Time Series ECONOMETRICS
The course provides an accessible introduction to the application of time series methods. Topics covered may include an introduction to the dynamic properties of time series, structural breaks, univariate autoregressive moving average models, forecast generation and evaluation, state-space models, unit root tests, univariate volatility models, regime-switching models, autoregressive distributed lag models, vector autoregression models, structural vector autoregression models, cointegration and error-correction models, and dynamic factor models.
This particular page is work in progress so many of the links may not work.
Course outline [link]
1) Introduction [slides] [tutorial] [R files]
2) Structural breaks [slides] [tutorial] [R files]
3) Univariate autoregressive moving average models [slides] [tutorial] [R files]
4) Forecasting and out-of-sample evaluations [slides] [tutorial] [R files]
5) Univariate state-space models [slides] [tutorial] [R files]
6) Decompositions and spectral analysis [slides] [tutorial] [R files]
7) Nonstationarity and unit root tests [slides] [tutorial] [R files]
8) Univariate volatility models [slides] [tutorial] [R files]
9) Nonlinear regime-switching models [slides] [tutorial] [R files]
10) Autoregressive distributed lag models [slides] [tutorial] [R files]
11) Vector autoregression models [slides] [tutorial] [R files]
12) Structural vector autoregression models [slides] [tutorial] [R files]
13) Cointegration and error correction models [slides] [tutorial] [R files]
14) Dynamic factor models [slides] [tutorial] [R files]