Semiparametric and Nonparametric Methods in Econometrics
Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that
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Joel L. Horowitz
Semiparametric and Nonparametric Methods in Econometrics
Semiparametric and Nonparametric Methods in Econometrics
Springer Series in Statistics Advisors P. Bickel, P. Diggle, S. Fienberg, U. Gather, I. Olkin, S. Zeger
For other titles published in this series, go to http://www.springer.com/series/692
Joel L. Horowitz
Semiparametric and Nonparametric Methods in Econometrics
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Joel L. Horowitz Northwestern University Department of Economics 2001 Sheridan Road Evanston IL 60208 USA [email protected]
ISBN 978-0-387-92869-2 e-ISBN 978-0-387-92870-8 DOI 10.1007/978-0-387-92870-8 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009929719 © Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
This book is intended to introduce graduate students and practicing professionals to some of the main ideas and methods of semiparametric and nonparametric estimation in econometrics. It contains more than enough material for a one-semester graduate-level course and, to a large extent, is based on a course in semiparametric and nonparametric methods that I teach at Northwestern University. In the book, as in the course, I try to emphasize key ideas and provide an intuitive grasp of how things work while avoiding formal proofs, which in this field tend to be highly technical, lengthy, and intimidating. Readers who want to see the proofs can find them in the references that are cited in the book. The book is mainly methodological, but it includes empirical examples that illustrate the usefulness of the estimation methods that are presented. The main prerequisite for this book is knowledge of econometric theory, especially asymptotic distribution theory, at the level found (for example) in the textbooks by Amemiya (1985) and Davidson and MacKinnon (1993) and the Handbook of Econometrics chapter by McFadden and Newey (1994). The literature in semiparametric and nonparametric estimation in econometrics and statistics is huge. A book of encyclopedic length would be needed to cover it exhaustively. The treatment in this book is highly selective. It presents a relatively small set of methods that are important for applied research and that use and, thereby,
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