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Using R to Teach Econometrics

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  • Racine, J
  • Hyndman, R.J.

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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. 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.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2001/wp10-01.pdf
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Bibliographic Info

Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 10/01.

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Length: 15 pages
Date of creation: Nov 2001
Date of revision:
Handle: RePEc:msh:ebswps:2001-10

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Keywords: Econometrics; Statistical software; Teaching;

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  1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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Cited by:
  1. Robert Finger, 2010. "Review of ‘Robustbase’ software for R," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(7), pages 1205-1210, November/.
  2. 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.
  3. 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.
  4. Zeileis, Achim & Leisch, Friedrich & Kleiber, Christian & Hornik, Kurt, 2002. "Monitoring structural change in dynamic econometric models," Technical Reports 2002,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  5. Miguel Rodrigues, 2005. "Regression with R," Econometrics 0508016, EconWPA.
  6. Shahram Amini & Christopher F. Parmeter, 2011. "A Review of the `BMS' Package for R," Working Papers 2011-8, University of Miami, Department of Economics.
  7. A. Talha Yalta & Riccardo Lucchetti, 2010. "The GNU/Linux Platform and Freedom Respecting Software for Economists," Working Papers 1005, TOBB University of Economics and Technology, Department of Economics.
  8. Giovanni Baiocchi, 2007. "Reproducible research in computational economics: guidelines, integrated approaches, and open source software," Computational Economics, Society for Computational Economics, vol. 30(1), pages 19-40, August.
  9. Zeileis, Achim, 2006. "Implementing a class of structural change tests: An econometric computing approach," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 2987-3008, July.
  10. Christine Choirat & Raffello Seri, 2009. "Econometrics with Python," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 698-704.

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