Recitations

The following recitation notes are supplements to the lecture notes. Notes are courtesy of Paul Schrimpf, the course TA, and are used with permission.

REC # TOPICS
1 Stationarity, autoregression moving average (ARMA), invertibility, covariances (PDF)
2

Heteroscedasticity autocorrelation-consistent (HAC) (PDF)

Time series in MATLAB (PDF)
3 Filtering (PDF)
4 Spectrum estimation, vector autoregression maximum likelihood (VAR ML) (PDF)
5 Variance decomposition (PDF)
6 Fundamentalness, testable factor-augmented vector autoregressive (FAVAR) restrictions, applications of factor models (PDF)
7 Empirical process theory, random walk asymptotics (PDF)
8 More empirical process theory, local to unity asymptotics, testing for breaks (PDF)
9 Consumption, income, wealth and cointegration (PDF)
10 Generalized method of moments (GMM) estimation of the New Keynesian Phillips Curve (NKPC) (PDF)
11 Kalman filtering (PDF)
12 Review of the asymptotics of extremum estimators, minimum distance, review of asymptotic normality, variance matrix estimation, hypothesis testing, asymptotics of simulated estimators (PDF)