Finally, hypothesis 4 theorized that country-specific macroeconomic factors would be more competent and sufficient in explaining CDS spread levels relative to global financial market variables, which is supported by the tremendous disparity in their R-squared values, which sides with the macroeconomic factors.
Moreover, there were several limitations noticed within the study that could have produced more effective results. Firstly, the empirical methodology of panel data analysis, although is a fitting model, if combined with a reduced form framework with latent factors, which provides better economic intuition on credit risk determination, as selection of observable covariates in a panel data regression is not straight-forward, the overall estimation results would have potentially yielded more robust and reliable figures.78 Additionally, as mentioned section five (data), although modified-modified restructuring (MMR) clause in 5-year CDS maturities is the most popular in European financial markets compared to the other two forms, the MMR data was missing for five out of the seven countries, hence, the next best option was utilized: full-restructuring. If the MMR CDS data was used, the results would be more accurate and provide better practical implications.
Furthermore, to better capture the effect of financial crises, data could have been retrieved starting 2007 instead of 2009, however, that would have resulted in complications with collecting CDS data due to the differences between the Thomson Reuters data versus CMA on Eikon. Furthermore, a crucial restraint that was encountered in our empirical methodology and data, is the radical and excessive nature of Greece’s CDS spreads. Initially, Greece was incorporated in our Southern region group, however, due to being an outlier that disrupted the Southern European regressions by misrepresenting the region effectively, it had to be removed in order to emphasize our aim for reliable, representative, and accurate results. Finally, all global variables were downloaded on a daily frequency, and all macroeconomic factors were downloaded on a quarterly basis, except for terms of trade and government debt, which could only be found in annual data. Thus, our panel regression observations were not as wide as anticipated, due to these two factors, however, due to the majority of variables that were abundant in larger frequencies, it is believed this limitation was not too problematic.
The empirical findings of this research are extensive, as it fills a knowledge gap regarding literature on drivers of sovereign CDS spreads, and they amplify our respective findings that suggest country-specific macroeconomic variables are vastly more pivotal in deciphering CDS spread levels, Southern European countries who represent the less economically developed nations are more responsive to both global and country-specific shocks and fluctuations, and that during times of financial turmoil do logically entail effects on CDS spreads, but the magnitude of which
78Doshi et al. “Economic and Financial Determinants of Credit Risk Premiums in the Sovereign CDS market”, 43-51
is debatable. These findings incorporate various important global implications when comparing the sovereign CDS spreads of wealthy economies versus less developed ones, however, future research is recommended to take into account a larger sample of countries using a longer time span, in order to statistically ensure the applicability and accuracy of the results to real world implications.
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