Understanding Sovereign Credit Ratings: Text-Based Evidence From the Credit Rating Reports

Abstract

In this paper we apply a novel approach to identifying the qualitative judgement of the rating committee in sovereign credit ratings. We extend the traditional regression with new measures - sentiment and subjectivity scores - obtained by textual sentiment analysis methods. By using an ordered logit with random effects for 98 countries in the period from 1996 to 2017, we find evidence that the subjectivity score provides additional information not captured by previously identified determinants of sovereign credit ratings, even after controlling for political risk, institutional strength and potential bias. The results from the bivariate and multivariate analysis confirm differences in textual sentiment between emerging markets and advanced economies, as well as before and after the 2008 global financial crisis.

Keywords: sovereign credit ratings, sovereign credit rating reports, textual sentiment analysis, soft information, bias, subjectivity

JEL Classification: G00, G01, G20, G24