Sovereign credit ratings are a condensed assessment of a government’s ability and willingness to repay its public debt on time, both in principal and in interests. In this, they are forward looking qualitative measures of the probability of default put forward by rating agencies. Sovereign credit ratings are particularly relevant for international financial markets, economic agents and governments. Indeed, they are important in three ways. First, sovereign ratings are a key determinant of the interest rates a country faces in the international financial market and therefore of its borrowing costs.
Second, the sovereign rating may have a constraining impact on the ratings assigned to domestic banks or companies. Third, some institutional investors have lower bounds for the risk they can assume in their investments and they will choose their bond portfolio composition taking into account the credit risk perceived via the rating notations. Therefore, it is important both for governments and for financial markets to understand what factors rating agencies put more emphasis on when attributing a rating score.
In this paper we perform an empirical analysis of foreign currency sovereign debt ratings, using rating data from the three main international rating agencies: Fitch Ratings, Moody’s, and Standard & Poor’s. We have compiled a comprehensive panel data set on sovereign debt ratings, macroeconomic data, and qualitative variables for a wide range of countries starting in 1995. In this context, the use of panel data is appealing because it allows examining not only how the agencies attribute a rating, but also how they decide on upgrades and downgrades.
Our main contributions to the existing literature are both the innovation of the econometric estimation procedure and the specification used. Indeed, the fact that a country’s rating does not have much variation across time raises some econometric problems. While fixed effects estimations are uninformative as the country dummy captures the average rating, random effects estimations will also be inadequate due to the correlation between the country specific error and the regressors.
We salvage the random effects approach by means of modelling the country specific error, which in practical terms implies adding time-averages of the explanatory variables as additional time-invariant regressors. This setting will allow us to make a distinction between short and long-run effects of a variable on the sovereign rating. This distinction can be very important for policy purposes because it can inform the governments what they can do to improve their rating in the short-run.