Introduction to Multiple Time Series Analysis
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Helmut Lütkepohl
Introduction to Multiple Time Series Analysis With 34 Figures
Springer-Verlag Berlin Heidelberg GmbH
Prof. Dr. Helmut Lütkepohl Institute of Statistics and Econometrics University ofKiel Olshausenstraße 40 2300 Kiel, FRG
Library of Congress Cataloging-in-Publication Data Lütkepohl, Helmut. Introduction to multiple time series analysis / Helmut Lütkepohl. p.cm. Includes bibliographical references and indexes. 1. Time-series analysis. I. TitJe. QA280.L87 1991 519.5'5--dc20
This work is subject to copyright. All rights are reserved, whether the whole or part ofthe material is concemed, specifically the rights oftranslation, reprinting, reuse ofillustrations, recitation, broadcasting, reproduction on microfilms or in other ways, and storage in data banks. Duplication ofthis publication or parts thereofis only permitted under the provisions ofthe German Copyright Law of September 9,1965, in its version ofJune 24,1985, and a copyright fee must always be paid. Violations fall under the prosecution act ofthe German Copyright Law. ISBN 978-3-540-53194-4 ISBN 978-3-662-02691-5 (eBook) DOI 10.1007/978-3-662-02691-5 © Springer-Verlag Berlin Heidelberg 1991 Originally published by Springer-Verlag Berlin Heidelberg New York in 1991. The use of 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. 214217130-543210
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Preface
A few years ago, when I started teaching a course on multiple time series analysis for graduate students in business and economics at the University of Kiel, Germany, a suitable textbook was not available. Therefore I prepared lecture notes from which the present text evolved. There are a number of books on time series analysis that contain portions on multiple time series models and methods. However, none of them covers the fuH range of models and methods that are now commonly used in the economics and econometrics literature. The present text also neglects some tools which are currently in widespread use. It goes beyond other time series books, however. Unlike advanced books on the topic such as Hannan & Deistler (1988) this text is written at a level which should be accessible to graduate students in business and economics. The issues and models covered in detail reflect my personal interests. ladmit that some important models and methods are omitted just because I havn't used them much in the past. EspeciaHy the omission of spectral methods may perhaps be regreted by some instructors. Although multiple time series analysis is applied in many disciplines I have prepared the text with economics and business students in mind. The examples and exercises are chosen accordingly. Despite this orientation I hope that the book will also serve multiple time series courses in other fields.1t contains enough material for a one semester course on multiple time series anal
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