The distribution of ratings changes plays a crucial role in many credit risk models. As is well known, these distributions vary across time and different issuer types. Ignoring such dependencies may lead to inaccurate assessments of credit risk. In this paper, a quantification is provided of the dependence of ratings transition probabilities on the industry and domicile of the obligor, and on the stage of the business cycle. The incremental impact of these factors is identified using ordered probit models. This approach gives a clearer picture (than is obtained by comparing transition matrices estimated from different sub-samples) of which conditioning factors are important.
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