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dc.contributor.authorSchrimpf, Paulen_US
dc.contributor.authorMikusheva, Annaen_US
dc.coverage.temporalFall 2008en_US
dc.date.issued2008-12
dc.identifier14.384-Fall2008
dc.identifierlocal: 14.384
dc.identifierlocal: IMSCP-MD5-18f2198e746c930aadd450bd4ad18668
dc.identifier.urihttp://hdl.handle.net/1721.1/90861
dc.description.abstractThe course provides a survey of the theory and application of time series methods in econometrics. Topics covered will include univariate stationary and non-stationary models, vector autoregressions, frequency domain methods, models for estimation and inference in persistent time series, and structural breaks. We will cover different methods of estimation and inferences of modern dynamic stochastic general equilibrium models (DSGE): simulated method of moments, maximum likelihood and Bayesian approach. The empirical applications in the course will be drawn primarily from macroeconomics.en_US
dc.languageen-USen_US
dc.relationen_US
dc.rights.uriUsage Restrictions: This site (c) Massachusetts Institute of Technology 2014. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions.en_US
dc.rights.uriUsage Restrictions: Attribution-NonCommercial-ShareAlike 3.0 Unporteden_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.subjectunivariate stationaryen_US
dc.subjectunivariate non-stationaryen_US
dc.subjectvector autoregressionsen_US
dc.subjectfrequency domain analysisen_US
dc.subjectpersistent time seriesen_US
dc.subjectstructural breaksen_US
dc.subjectdynamic stochastic general equilibriumen_US
dc.subjectDSGEen_US
dc.subjectBayesianen_US
dc.subjecteconometricsen_US
dc.subjectVARen_US
dc.subjectunit rooten_US
dc.subjectprediction regressionen_US
dc.subjectGMMen_US
dc.subjectMCMCen_US
dc.title14.384 Time Series Analysis, Fall 2008en_US
dc.title.alternativeTime Series Analysisen_US


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