This assignment introduces students to basic tests for stationarity and normality and then has them fit several ARIMA models to a single time series, forecasting the model using the last few data points.
If you use these materials, please include the following citation.
JanetBox-Steffensmeier, , 2012, "Time Series Modeling in Politics, Syllabus Spring 2012", http://opossem.org/content/time-series-modeling-politics-syllabus-spring-2012
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CC BY-NC-SA 3.0
Syllabus for advanced graduate level seminar in Time Series methodology. Topics include ARIMA modeling, vector autoregression, error correction models, bayesian approaches, fractional integration and cointegration, and forecasting.