moore, J. (1997). Credit Cycles. Journal of Political Economy, 105(2), 211–248.
• Klein, N. (2013). Non-Performing Loans in CESEE; Determinants and Impact on Macroeconomic Performance (IMF Working Papers No. 13/72). International Monetary Fund.
• Koehn, M. & Santomero, A. (1980). Regulation of bank capital and portfolio risk. Journal of Finance, 35(5), 1235-1244.
• Louzis, D. P., Vouldis, A. T., & Metaxas, V. L. (2010). Macroeconomic and Bank-Specific Determinants of Non-Performing Loans in Greece: A Comparative Study of Mortgage, Business and Consumer Loan Portfolios (SSRN Scholarly Paper No. ID 1703026). Rochester, NY: Social Science Research Network.
• Macit, F. (2012). What Determines The Non-Performing Loans Ratio: Evidence From Turkish Commercial Banks. CEA Journal of Economics, 7(1).
• Makri, V., Tsaganos, A., & Bellas, A. (2014). Determinants of Non-Performing Loans: The Case of Eurozone (SSRN Scholarly Paper No. ID 2411932). Rochester, NY: Social Science Research Network.
• Morakinyo, A. E., & Sibanda, M. (2016). The Determinants of Non-Performing Loans in the ‘MINT’ Economies. Journal of Economics and Behavioral Studies, 8(5), 39–55.
• Nkusu, M. (2011). Nonperforming Loans and Macrofinancial Vulnerabilities in Advanced Economies (SSRN Scholarly Paper No. ID 1888904). Rochester, NY: Social Science Research Network.
• Ouhibi, S., & Hammami, S. (2015). Determinants of nonperforming loans in the Southern Mediterranean countries. International Journal of Accounting and Economics Studies, 3(1), 50–53.
• Rajan R. (1994). Why Bank Credit Policies Fluctuate: A Theory and Some Evidence. The Quarterly Journal of Economics, 109, 399-441
• Rime, B. (2001). Capital requirements and bank behaviour: empirical evidence for Switzerland. Journal of Banking & Finance, 25(5), 789-805.
• Roodman, D. (2009a). How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal, 9(1), 86–136.
• Roodman, D. (2009b). A Note on the Theme of Too Many Instruments*. Oxford Bulletin of Economics and Statistics, 71(1), 135–158.
• Salas, V., & Saurina, J. (2002). Credit Risk in Two Institutional Regimes: Spanish Commercial and Savings Banks. Journal of Financial Services Research, 22(3), 203–224.
• Skarica, B. (2014). Determinants of non-performing loans in Central and Eastern European countries. Financial Theory and Practice, 38(1), 37–59.
• Stern, G.H. & Feldman, R.J. (2004). Too Big To Fail: The Hazards of Bank Bailouts. Brookings Institution Press, Washington, DC, USA.
• Us, V. (2016). Determinants of Non-Performing Loans in the Turkish Banking Sector: What Has Changed After the Global Crisis? The Central Bank of Turkey Research Notes in Economics, No. 16/27,1-14.
• Vithessonthi, C. (2016). Deflation, bank credit growth, and non-performing loans: Evidence from Japan. International Review of Financial Analysis, 45, 295–305.
• Williams, J. (2004). Determining Management Behaviour in European Banking. Journal of Banking & Finance, 28(10), 2427-2460.
• Windmeijer, F. (2005). A Finite Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators. Journal of Econometrics, 126(1), 25–51.