Journals / Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2022 / Cilt: 40 Sayı: 4

DETERMINANTS OF SOVEREIGN CREDIT DEFAULT SWAP (CDS) SPREADS IN EMERGING COUNTRIES: EVIDENCE FROM TURKEY

Gelişmekte Olan Ülkelerde Kredi Temerrüt Takası (CDS) Primlerinin Belirleyicileri: Türkiye'den Kanıtlar

Hasan Murat Ertuğrul(Hazine ve Maliye Bakanlığı)0000-0001-9822-4683
Fatih Ayhan(BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ İİBF İKTİSAT BÖLÜMÜ)0000-0002-7447-5506
Pages
742–761
Publication Date
2022-12-27
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AI Summary & Key Takeaways

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

The results show that (i) market component has a greater effect than other components for all models, which indicates that it is the most important variable for Turkey’s CDS spreads; (ii) global and market components are positive and statistically significant for the ARDL, FMOLS, and DOLS models; (iii) macro component is negative for all models.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Turkey faces increasing CDS (Credit Default Swap) spreads.
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Key Findings & Data:In this context, countries need to identify the influential factors in order to decrease CDS spreads.
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Conclusion & Impact:The results show that (i) market component has a greater effect than other components for all models, which indicates that it is the most important variable for Turkey’s CDS spreads; (ii) global and market components are positive and statistically significant for the ARDL, FMOLS, and DOLS models; (iii) macro component is negative for all models.
🔬Design:Modeling & Simulation
📍Scope:2004 Verileri
⚙️Variables:KREDİ TEMERRÜT SWAPLARI · TEMEL BİLEŞEN ANALİZİ · ARDL

Abstract

Turkey faces increasing CDS (Credit Default Swap) spreads. The level of CDS spreads shows the riskiness of a country in terms of credit default and countries can’t attract high foreign investment inflows when CDS spreads are high. In this context, countries need to identify the influential factors in order to decrease CDS spreads. In this study, ten independent variables classified in global, macro, and market factors are analyzed using monthly data between January 2004 and December 2019 with autoregressive distributed lag (ARDL), fully modified least square (FMOLS), dynamic ordinary least square (DOLS), and Markov Switching Regression (MSR) after applying principal component analysis (PCA). The results show that (i) market component has a greater effect than other components for all models, which indicates that it is the most important variable for Turkey’s CDS spreads; (ii) global and market components are positive and statistically significant for the ARDL, FMOLS, and DOLS models; (iii) macro component is negative for all models.

Özet

Türkiye son zamanlarda artan kredi temerrüt takası ile karşı karşıyadır. CDS düzeyi, bir ülkenin kredi temerrüdü açısından riskli olduğunu göstermektedir. Yüksek CDS’e sahip ülkeler için yüksek yabancı yatırım girişi beklenmemektedir. Ayrıca yabancı yatırım girişinin az olması makroekonomik ortamdaki belirsizlikleri artırabilmektedir. Bu bağlamda ekonomilerin CDS spreadlerini düşürmede etkili olan faktörleri belirlemeye ihtiyaç duyarlar. Çalışmada; küresel, makro ve piyasa kategorilerinde sınıflandırılan on bağımsız değişken, 2004:1 ile 2019:12 dönemine ait aylık veriler kullanılarak temel bileşen analizi, dinamik Markov Switching, ARDL, FMOLS ve DOLS modelleri uygulanarak analiz edilmiştir. Model sonucunde elde edilen bulgulara göre; (i) tüm modeller için piyasa bileşeninin diğer bileşenlere göre daha büyük bir etkiye sahip olduğunu ve Türkiye'nin CDS yayılımı için en önemli değişken olduğunu göstermektedir; (ii) küresel ve piyasa bileşenleri, tüm statik modeller için pozitif ve istatistiksel olarak anlamlıdır; (iii) makro bileşen ise tüm modeller için negatiftir.

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Cite This Article

Kartal, M. T., Ertuğrul, H. M., Ayhan, F. (2022). DETERMINANTS OF SOVEREIGN CREDIT DEFAULT SWAP (CDS) SPREADS IN EMERGING COUNTRIES: EVIDENCE FROM TURKEY. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 40 Sayı: 4, 742–761. https://doi.org/10.17065/huniibf.1054042

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