Multivariate Modelling of Non-Stationary Economic Time Series
This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stati
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Multivariate Modelling of Non-Stationary Economic Time Series John Hunter Simon P. Burke Alessandra Canepa
Palgrave Texts in Econometrics
This is a series of themed books in econometrics, where the subject is interpreted as including theoretical developments, applied econometrics and more specialized fields of application, for example financial econometrics, the econometrics of panel data sets, forecasting and so on. Each book in the series is directed to particular aspects of the underlying and unifying theme. More information about this series at http://www.springer.com/series/14078
John Hunter • Simon P. Burke • Alessandra Canepa
Multivariate Modelling of Non-Stationary Economic Time Series
John Hunter Department of Economics and Finance Brunel University Uxbridge, UK
Simon P. Burke Department of Economics University of Reading Reading, UK
Alessandra Canepa Department of Economics and Finance Brunel University Uxbridge, UK
Palgrave Texts in Econometrics ISBN 978-0-230-24330-9 ISBN 978-1-137-31303-4 (eBook) ISBN 978-0-230-24331-6 (softcover) DOI 10.1057/978-1-137-31303-4 Library of Congress Control Number: 2016957164 © The Editor(s) (if applicable) and The Author(s) 2017 1st edition: © Palgrave Macmillan 2005 The author(s) has/have asserted their right(s) to be identified as the author(s) of this work in accordance with the Copyright, Designs and Patents Act 1988. This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover illustration: Cover image © Chad Baker Printed on acid-free paper This Palgrave Macmillan imprint is published by Springer Nature The registered company is Macmillan Publishers Ltd. The registered company address is: The Campus, 4 Crinan Street, London, N1 9XW, United Kingdom
Preface
The authors felt that, rather than produce a second edition of their book Modelling Non-Stationary Economic Time Series, there
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