Time-Series Analysis, Inertial Forecasting & Cointegration Modeling

Catalog description

This course covers time-series methods. We will begin with serial correlation as a violation of the assumption of the Classical Model. We study Time-Series Analysis, including univariate methods, topics will include white noise, random walks, stationarity, seasonality, and ARIMA modeling. Next we study deterministic trends, stochastic trends, and a discussion of business cycles in the context of time-series econometrics. Next we will test for trends and unit roots and study Intervention models. The later part of the course will cover Vector-autoregressions (VAR), and Cointegration techniques (SE-ECM and FM-OLS). Students complete their homework assignments using computer programming. The class will include Mini-Project assignments, where the student will write a professional-style report.