| dc.contributor.author | Schrimpf, Paul | en_US |
| dc.contributor.author | Mikusheva, Anna | en_US |
| dc.coverage.temporal | Fall 2008 | en_US |
| dc.date.issued | 2008-12 | |
| dc.identifier | 14.384-Fall2008 | |
| dc.identifier | local: 14.384 | |
| dc.identifier | local: IMSCP-MD5-18f2198e746c930aadd450bd4ad18668 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/90861 | |
| dc.description.abstract | The 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.language | en-US | en_US |
| dc.relation | | en_US |
| dc.rights.uri | Usage 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.uri | Usage Restrictions: Attribution-NonCommercial-ShareAlike 3.0 Unported | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ | en_US |
| dc.subject | univariate stationary | en_US |
| dc.subject | univariate non-stationary | en_US |
| dc.subject | vector autoregressions | en_US |
| dc.subject | frequency domain analysis | en_US |
| dc.subject | persistent time series | en_US |
| dc.subject | structural breaks | en_US |
| dc.subject | dynamic stochastic general equilibrium | en_US |
| dc.subject | DSGE | en_US |
| dc.subject | Bayesian | en_US |
| dc.subject | econometrics | en_US |
| dc.subject | VAR | en_US |
| dc.subject | unit root | en_US |
| dc.subject | prediction regression | en_US |
| dc.subject | GMM | en_US |
| dc.subject | MCMC | en_US |
| dc.title | 14.384 Time Series Analysis, Fall 2008 | en_US |
| dc.title.alternative | Time Series Analysis | en_US |
| dc.type | Learning Object | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Economics | |
