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.
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