Introduction to Modern Time Series Analysis
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Gebhard Kirchgässner · Jürgen Wolters
Introduction to Modern Time Series Analysis With 43 Figures and 17 Tables
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Professor Dr. Gebhard Kirchgässner University of St. Gallen SIAW-HSG Bodanstrasse 8 CH-9000 St. Gallen Switzerland [email protected] Professor Dr. Jürgen Wolters Freie Universität Berlin Institute for Statistics and Econometrics Boltzmannstraße 20 14195 Berlin Germany [email protected]
Library of Congress Control Number: 2007932230
ISBN 978-3-540-73290-7 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com © Springer-Verlag Berlin Heidelberg 2007 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Production: LE-TEX Jelonek, Schmidt & Vöckler GbR, Leipzig Cover-design: WMX Design GmbH, Heidelberg SPIN 12071654
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Preface
Econometrics has been developing rapidly over the past four decades. This is not only true for microeconometrics which more or less originated during this period, but also for time series econometrics where the cointegration revolution influenced applied work in a substantial manner. Economists have been using time series for a very long time. Since the 1930s when econometrics became an own subject, researchers have mainly worked with time series. However, economists as well as econometricians did not really care about the statistical properties of time series. This attitude started to change in 1970 with the publication of the textbook Time Series Analysis, Forecasting and Control by GEORGE E.P. BOX and GWILYM M. JENKINS. The main impact, however, stems from the work of CLIVE W.J. GRANGER starting in the 1960s. In 2003 together with ROBERT W. ENGLE, he received the Nobel Prize in Economics for his work. This textbook provides an introduction to these recently developed methods in time series econometrics. Thus, it is assumed that the reader is familiar with a basic knowledge of calculus and matrix algebra as well as of econometrics and statistics at the level of introductory textbooks. The book aims at advanced Bachelor and especially Master students in economics and applied econometrics but also at the general audience of economists using empirical methods to analyse
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