About this book
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 data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research.
An R package accompanying this book, AER, is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/package=AER.
It contains some 100 data sets taken from a wide variety of sources, the full source code for all examples used in the text plus further worked examples, e.g., from popular textbooks. The data sets are suitable for illustrating, among other things, the fitting of wage equations, growth regressions, hedonic regressions, dynamic regressions and time series models as well as models of labor force participation or the demand for health care.
The goal of this book is to provide a guide to R for users with a background in economics or the social sciences. Readers are assumed to have a background in basic statistics and econometrics at the undergraduate level. A large number of examples should make the book of interest to graduate students, researchers and practitioners alike.
Christian Kleiber is Professor of Econometrics and Statistics at Universität Basel, Switzerland. Achim Zeileis is Assistant Professor in the Dept. of Statistics and Mathematics at Wirtschaftsuniversität Wien, Austria. R users since version 0.64.0, they have been collaborating on econometric methodology in R, including several R packages, for the past eight years.
- Book Title Applied Econometrics with R
- Series Title Use R
- DOI https://doi.org/10.1007/978-0-387-77318-6
- Copyright Information Springer Science+Business Media, LLC 2008
- Publisher Name Springer, New York, NY
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Softcover ISBN 978-0-387-77316-2
- eBook ISBN 978-0-387-77318-6
- Edition Number 1
- Number of Pages X, 222
- Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
Statistics for Business, Management, Economics, Finance, Insurance
Economic Theory/Quantitative Economics/Mathematical Methods
Game Theory, Economics, Social and Behav. Sciences
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- Industry Sectors
- Finance, Business & Banking
Researchers in quantitative social sciences in general, and econometrics in particular, have often favored scripting languages such as GAUSS or Stat, or packages such as EViews. Introducing R to this particular audience could therefore be a well-appreciated title among the growing number of publications about R…. So, is this a good introduction of R for econometricians? Absolutely— with a well-rounded selection of available methodologies, both classic and current, and a good focus on introducing graphical methods, as well as gently covering more novel and therefore less familiar approaches, it fulfills its task with aplomb. The writing style is conversational without being shallow. (Dirk Eddelbuettel, Journal of Statistical Software, February 2009, Vol. 29, Book Review 14)