Quantile Regression for Cross-Sectional and Time Series Data Applica
This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit
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Jorge M. Uribe Montserrat Guillen
Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R
SpringerBriefs in Finance
More information about this series at http://www.springer.com/series/10282
Jorge M. Uribe Montserrat Guillen •
Quantile Regression for Cross-Sectional and Time Series Data Applications in Energy Markets Using R
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Jorge M. Uribe Faculty of Economics and Business Open University of Catalonia Barcelona, Spain
Montserrat Guillen Department of Econometrics University of Barcelona Barcelona, Spain
ISSN 2193-1720 ISSN 2193-1739 (electronic) SpringerBriefs in Finance ISBN 978-3-030-44503-4 ISBN 978-3-030-44504-1 (eBook) https://doi.org/10.1007/978-3-030-44504-1 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 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, expressed 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This book project started during the writing of the Ph.D. thesis of Jorge, under the supervision of Montserrat, at the University of Barcelona in 2015. Quantile regression back then quickly became a useful tool to answer some intriguing research questions in economics and finance for several of the thesis chapters, and also as a preliminary data visualization device that served us to construct a complete panorama of the variables involved in the different economic models explored during the conducting of several research projects. We also noticed then that there was a lack of bibliographical resources approaching the topic from a rather eclectic perspective, which leaves out the technicalities that feature the methodology, and that focus on the more practical aspects of quantile regression implementation, and more imp
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