Bristol MSc Time Series 2015

MSc Time Series Econometrics, Spring 2015

Here is a short course I taught in my last year at Bristol.  The objective is to get students to the point where they understand some of the basic tools in modern empirical macro, building from univariate time series topics, to multivariate vector autoregressions and factor models.

Overview/motivation

Slides:  PPT

Slides:  pdf

Part 1:  Univariate time series processes, Maximum Likelihood estimation, Kalman Filter, stationarity

Lecture 1:  Univariate time series processes:  preliminaries

Slides:  PPT

Slides:  Pdf

Assignment

Solutions

Lecture notes

Lecture 2:  Estimation and inference with an AR(1) via Maximum Likelihood

Slides:  PPT

Slides:  pdf

Lecture notes

Assignment

Solutions

Lecture 3:  The Kalman Filter

Slides:  PPT

Slides:  pdf

Lecture notes

Assignment

Solutions

Part 2:  estimating and identifying VARs, factor analysis, TVP-VARs, Bayesian time series econometrics

Note:  lecture notes for ALL of part 2 posted at the end of this section.

Lecture 1:  Introduction, motivation, technical preliminaries

Slides:   pdf

Slides:  PPT

Assignments

Solutions

Lecture 2:  Structural identification of Vector Autoregressions

Slides:  pdf

Slides:  PPT

Assignment

Solutions

Lecture 3:  Time-varying parameter VARs

Slides:  pdf

Slides:  PPT

Assignment

Lecture 4:  Intro to Bayesian time series econometrics

Slides: pdf

Slides: PPT

Assignment

Solutions

Lecture 5:  Factor models and VARs

Slides:  pdf

Slides: PPT

Lecture notes

Assignment

Solutions

Revision lecture slides

Slides:  pdf

Slides:PPT

Miscellaneous further resources

More practice questions on part 2

Lecture notes for part 2 of the course

 

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