Lecture Notes | Time Series Analysis | Economics | MIT OpenCourseWare

Course Info

Instructor

Prof. Anna Mikusheva

Departments

Economics

As Taught In

Fall 2013

Level

Graduate

Topics

Learning Resource Types

Lecture Notes

Problem Sets

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Lecture Notes

Lecture Notes 1: Stationarity, Lag Operator, ARMA, and Covariance Structure

Lecture Notes 2: Limit Theorems, OLS, and HAC

Lecture Notes 3: More HAC and Intro to Spectrum

Lecture Notes 4: Spectrum

Lecture Notes 5: Spectrum Estimation and Information Criteria

Lecture Notes 6: GMM

Lecture Notes 7-8: Weak IV

Lecture Notes 9: Bootstrap

Lecture Notes 10: Introduction to VARs

Lecture Notes 11: VARs

Lecture Notes 12-13: Structural VARs

Lecture Notes 14: Factor Models

Lecture Notes 15: Factor Models Part 2

Lecture Notes 16: Empirical Processes

Lecture Notes 17: Unit Roots

Lecture Notes 18: More Non-Stationarity

Lecture Notes 19: Breaks and Cointegration

Lecture Notes 20: Cointegration

Lecture Notes 21: Filtering, State space models, Kalman filter

Lecture Notes 22: State-space models, ML estimation, DSGE models

Lecture Notes 23-24: Intro to Bayes approach, Reasons to be Bayesian

Lecture Notes 25: MCMC: Metropolis Hastings Algorithm

Lecture Notes 26: MCMC: Gibbs Sampling

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