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dc.contributor.authorBarradas, R.-
dc.date.accessioned2013-05-23T08:46:13Z-
dc.date.available2013-05-23T08:46:13Z-
dc.date.issued2013-05-23-
dc.identifier.urihttp://hdl.handle.net/10071/4980-
dc.description.abstractThis paper empirically applies the New Keynesian Model to the euro area’s economy during the period from the first quarter of 1999 to the last quarter of 2008, which is consistent with the scant empirical evidence on this Dynamic Stochastic General Equilibrium model. Specifically, we proceed with an econometric estimation of the IS Curve, the Phillips Curve and the Taylor Rule to assess the ability of these three equations to describe the dynamics of aggregate demand and the inflation rate in the euro area, as well as monetary policy steering by the European Central Bank during its first 10 years. The New Keynesian Model is estimated using the Generalized Method of Moments, since the three equations denote hybrid features including backward and forward looking behaviours by economic agents and elements with rational expectations. Although this method of estimation may present some limitations, the New Keynesian Model seems to describe reasonably well the evolution of economic activity, the inflation rate and monetary policy in the euro area. Against this backdrop, the New Keynesian Model may provide an important tool for aiding the governments of euro area countries and the European Central Bank in the adoption and implementation of its policies over time.por
dc.description.sponsorshipFCTpor
dc.language.isoengpor
dc.relation.ispartofseriesWorking Paperspor
dc.relation.ispartofseriesDINAMIA_2013_01por
dc.rightsopenAccesspor
dc.subjectNew Keynesian Modelpor
dc.subjectIS Curvepor
dc.subjectPhillips Curvepor
dc.subjectTaylor Rulepor
dc.subjectGeneralized Method of Momentspor
dc.subjectEuro Areapor
dc.titleThe New Keynesian Model: An empirical application to the euro area economypor
dc.typeworkingPaperpor
dc.peerreviewedSimpor
degois.publication.issueDINAMIA_WP_2013-01por
degois.publication.locationLisboapor
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