Lecture 1‐2, July 21, 2008Outline 0. Introduction to Course 1. Time Series Basics 2. Spectral representation of stationary process 3. Spectral Properties of Filters (a) Band Pass Filters (b) One-Sided Filters 4. Multivariate spectra 5. Spectral Estimation (a few words – more in Lecture 9)
Lecture 1‐3, July 21, 2008Introduction to Course Some themes that have occupied time-series econometricians and empirical macroeconomists in the last decade or so: 1. Low-frequency variability: (i) unit roots, near unit roots, cointegration, fractional models, and so forth; (ii) time varying parameters; (iii) stochastic volatility; (iv) HAC covariance matrices; (v) long-run identification in SVAR 2. Identification: methods for dealing with “weak” identification in linear models (linear IV, SVAR) and nonlinear models (GMM). 3. Forecasting: (i) inference procedures for relative forecast performance of existing models; (ii) potential improvements in forecasts from using many predictors
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