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dc.contributor.authorPicavet, Emmanuel
dc.contributor.authorJacques, Jean-François
dc.date.accessioned2009-09-23T11:35:37Z
dc.date.available2009-09-23T11:35:37Z
dc.date.issued2003
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/1901
dc.language.isofren
dc.subjectEpistemologyen
dc.subjectCausalityen
dc.subjectMacroeconometricsen
dc.subjectMeasurementsen
dc.subjectModelizationen
dc.subject.ddc339en
dc.subject.classificationjelE01en
dc.titleMesure des associations phénoménales et causalité en macro-économétrieen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherUniversité de Franche-Comté;France
dc.description.abstractenThe article studies the conceptions of causality encountered in macroeconometrics. From an empiricist standpoint, it is natural to privilege measurements of phenomenal associations, spread over a period of time, between series of data. This method has made a major comeback since the 1970s, whereas these years seem to be moving away from the established approach to research in causality in this area. The authors seek to establish in particular the type of causality underpinning the approaches put forward by Clive Granger and Christopher Sims. They show that this definition of causality has distinctive advantages for the study of phenomena in which forecasting, different sets of information, interaction between the behaviour of developers of modelization tools and that of the other agents play a determining role.en
dc.relation.isversionofjnlnameSocial science information
dc.relation.isversionofjnlvol42en
dc.relation.isversionofjnlissue4en
dc.relation.isversionofjnldate2003
dc.relation.isversionofjnlpages591-624en
dc.relation.isversionofdoihttp://dx.doi.org/10.1177/0539018403424007en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSageen
dc.subject.ddclabelMacroéconomieen


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