  We develop a model for credit rating migration that accounts for the impact
of economic state fluctuations on default probabilities. The joint process for
the economic state and the rating is modelled as a time-homogeneous Markov
chain. While the rating process itself possesses the Markov property only under
restrictive conditions, methods from Markov theory can be used to derive the
rating process' asymptotic behaviour. We use the mathematical framework to
formalise and analyse different rating philosophies, such as point-in-time
(PIT) and through-the-cycle (TTC) ratings. Furthermore, we introduce stochastic
orders on the bivariate process' transition matrix to establish a consistent
notion of "better" and "worse" ratings. Finally, the construction of PIT and
TTC ratings is illustrated on a Merton-type firm-value process.
