This paper compares the importance of different sovereign credit rating determinants over time, using a sample of 90 countries for the years 2002–2015. Applying the composite marginal likelihood approach, we estimate a multi-year ordered probit model for each of the three major credit rating agencies. After the start of the European debt crisis in 2009, the importance of the financial balance, the economic development and the external debt increased substantially and the effect of eurozone membership switched from positive to negative. In addition, GDP growth gained a lot of importance for highly indebted sovereigns and government debt became much more important for countries with a low GDP growth rate. These findings provide empirical evidence that the credit rating agencies changed their sovereign credit rating assessment after the start of the European debt crisis.

This paper proposes a measure of dynamic comovement between (possibly many) time series and names it cohesion. The measure is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations. In the bivariate case, the measure reduces to dynamic correlation and is related, but not equal, to the well known quantities of coherence and coherency. Dynamic correlation on a frequency band equals (static) correlation of bandpass-filtered series. Moreover, long-run correlation and cohesion relate in a simple way to co-integration. Cohesion is useful to study problems of business-cycle synchronization, to investigate short-run and long-run dynamic properties of multiple time series, and to identify dynamic clusters. We use state income data for the United States and GDP data for European nations to provide an empirical illustration that is focused on the geographical aspects of business-cycle fluctuations.