Applied Econometrics with R
This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel
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Use R! Albert: Bayesian Computation with R Bivand/Pebesma/G´omez-Rubio: Applied Spatial Data Analysis with R Claude: Morphometrics with R Cook/Swayne: Interactive and Dynamic Graphics for Data Analysis: With R and GGobi Hahne/Huber/Gentleman/Falcon: Bioconductor Case Studies Kleiber/Zeileis, Applied Econometrics with R Nason: Wavelet Methods in Statistics with R Paradis: Analysis of Phylogenetics and Evolution with R Peng/Dominici: Statistical Methods for Environmental Epidemiology with R: A Case Study in Air Pollution and Health Pfaff: Analysis of Integrated and Cointegrated Time Series with R, 2nd edition Sarkar: Lattice: Multivariate Data Visualization with R Spector: Data Manipulation with R
Christian Kleiber · Achim Zeileis
Applied Econometrics with R
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Christian Kleiber Universit¨at Basel WWZ, Department of Statistics and Econometrics Petersgraben 51 CH-4051 Basel Switzerland [email protected]
Achim Zeileis Wirtschaftsuniversit¨at Wien Department of Statistics and Mathematics Augasse 2–6 A-1090 Wien Austria [email protected]
Series Editors Robert Gentleman Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Avenue N., M2-B876 PO Box 19024, Seattle, Washington 98102-1024 USA
Kurt Hornik Department of Statistics and Mathematics Wirtschaftsuniversit¨at Wien Augasse 2–6 A-1090 Wien Austria
Giovanni Parmigiani The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University 550 North Broadway Baltimore, MD 21205-2011 USA
ISBN: 978-0-387-77316-2 DOI: 10.1007/978-0-387-77318-6
e-ISBN: 978-0-387-77318-6
Library of Congress Control Number: 2008934356 c 2008 Springer Science+Business Media, LLC 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.com
Preface
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially developed at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned rou
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