Impact of Credit Ratings and Credit Default Swap (CDS) on Turkey’s Borrowing: Comparative Analysis with G7 Countries

Year 2025, Volume: 12 Issue: 2, 292 - 317, 13.08.2025

Yusuf Özalp , Server Demirci

https://doi.org/10.26650/JEPR1614878

Abstract

This study investigates the effect of credit default swap (CDS) premiums on government bond yields, focusing specifically on Turkey and the G7 countries. CDS is a financial derivative that provides protection to lenders against default risk, whereas government bond yields indicate the annual return on sovereign debt instruments. Variations in CDS premiums reflect investor confidence in a country’s creditworthiness, while bond yields are a direct indicator of perceived sovereign risk. Understanding the relationship between these two variables is essential for evaluating the impact of macroeconomic risk perceptions on investor decisions. For Turkey, time series analysis was employed to assess both the long-term equilibrium and short-term dynamics between CDS premiums and bond yields. The Johansen co-integration test reveals a long-run relationship, with CDS premiums exerting a positive influence on bond yields. The Vector Error Correction Model (VECM) supports this by confirming a significant long-term impact although the short-term effects remain relatively limited. Additionally, the Granger causality test indicates a strong bidirectional causality between the variables. For the G7 countries, panel data analysis was conducted using only the Kao and Pedroni co-integration tests to identify long-run relationships. The results point to relatively weak long term co-integration among the G7 countries. Overall, the findings demonstrate that CDS premiums significantly affect bond yields in Turkey, emphasising the importance of incorporating sovereign risk indicators into economic policy formulation. These results offer valuable insights for improving the understanding and management of the factors influencing Turkey’s borrowing costs.

JEL Classification : F30 , G1 , G2

Keywords

Credit Default Swap (CDS) , Bond Yield , Johansen Co-integration Test , G7 Countries , Granger Causality Test

Türkiye’nin Borçlanmasında Derecelendirme Notu ve Kredi Temerrüt Takasının (CDS) Etkisi: G7 Ülkeleriyle Karşılaştırmalı Analiz

Abstract

Bu çalışma, kredi temerrüt takası (CDS) primlerinin devlet tahvili faiz oranları üzerindeki etkisini Türkiye ve G7 ülkeleri özelinde analiz etmektedir. CDS, borç verenlerin borç geri ödeme riskine karşı korundukları bir finansal araçtır ve devlet tahvili faiz oranları ise bir ülkenin çıkardığı tahvillerin yatırımcılara sunduğu yıllık getiriyi ifade etmektedir. CDS primlerindeki değişiklikler, yatırımcıların bir ülkenin borç ödeme kapasitesine dair güvenini yansıtırken tahvil faiz oranları bu riskin doğrudan bir göstergesidir. Bu nedenle, her iki kavram arasındaki ilişki, bir ülkenin ekonomik durumu ve risk algısının yatırımcı davranışlarına etkisini anlamada kritik öneme sahiptir. Çalışma, Türkiye için zaman serisi analizi yaparak CDS primleri ile tahvil faiz oranları arasındaki uzun dönemli denge ilişkilerini ve kısa dönem dinamik etkileri incelemiştir. Johansen eşbütünleşme testi, CDS primi ile tahvil faiz oranları arasında uzun dönemde bir denge ilişkisi bulunduğunu ve CDS priminin tahvil faiz oranları üzerinde pozitif bir etkisi olduğunu göstermektedir. Vektör Hata Düzeltme Modeli (VECM) ise, CDS priminin tahvil faiz oranlarını uzun dönemde pozitif etkilediğini ancak kısa dönemde etkisinin daha sınırlı olduğunu ortaya koymuştur. Granger nedensellik testi, iki değişken arasında güçlü bir çift yönlü nedenselliği doğrulamaktadır. G7 ülkeleri için gerçekleştirilen panel veri analizinde, CDS primleri ile tahvil faiz oranları arasındaki uzun dönemli ilişkilerin tespiti amacıyla Kao ve Pedroni eşbütünleşme testleri uygulanmıştır. Çalışmanın sonuçları, CDS primlerinin özellikle Türkiye için tahvil faiz oranları üzerinde belirgin bir etkisi olduğunu ve bu ilişkinin ekonomik politika tasarımında dikkate alınması gerektiğini vurgulamaktadır. Bu bulgular, Türkiye’nin borçlanma maliyetlerini etkileyen risk unsurlarının daha iyi anlaşılmasını ve yönetilmesini sağlayacak önemli bilgiler sunmaktadır.

JEL Classification : F30 , G1 , G2

Keywords

Kredi Temerrüt Takası (CDS) , Tahvil Faizi Oranı , Johansen Eşbütünleşme Testi , Granger Nedensellik Testi , G7 ülkeleri

References

• Acharya, V. V., & Johnson, T. C. (2007). Insider trading in credit derivatives. Journal of Financial Economics, 84(1), 110-141. https://doi.org/ 10.1016/j.jfineco.2006.05.003. google scholar
• Amstad, M., & Packer, F. (2015). Sovereign ratings of advanced and emerging economies after the crisis. Journal of International Money and Finance, 58, 233-255. https://doi.org/10.1016/j.jimonfin.2015.08.005. google scholar
• Cantor, R., & Packer, F. (1996). Determinants and impact of sovereign credit ratings. Economic Policy Review, 2(2), 37-53. google scholar
• Enders, W. (2014). Applied Econometric Time Series. Wiley. google scholar
• Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276. google scholar
• Fabozzi, F. J. (2013). Bond markets, analysis, and strategies. Pearson Education. google scholar
• Fitch Ratings. (2020). Sovereign ratings: Methodology and assumptions. https://www.fitchratings.com . google scholar
• Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross- spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791 google scholar
• Gujarati, D. N., & Porter, D. C. (2009). Basic Econometrics (5th ed.). McGraw-Hill Education. google scholar
• Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating Vector Autoregressions with google scholar
• Hull, J. C. (2015). Risk management and financial institutions (4th ed.). John Wiley & Sons. google scholar
• Hull, J., Predescu, M., & White, A. (2004). The relationship between credit default swap spreads and bond yields. Journal of Banking & Finance, 28(11), 2789–2803. google scholar
• Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. https://doi. org/10.1016/0165- 1889(88)90041-3. google scholar
• Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210. https://doi.org/10.1111/j.1468- 0084.1990.mp52002003. google scholar
• Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90(1), 1-44. https:// doi.org/10.1016/S0304-4076(98)00023-2. google scholar
• Longstaff, F. A., Mithal, S., & Neis, E. (2005). Corporate yield spreads: Default risk or liquidity? New evidence from the credit default swap market. The Journal of Finance, 60(5), 2213-2253. https://doi.org/10.1111/j.1540-6261.2005.00797. google scholar
• Love, I., & Zicchino, L. (2006). Financial Development and Dynamic Investment Behavior: Evidence from Panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190–210. https://doi.org/10.1016/j.qref.2005.11.007 google scholar
• Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer Science & Business Media. google scholar
• Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of Finance, 29(2), 449-470. https:// doi.org/10.1111/j.1540-6261.1974.tb03058. google scholar
• Norden, L., & Weber, M. (2004). Informational efficiency of credit default swap and stock markets: The impact of credit rating announce- ments. Journal of Banking & Finance, 28(11), 2813-2843. https://doi.org/10.1016/j.jbankfin.2004.06.011. google scholar
• Panel Data. Econometrica, 56(6), 1371–1395. https://doi.org/10.2307/1913103 google scholar
• Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653-670. https://doi.org/10.1111/1468-0084.0610s1653. google scholar
• Pedroni, P. (2004). Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the google scholar
• PPP hypothesis. Econometric Theory, 20(3), 597-625. https://doi.org/10.1017/S0266466604203073. google scholar
• Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. CESifo Working Paper Series No. 1233, 1-38. google scholar
• Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22(2), 265-312. google scholar
• Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. google scholar
• Reinhart, C. M., & Rogoff, K. S. (2009). This time is different: Eight centuries of financial folly. Princeton University Press. google scholar
• S&P Global Ratings. (2021). Sovereign rating methodology. Retrieved from https://www.spglobal.com. google scholar
• Stulz, R. M. (2010). Credit default swaps and the credit crisis. The Journal of Economic Perspectives, 24(1), 73-92. https://doi.org/10.1257/ jep.24.1.73. google scholar
• Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. MIT Press. google scholar