Time-Series Econometrics Laboratory

Problem-solving and project-based analysis requiring students to apply time-series analysis from course 149 to real-world time-series data. Applications involve 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.