This is an archived course. A more recent version may be available at ocw.mit.edu.
Graph of time series equation. (Image courtesy of Daniel Bersak.)
Paul Schrimpf
Prof. Anna Mikusheva
14.384
Fall 2008
Graduate
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.
Schrimpf, Paul, and Anna Mikusheva. 14.384 Time Series Analysis, Fall 2008. (MIT OpenCourseWare: Massachusetts Institute of Technology), https://ocw.mit.edu/courses/economics/14-384-time-series-analysis-fall-2008 (Accessed). License: Creative Commons BY-NC-SA
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