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Semiparametric Estimation of a Corporate Bond Rating Model

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  • Yixiao Jiang

    (Department of Economics, Christopher Newport University, Newport News, VA 23606, USA)

Abstract

This paper investigates the incentive of credit rating agencies (CRAs) to bias ratings using a semiparametric, ordered-response model. The proposed model explicitly takes conflicts of interest into account and allows the ratings to depend flexibly on risk attributes through a semiparametric index structure. Asymptotic normality for the estimator is derived after using several bias correction techniques. Using Moody’s rating data from 2001 to 2016, I found that firms related to Moody’s shareholders were more likely to receive better ratings. Such favorable treatments were more pronounced in investment grade bonds compared with high yield bonds, with the 2007–2009 financial crisis being an exception. Parametric models, such as the ordered-probit, failed to identify this heterogeneity of the rating bias across different bond categories.

Suggested Citation

  • Yixiao Jiang, 2021. "Semiparametric Estimation of a Corporate Bond Rating Model," Econometrics, MDPI, vol. 9(2), pages 1-20, May.
  • Handle: RePEc:gam:jecnmx:v:9:y:2021:i:2:p:23-:d:564043
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    References listed on IDEAS

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    Cited by:

    1. Michael Jacobs, 2021. "Validation of Corporate Probability of Default Models Considering Alternative Use Cases," IJFS, MDPI, vol. 9(4), pages 1-22, November.

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