A New Approach to Dating the Reference Cycle

Camacho, Maximo; Gadea, María Dolores; Gómez Loscos, Ana

Publication:
A New Approach to Dating the Reference Cycle

dc.contributor.author	Camacho, Maximo
dc.contributor.author	Gadea, María Dolores
dc.contributor.author	Gómez Loscos, Ana
dc.contributor.department	Métodos Cuantitativos para la Economía y la Empresa
dc.date.accessioned	2024-01-30T08:05:38Z
dc.date.available	2024-01-30T08:05:38Z
dc.date.issued	2020-07-01
dc.description	© 2022. The authors. This document is the published version of a Published Work that appeared in final form in Journal of Business & Economic Statistics. To access the final edited and published work see https://doi.org/10.1080/07350015.2020.1773834	es
dc.description.abstract	This article proposes a new approach to the analysis of the reference cycle turning points, defined on thebasis of the specific turning points of a broad set of coincident economic indicators. Each individual pair ofspecific peaks and troughs from these indicators is viewed as a realization of a mixture of an unspecifiednumber of separate bivariate Gaussian distributions whose different means are the reference turningpoints. These dates break the sample into separate reference cycle phases, whose shifts are modeled by ahidden Markov chain. The transition probability matrix is constrained so that the specification is equivalentto a multiple change-point model. Bayesian estimation of finite Markov mixture modeling techniques issuggested to estimate the model. Several Monte Carlo experiments are used to show the accuracy of themodel to date reference cycles that suffer from short phases, uncertain turning points, small samples, andasymmetric cycles. In the empirical section, we show the high performance of our approach to identifyingthe US reference cycle, with little difference from the timing of the turning point dates established by theNBER. In a pseudo real-time analysis, we also show the good performance of this methodology in terms ofaccuracy and speed of detection of turning point dates.	es
dc.format	application/pdf	es
dc.format.extent	17	es
dc.identifier.citation	Journal of Business & Economic Statistics Volume 40, 2022 - Issue 1 pp.: 66–81
dc.identifier.doi	https://doi.org/10.1080/07350015.2020.1773834
dc.identifier.issn	Print: 0735-0015
dc.identifier.issn	Electronic: 1537-2707
dc.identifier.uri	http://hdl.handle.net/10201/138059
dc.language	eng	es
dc.publisher	Taylor & Francis Group	es
dc.relation	M. Camacho and M. D. Gadea are grateful for the support of grantsPID2019-107192GB-I00 (AEI/10.13039/501100011033) and 19884/GERM/15, and ECO2017-83255-C3-1-P and ECO2017-83255-C3-3-P (MICINU,AEI/ERDF, EU), respectively	es
dc.relation.publisherversion	https://www.tandfonline.com/doi/epdf/10.1080/07350015.2020.1773834?needAccess=true	es
dc.rights.accessRights	info:eu-repo/semantics/restrictedAccess
dc.subject	Business cycles	es
dc.subject	Finite mixture models	es
dc.subject	Turning points	es
dc.title	A New Approach to Dating the Reference Cycle	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es