Time-Series Econometrics

Time-series econometrics studies dynamic behaviors of economic variables using tools from probability theory and statistics. It plays important role in data analysis in macroeconomics and finance. Introduction to methods of time-series analysis in econometrics. Topics include weak dependence, autoregressive-moving-average (ARMA) processes, linear processes, economic forecasting, long-run variance and heteroskedasticity and autocorrelation consistent (HAC) estimation, unit root theory, estimation and inference of time-varying volatility models. Provides useful preparation to students who plan to take empirically oriented macroeconomics and finance courses, and solid understanding of tools required to analyze and model economic time series data and financial asset prices/returns. Emphasis throughout on link between statistical models and implementation.

P/NP or letter grading.