ECON 615 - Time Series Econometrics and Forecasting

Units: 4
Empirical tools and models in applied time series analysis, including trends, seasonality, auto-regressive and moving-average models, with an emphasis on applications to macroeconomic and financial data. Vector auto-regression (VAR) and Granger causality are also covered for identifying the transmission channels, effects, and forecasts of monetary and fiscal policies. Utilize statistical software for computation, visualization and analysis of time series data in economics and finance.

Prerequisites: ECON 610.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Distinguish cross-sectional and time series data in economics.
Be acquainted with the main concepts and theories of time series analysis.
Identify time series models that provides good fit for economic and financial data.
Apply time series forecasting tools to predict future trends in economics and finance.