Time Series Econometrics
This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the s
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Klaus Neusser
Time Series Econometrics
Springer Texts in Business and Economics
More information about this series at http://www.springer.com/series/10099
Klaus Neusser
Time Series Econometrics
123
Klaus Neusser Bern, Switzerland
ISSN 2192-4333 ISSN 2192-4341 (electronic) Springer Texts in Business and Economics ISBN 978-3-319-32861-4 ISBN 978-3-319-32862-1 (eBook) DOI 10.1007/978-3-319-32862-1 Library of Congress Control Number: 2016938514 © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved 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. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
Over the past decades, time series analysis has experienced a proliferous increase of applications in economics, especially in macroeconomics and finance. Today these tools have become indispensable to any empirically working economist. Whereas in the beginning the transfer of knowledge essentially flowed from the natural sciences, especially statistics and engineering, to economics, over the years theoretical and applied techniques specifically designed for the nature of economic time series and models have been developed. Thereby, the estimation and identification of structural vector autoregressive models, the analysis of integrated and cointegrated time series, and models of volatility have been extremely fruitful and far-reaching areas of research. With the award of the Nobel Prizes to Clive W. J. Granger and Robert F. Engle III in 2003 and to Thomas J. Sargent and Christopher A. Sims in 2011, the field has reached a certain degree of maturity. Thus, the idea suggests itself to assemble the vast amount of material scattered over many papers into a comprehensive textbook. The book is self-contained and addresses economics students who have already some prerequisite knowledge in econometrics. It is thus suited for advanced bachelor, master’s, or beginning PhD st
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