Using R to teach econometrics

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Using R to teach econometrics

Author Info

Jeff Racine (Department of Economics, University of South Florida Tampa, FL, 33620 USA)
Rob Hyndman (Department of Econometrics & Business Statistics, Monash University, Melbourne, VIC 3800, Australia)

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Abstract

R, an open-source programming environment for data analysis and graphics, has in only a decade grown to become a de-facto standard for statistical analysis against which many popular commercial programs may be measured. The use of R for the teaching of econometric methods is appealing. It provides cutting-edge statistical methods which are, by R's open-source nature, available immediately. The software is stable, available at no cost, and exists for a number of platforms, including various flavours of Unix and Linux, Windows (9x|NT|2000), and the MacOS. Manuals are also available for download at no cost, and there is extensive on-line information for the novice user. This review focuses on using R for teaching econometrics. Since R is an extremely powerful environment, this review should also be of interest to researchers. Copyright © 2002 John Wiley & Sons, Ltd.

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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 17 (2002)
Issue (Month): 2 ()
Pages: 175-189
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Handle: RePEc:jae:japmet:v:17:y:2002:i:2:p:175-189

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Paper
- Racine, J & Hyndman, R.J., 2001. "Using R to Teach Econometrics," Monash Econometrics and Business Statistics Working Papers 10/2001, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]

References listed on IDEAS
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Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January. [Downloadable!] (restricted)

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

Christine Choirat & Raffello Seri, 2009. "Econometrics with Python," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 698-704. [Downloadable!]
Ryan J. Smith & J. Wilson Mixon Jr, 2006. "Teaching undergraduate econometrics with GRETL," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1103-1107. [Downloadable!]
A. Talha Yalta & Riccardo Lucchetti, 2008. "The GNU|Linux platform and freedom respecting software for economists," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 279-286. [Downloadable!]
Jinhu Li & Jeffrey S. Racine, 2008. "Maxima: An open source computer algebra system," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 515-523. [Downloadable!]
Giovanni Baiocchi, 2007. "Reproducible research in computational economics: guidelines, integrated approaches, and open source software," Computational Economics, Springer, vol. 30(1), pages 19-40, August. [Downloadable!] (restricted)
Kurt Hornik & Friedrich Leisch & Christian Kleiber & Achim Zeileis, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121. [Downloadable!]
Miguel Rodrigues, 2005. "Regression with R," Econometrics 0508016, EconWPA. [Downloadable!]

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