Description
Aims: The goal of this module 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 module is primarily applied, there will also be some emphasis on the theoretical foundations of the techniques analyzed.
Topics
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 deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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