ECONG004 - Time Series Economics


The goal of this course is to provide students with an understanding and working knowledge of statistical techniques for the empirical analysis and forecasting of time series in macroeconomics and, to a lesser extent, finance. Although the focus of the course is primarily applied, there will also be some emphasis on the theoretical foundations of the techniques analyzed

Course outline:

1. Univariate Time Series
Topics include: Tests for structural breaks; Nonlinear models of the conditional mean; Models of the conditional variance: ARCH/GARCH 

2. Multivariate Time Series
Topics include: VAR; Structural VAR; Impulse-response analysis; Granger causality; Cointegration 

3. Elements of forecasting

Topics include: Forecasting with regression models; Model selection and information criteria; Forecast evaluation and Combination; Forecasting with many predictors: data-reduction methods


Module video presented by Raffaella Giacomini

Taught by:
Raffaella Giacomini
Assessment: 2 hours of lectures per week and weekly tutorial/practical classes with written assignments. The course will be examined by a 2-hour written exam in Term 3.
Suitable for:
Graduate students
Prerequisites: Permission from the Economics Department
Moodle page: ECONG004