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Clustering regional business cycles

María Gadea (), Ana Gómez-Loscos () and Eduardo Bandrés

Economics Letters, 2018, vol. 162, issue C, 171-176

Abstract: 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.

Keywords: Business cycles; Clusters; Regions; Finite Mixture Markov models (search for similar items in EconPapers)
JEL-codes: C22 C32 E32 R11 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:162:y:2018:i:c:p:171-176

DOI: 10.1016/j.econlet.2017.10.029

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