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

40 Pages Posted: 10 Jul 2019

See all articles by Ursula Slapnik

Ursula Slapnik

University of Ljubljana, Faculty of Economics, Students

Igor Loncarski

University of Ljubljana - Faculty of Economics

Date Written: April 9, 2019

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

Suggested Citation

Slapnik, Ursula and Lončarski, Igor, Understanding Sovereign Credit Ratings: Text-Based Evidence From the Credit Rating Reports (April 9, 2019). Available at SSRN: https://ssrn.com/abstract=3372270 or http://dx.doi.org/10.2139/ssrn.3372270

Ursula Slapnik

University of Ljubljana, Faculty of Economics, Students ( email )

Kardeljeva ploscad 17
Ljubljana, 1000
Slovenia

Igor Lončarski (Contact Author)

University of Ljubljana - Faculty of Economics ( email )

Kardeljeva ploscad 17
Ljubljana, SI-1000
Slovenia
+386 5892 628 (Phone)
+386 5892 698 (Fax)

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