Clustering Regional Business Cycles

The aim of this paper is to show the usefulness of Finite Mixture Markov Models (FMMMs) for regional analysis. FMMMs 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 sound performance of the proposed method

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Year of publication:	2017
Authors:	Gadea Rivas, Maria Dolores
Other Persons:	Gómez-Loscos, Ana (contributor) ; Bandrés, Eduardo (contributor)
Publisher:	[2017]: [S.l.] : SSRN
Subject:	Regionale Konjunktur \| Regional business cycle \| Regionales Cluster \| Regional cluster \| Konjunktur \| Business cycle \| Räumliche Verteilung \| Spatial distribution \| Clusteranalyse \| Cluster analysis

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Extent:	1 Online-Ressource (23 p)
Series:	Banco de Espana Working Paper ; No. 1744
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 13, 2017 erstellt
Other identifiers:	10.2139/ssrn.3087272 [DOI]
Classification:	C22 - Time-Series Models ; C32 - Time-Series Models ; E32 - Business Fluctuations; Cycles ; R11 - Regional Economic Activity: Growth, Development, and Changes
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012941437