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Understanding sovereign credit ratings: Text-based evidence from the credit rating reports

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  • Slapnik, Ursula
  • Lončarski, Igor

Abstract

We apply a novel approach to identifying the qualitative judgment of the rating committee in sovereign credit ratings by extending the traditional regression with new measures – sentiment and subjectivity scores – obtained by textual sentiment analysis methods. Using an ordered logit with random effects for 98 countries from 1995 to 2018, 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 and subjectivity between emerging markets and advanced economies, as well as before and after the 2008 global financial crisis.

Suggested Citation

  • Slapnik, Ursula & Lončarski, Igor, 2023. "Understanding sovereign credit ratings: Text-based evidence from the credit rating reports," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
  • Handle: RePEc:eee:intfin:v:88:y:2023:i:c:s1042443123001063
    DOI: 10.1016/j.intfin.2023.101838
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