dc.contributorEscolas::EPGE
dc.contributorFGV
dc.creatorEngle, R. F.
dc.creatorIssler, João Victor
dc.date.accessioned2008-05-13T15:26:35Z
dc.date.accessioned2022-11-03T20:18:53Z
dc.date.available2008-05-13T15:26:35Z
dc.date.available2022-11-03T20:18:53Z
dc.date.created2008-05-13T15:26:35Z
dc.date.issued1994-03
dc.identifier0104-8910
dc.identifierhttp://hdl.handle.net/10438/556
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5035913
dc.description.abstractThis paper investigates the degree of short run and long run co-movement in U.S. sectoral output data by estimating sectoraI trends and cycles. A theoretical model based on Long and Plosser (1983) is used to derive a reduced form for sectoral output from first principles. Cointegration and common features (cycles) tests are performed; sectoral output data seem to share a relatively high number of common trends and a relatively low number of common cycles. A special trend-cycle decomposition of the data set is performed and the results indicate a very similar cyclical behavior across sectors and a very different behavior for trends. Indeed. sectors cyclical components appear as one. In a variance decomposition analysis, prominent sectors such as Manufacturing and Wholesale/Retail Trade exhibit relatively important transitory shocks.
dc.languageeng
dc.publisherEscola de Pós-Graduação em Economia da FGV
dc.relationEnsaios Econômicos;232
dc.rightsTodo cuidado foi dispensado para respeitar os direitos autorais deste trabalho. Entretanto, caso esta obra aqui depositada seja protegida por direitos autorais externos a esta instituição, contamos com a compreensão do autor e solicitamos que o mesmo faça contato através do Fale Conosco para que possamos tomar as providências cabíveis
dc.titleEstimating sectoral cycles using cointegration and common features
dc.typeWorking Paper


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