Introduction to Modern Time Series Analysis

This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.

List of contents

Introduction and Basics.- Univariate Stationary Processes.- Granger Causality.- Vector Autoregressive Processes.- Nonstationary Processes.- Cointegration.- Nonstationary Panel Data.- Autoregressive Conditional Heteroscedasticity.

About the author

Gebhard Kirchgässner ist Professor für Volkswirtschaftslehre und Ökonometrie an der Universität St. Gallen.

Summary

This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
 

Product details

• Authors: Uwe Hassler, Gebhar Kirchgässner, Gebhard Kirchgässner, Jürge Wolters, Jürgen Wolters
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2014
• EAN: 9783642440298
• ISBN: 978-3-642-44029-8
• No. of pages: 320
• Dimensions: 155 mm x 18 mm x 234 mm
• Weight: 524 g
• Illustrations: XII, 320 p.
• Series: Springer Texts in Business and Economics; Springer Texts in Business and Economics
• Subjects: Natural sciences, medicine, IT, technology > Mathematics; Social sciences, law, business > Business > Economics; B, Economics, finance, business & management, Statistics, macroeconomics, Economics and Finance, Macroeconomics and Monetary Economics, Macroeconomics/Monetary Economics//Financial Economics, Game Theory, Economics, Social and Behav. Sciences, game theory, Monetary Economics, Management science, Probability & statistics, Econometrics