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Reliability of Statistical Software

Listed author(s):
  • Oluwarotimi O. Odeh
  • Allen M. Featherstone
  • Jason S. Bergtold

The reliability of several statisitcal software packages was examined using the National Institute of Standards and Technology linear and nonlinear least squares datasets and models. Software tested include Excel 2007, GAMS 23.4, GAUSS 9.0, LIMDEP 8.0, Mathematica 7.0, MATLAB 7.5, R 2.10, SAS 9.1, SHAZAM 10, and Stata 10. While some of these packages have been previously examined, others, including GAMS and MATLAB, have not been extensively examined. Reliability tests indicate improvements in some of the software packages that were previously tested, but some of these packages failed reliability tests under certain conditions. The findings underscore the need to benchmark software packages to ascertain reliability before use and the importance of solving econometric problems using more than one package. Copyright 2010, Oxford University Press.

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File URL: http://hdl.handle.net/10.1093/ajae/aaq068
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Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

Volume (Year): 92 (2010)
Issue (Month): 5 ()
Pages: 1472-1489

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Handle: RePEc:oup:ajagec:v:92:y:2010:i:5:p:1472-1489
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  1. Silk, Julian, 1996. "Systems Estimation: A Comparison of SAS, SHAZAM and TSP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 437-450, July-Aug..
  2. Yalta, A. Talha, 2007. "The Numerical Reliability of GAUSS 8.0," The American Statistician, American Statistical Association, vol. 61, pages 262-268, August.
  3. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
  4. Sawitzki, Gunther, 1994. "Report on the Numerical Reliability of Data Analysis Systems," Computational Statistics & Data Analysis, Elsevier, vol. 18(2), pages 289-301, September.
  5. B. D. McCullough, 2006. "A review of TESTU01," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 677-682.
  6. Sawitzki, Gunther, 1994. "Testing numerical reliability of data analysis systems," Computational Statistics & Data Analysis, Elsevier, vol. 18(2), pages 269-286, September.
  7. H. D. Vinod & B. D. McCullough, 1999. "The Numerical Reliability of Econometric Software," Journal of Economic Literature, American Economic Association, vol. 37(2), pages 633-665, June.
  8. H. D. Vinod & B. D. McCullough, 1999. "Corrigenda: The Numerical Reliability of Econometric Software," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1565-1565, December.
  9. Simon, Stephen D. & Lesage, James P., 1988. "Benchmarking numerical accuracy of statistical algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 7(2), pages 197-209, December.
  10. A. Talha Yalta, 2010. "The Accuracy of Statistical Distributions in Microsoft (R) Excel 2007," Working Papers 1006, TOBB University of Economics and Technology, Department of Economics.
  11. McCullough, B D, 1999. "Econometric Software Reliability: EViews, LIMDEP, SHAZAM and TSP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 191-202, March-Apr.
  12. H. D. Vinod, 2000. "Review of GAUSS for Windows, including its numerical accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 211-220.
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