Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by
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Estela Bee Dagum Silvia Bianconcini
Seasonal Adjustment Methods and Real Time TrendCycle Estimation
Statistics for Social and Behavioral Sciences
Series editor Stephen E. Fienberg Carnegie Mellon University Pittsburgh Pennsylvania USA
Statistics for Social and Behavioral Sciences (SSBS) includes monographs and advanced textbooks relating to education, psychology, sociology, political science, public policy, and law.
More information about this series at http://www.springer.com/series/3463
Estela Bee Dagum • Silvia Bianconcini
Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
123
Estela Bee Dagum Department of Statistical Sciences University of Bologna Bologna, Italy
Silvia Bianconcini Department of Statistical Sciences University of Bologna Bologna, Italy
ISSN 2199-7357 ISSN 2199-7365 (electronic) Statistics for Social and Behavioral Sciences ISBN 978-3-319-31820-2 ISBN 978-3-319-31822-6 (eBook) DOI 10.1007/978-3-319-31822-6 Library of Congress Control Number: 2016938799 Mathematics Subject Classification (2010): 62G08, 62M10, 62P20, 62P25 © 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
To my sons, Alex, Paul, and Leo, with their lovely families for their strong valuable support and lively discussions during the writing of this book To Paolo who always inspires me to try my best
Preface
In order to assess the current stage of the business cycle at which the economy stands, real time trend-cycle estimates are needed. The basic approach is that of assessing the real time trend-cycle of major socioeconomic indicators (leading, coincident, and lagging) using percentage changes, based on seasonally adjusted data, calculated for months and quarters in chronological sequence. The main goal is to evaluate the behavior of the economic indicator
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