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dc.contributor.authorGil Alana, Luis A. 
dc.contributor.authorGonzález Blanch, María Jesús
dc.contributor.authorPoza Lara, Carlos 
dc.date.accessioned2024-03-15T17:28:51Z
dc.date.available2024-03-15T17:28:51Z
dc.date.issued2024
dc.identifier.issn0003-6846spa
dc.identifier.urihttps://hdl.handle.net/10641/4241
dc.description.abstractThis paper examines the G7 labour market, analysing unemployment, job vacancies and the spread of both in terms of time series persistence from January 2002 to October 2023. Using fractional integration, we observe the series show long memory and persistence in all G7 countries. These findings differ slightly depending on the specification of the error term. If it is white noise, no evidence of mean reversion is found in any scenario except for US unemployment. With autocorrelated disturbances, mean reversion is found in unemployment rates in Canada, Germany, and the US. In France, this is the case for job vacancies, and in France and Italy, for spread. The UK is the only country that does not display any degree of reversion to the mean in the three series examined. Our results show evidence of a downward trend for unemployment and an upward trend for job vacancies in all G7 countries. Consequently, the reduction of the imbalance unemployment-vacancies seems permanent, which is a positive outcome for advanced economies.spa
dc.language.isoengspa
dc.publisherApplied Economicsspa
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectLabour marketspa
dc.subjectUnemploymentspa
dc.subjectJob vacanciesspa
dc.subjectFractional integrationspa
dc.subjectG7 countriesspa
dc.titleLabour market mismatches in G7 countries: a fractional integration approach.spa
dc.typejournal articlespa
dc.type.hasVersionVoRspa
dc.rights.accessRightsopen accessspa
dc.description.extent5649 KBspa
dc.identifier.doi10.1080/00036846.2024.2305620spa
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/00036846.2024.2305620spa


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