This paper provides a historical chronology of economic activity in 16th- and 17th-century France that is based on wheat price series in Paris and Toulouse. A stochastic regime-switching model enables us to benchmark eras and summarize the salient features of a development difficult to appraise in all its complexity. A new class of Markov regime-switching time-series models is introduced to allow for nontrivial interdependencies between different types of cycles that make the economy grow at an unsteady rate. With a predominantly agricultural cycle, we uncover a strongly periodic Markov switching scheme for recorded wheat prices from the grain markets of Paris and Toulouse. Besides the periodic nature of the Markov chain, we also study whether a common factor determined the state of the economy in Paris and Toulouse or whether each series moved independently.

We present a class of stochastic regime-switching models. The time-series models may have periodic transition probabilities and the drifts may be seasonal. In the latter case, the model exhibits seasonal dummy variation that may change with the regime. The processes entail nontrivial interactions between so-called business and seasonal cycles. We discuss the stochastic properties as well as their relationship with periodic ARMA processes. Estimation and testing are also discussed in detail.