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

Yıl 2022, Cilt: 40 Sayı: 4, 742 - 761, 27.12.2022

Mustafa Tevfik Kartal Hasan Murat Ertuğrul Fatih Ayhan

https://doi.org/10.17065/huniibf.1054042

Cited By: 2

Öz

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.

Anahtar Kelimeler

Principal Compenent Analysis, ARDL, CDS, Dynamic Markov Swithching Regression, FMOLS and DOLS Models, Turkey

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

Öz

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.

Anahtar Kelimeler

KREDİ TEMERRÜT SWAPLARI;, TEMEL BİLEŞEN ANALİZİ;, ARDL;, Dinamik Markov Switching Regresyonu, FMOLS ve DOLS Modelleri, Türkiye

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