New Introduction to Multiple Time Series Analysis
This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated,vector autoregressive moving average, multivari
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New Introduction to Multiple Time Series Analysis
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New Introduction to Multiple Time Series Analysis
Helmut Lütkepohl
New Introduction to Multiple Time Series Analysis With 49 Figures and 36 Tables
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Professor Dr. Helmut Lütkepohl Department of Economics European University Institute Villa San Paolo Via della Piazzola 43 50133 Firenze Italy E-mail: [email protected]
Cataloging-in-Publication Data Library of Congress Control Number: 2005927322
ISBN 3-540-40172-5 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-Verlag. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2005 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. Cover design: Erich Kirchner Production: Helmut Petri Printing: Strauss Offsetdruck SPIN 10932797
Printed on acid-free paper – 43/3153 – 5 4 3 2 1 0
To Sabine
Preface
When I worked on my Introduction to Multiple Time Series Analysis (L¨ u ¨tkepohl (1991)), a suitable textbook for this field was not available. Given the great importance these methods have gained in applied econometric work, it is perhaps not surprising in retrospect that the book was quite successful. Now, almost one and a half decades later the field has undergone substantial development and, therefore, the book does not cover all topics of my own courses on the subject anymore. Therefore, I started to think about a serious revision of the book when I moved to the European University Institute in Florence in 2002. Here in the lovely hills of Toscany I had the time to think about bigger projects again and decided to prepare a substantial revision of my previous book. Because the label Second Edition was already used for a previous reprint of the book, I decided to modify the title and thereby hope to signal to potential readers that significant changes have been made relative to my previous multiple time series book. Although Chapters 1–5 still contain an introduction to the vector autoregressive (VAR) methodology and their structure is largely the same as in Lutkepohl ¨ (1991), there have been some adjustments and additions, partly in response to feedback from students and colleagues. In particular, some discussion on multi-step causality and also bootstrap inference for impulse
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