Financial Frictions and Monetary Policy Effectiveness in Türkiye

Öz

Financial friction affects the real economy through cyclical fluctuations. Therefore, financial friction must be considered when conducting monetary policy. This situation became even more pronounced with the 2008 financial crisis. As a result, many central banks, including the Central Bank of Turkey (CBRT), added a financial stability target alongside their price stability target. However, studies considering the impact of financial friction in Türkiye are quite limited, both in academic research and for policymakers. This study aims to investigate how financial friction affects monetary policy in Türkiye. In this context, the New Keynesian (NK) DSGE model, designed by Gertler and Karadi (2011) and including financial friction originating from the banking sector, has been extended for Turkey and estimated using Bayesian methods for the quarterly period 2011–2024. The findings of the model show that negative shocks originating from the financial system negatively affect investment, consumption, and output. It was observed that monetary policy responds to these shocks with a limited and delayed response. In contrast, an external interest rate shock is strongly transmitted to the real economy through financial friction. These results indicate that financial friction increases the effectiveness of internal monetary policy in Türkiye while strengthening the transmission of an external interest rate shock.

Anahtar Kelimeler

• Financial Frictions
• Monetary Policy
• DSGE Model
• Bayesian Estimation
• Monetary Transmission

Kaynakça

1. Abadi, J., Brunnermeier, M., & Koby, Y. (2023). The reversal interest rate. American Economic Review, 113(8), 2084–2120. google scholar
2. Agénor, P., & Alper, K. (2012). Monetary shocks and central bank liquidity with credit market imperfections. Oxford Economic Papers, 64(3), 563–591. google scholar
3. Agénor, P., Alper, K., & da Silva, L. (2012). Capital requirements and business cycles with credit market imperfections. Journal of Macroeconomics, 34(3), 687–705. google scholar
4. Akerlof, G. A. (1970). The market for “lemons”: Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488–500. google scholar
5. Akın, G., Aysan, A., İleri, S., & Yıldıran, L. (n.d.). Demand and competition analysis in the Turkish deposit and credit markets. Emerging Markets Finance and Trade, 41–58. google scholar
6. Alp, M., & Elekdağ, S. (2011). The role of monetary policy in Turkey during the global financial crisis (IMF Working Paper). International Monetary Fund. google scholar
7. Aysun, U., Brady, R., & Honig, A. (2013). Financial frictions and the strength of monetary transmission. Journal of International Money and Finance, 32, 1097–1119. google scholar
8. Bari, B. (2013). Optimum monetary policy in a New Keynesian model: DSGE model estimation for Turkey (Doctoral dissertation, Anadolu University). google scholar

9. Başçı, E., & Kara, H. (2011). Financial stability and monetary policy. İktisat İşletme ve Finans, 26(302), 9–25. google scholar
10. Bernanke, B. S., & Gertler, M. (1989). Agency costs, net worth, and business fluctuations. American Economic Review, 79(1), 14–31. google scholar
11. Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. In J. B. Taylor & M. Woodford (Eds.), Handbook of macroeconomics (Vol. 1C, pp. 1341–1393). Elsevier. google scholar
12. Bertocco, G., & Kalajzić, A. (2024). A critical analysis of the financial frictions approach in a Minskyan perspective. Journal of Economic Issues, 58(1), 85–111. google scholar
13. Bluwstein, K. (2017). Asymmetric macro-financial spillovers (Working Paper No. 337). Sveriges Riksbank. google scholar
14. Bratsiotis, G., & Kalubowila, C. (2025). The cyclicality of the finance premium over the business cycle. Economic Modelling, 142. google scholar
15. Canova, F. (2007). Methods for applied macroeconomic research. Princeton University Press. google scholar
16. Christiano, L. J., Eichenbaum, M., & Evans, C. L. (2005). Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy, 113(1), 1–45. google scholar
17. Christiano, L., Gust, C., & Roldos, J. (2002). Monetary policy in a financial crisis. google scholar
18. Christiano, L., Motto, R., & Rostagno, M. (2014). Risk shocks. American Economic Review, 104(1), 27–65. google scholar
19. Christiano, L. J., Trabandt, M., & Walentin, K. (2011). Introducing financial frictions and unemployment into a small open economy model. Journal of Economic Dynamics and Control, 35(12), 1999–2041. google scholar
20. Fama, E. F. (1980). Banking in the theory of finance. Journal of Monetary Economics, 6(1), 39–57. google scholar
21. Fligstein, N., Brundage, J. S., & Schultz, M. (2017). Seeing like the Fed: Culture, cognition, and framing in the failure to anticipate the financial crisis of 2008. American Sociological Review, 82(5), 879–909. google scholar
22. Gallegati, M., Giri, F., & Palestrini, A. (2019). DSGE model with financial frictions over subsets of business cycle frequencies. Journal of Economic Dynamics and Control, 100, 152–163. google scholar
23. Gambacorta, L., & Ibanez, D. (2011). The bank lending channel: Lessons from the crisis. Economic Policy. google scholar
24. Gertler, M., & Karadi, P. (2011). A model of unconventional monetary policy. Journal of Monetary Economics, 58(1), 17–34. google scholar
25. Gertler, M., & Kiyotaki, N. (2010). Financial intermediation and credit policy in business cycle analysis. In B. M. Friedman & M. Woodford (Eds.), Handbook of monetary economics (Vol. 3, pp. 547–599). Elsevier. google scholar
26. Gürkaynak, R., Kısacıkoğlu, B., & Lee, S. (2023). Exchange rate and inflation under weak monetary policy: Turkey verifies theory. Economic Policy, 38(115), 519–560. google scholar
27. Herbst, E., & Schorfheide, F. (2015). Bayesian estimation of DSGE models. Princeton University Press. google scholar
28. Jia, D. (2020). Dynamic macroeconomic models in emerging market economies: DSGE modelling with financial and housing sectors. Springer Nature. google scholar
29. Kara, H. (2012). Post-crisis monetary policy (CBRT Working Paper No. 12/17). Central Bank of the Republic of Türkiye. google scholar
30. Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Political Economy, 105(2), 211–248. google scholar
31. Lee, S., Luetticke, R., & Ravn, M. (2021). Financial frictions: Micro vs. macro volatility (ECB Working Paper No. 2622). European Central Bank. google scholar
32. Li, Z. (2022). Financial intermediary leverage and monetary policy transmission. European Economic Review, 144, 104080. google scholar
33. Lieberknecht, P. (2018). Financial frictions, the Phillips curve, and monetary policy (ECB Working Paper). European Central Bank. google scholar
34. Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. American Economic Review, 48(3), 261–297. google scholar
35. Palic, I. (2018). The empirical evaluation of monetary policy shock in dynamic stochastic general equilibrium model with financial frictions: Case of Croatia. International Journal of Engineering Business Management, 10. google scholar
36. Sekmen, A., & Şıklar, İ. (2016). Para politikası ve makro ihtiyati politikalar: Türkiye için tahmin edilmiş bir DSGE modeli. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 16(4), 67–92. google scholar
37. Smets, F., & Wouters, R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, 97(3), 586–606. google scholar
38. Stiglitz, J. E., & Weiss, A. (1981). Credit rationing in markets with imperfect information. American Economic Review, 71(3), 393–410. google scholar
39. Ünal, İ. (2020). Dinamik stokastik genel denge modeli tahminiyle Türkiye ekonomisi için makroekonomik şokların incelenmesi (Uzmanlık tezi). Türkiye Cumhuriyeti Cumhurbaşkanlığı Strateji ve Bütçe Başkanlığı. google scholar
40. Yıldırım, Y., & Anirbal, S. (2021). Financial stress and effect on real economy: The Turkish experience. google scholar