Understanding sovereign credit ratings: Text-based evidence from the credit rating reports
通过文本情感分析方法提取评级报告中的情感和主观性得分，发现主观性得分能提供传统因素之外的信息，并揭示了新兴市场与发达经济体以及金融危机前后的差异。
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.