Random effects model for credit rating transitions

Yoonseong Kim, So Young Sohn

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


This paper proposes a random effects multinomial regression model to estimate transition probabilities of credit ratings. Unlike the previous studies on the rating transition, we applied a random effects model, which accommodates not only the environmental characteristics of the exposures of a rating but also the uncertainty not explained by such factors. The rating category specific factors such as retained earning and market equity are included in our proposed model. The random effects model provides less diagonally dominant matrix, where the transition probabilities are over-dispersed from the diagonal elements. Our study is expected to incorporate potential chances of rating transitions due to extra random variations.

Original languageEnglish
Pages (from-to)561-573
Number of pages13
JournalEuropean Journal of Operational Research
Issue number2
Publication statusPublished - 2008 Jan 16

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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