Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The aim of this paper is to show the usefulness of Finite Mixture Markov models (FMMM) for regional analysis. FMMM combine clustering techniques and Markov Switching models, providing a powerful methodological framework to jointly obtain business cycle datings and clusters of regions that share similar business cycle characteristics. An illustration with European regional data shows the good performance of the proposed method.