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Programming Languages in Economics

Author

Listed:
  • Hans M. Amman

    () (Eco, U. of Netherlands)

  • David A. Kendrick

    () (Eco, U. of Texas)

Abstract

Young economists sometimes ask which computer programming languages they should learn. This paper answers that question by suggesting that they begin with a high level language like GAUSS, GAMS, Mathematica, Maple or MATLAB depending on their field of specialization in economics. Then they should work down to one of the low level languages such as Fortran, Basic, C, C++ or Java depending on the planned areas of application. Finally, they should proceed to the languages which are used to develop graphical interfaces and internet applications, viz. Visual Basic, C. C++ or Java. Citation Copyright 1999 by Kluwer Academic Publishers.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hans M. Amman & David A. Kendrick, 1995. "Programming Languages in Economics," CARE Working Papers 9504, The University of Texas at Austin, Center for Applied Research in Economics.
  • Handle: RePEc:tex:carewp:9504
    Note: None
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    File URL: http://www.eco.utexas.edu/Ecopapers/wp9504.pdf
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    Citations

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    Cited by:

    1. Buda, Rodolphe, 2005. "Numerical Analysis in Econom(etr)ic Softwares: the Data-Memory Shortage Management," MPRA Paper 9145, University Library of Munich, Germany, revised 2007.
    2. Vieira, Wilson da Cruz & Lelis, Levi H. Santana de, 2005. "Programming languages in economics: a comparison among Fortran77, C++, and Java," Revista de Economia e Agronegocio / Brazilian Review of Economics and Agribusiness, Federal University of Vicosa, Department of Agricultural Economics, vol. 3(3).
    3. Francisco Cribari-Neto & Spyros Zarkos, 2003. "Econometric and Statistical Computing Using Ox," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 277-295, June.
    4. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.
    5. mercado, p. ruben, 2003. "Empirical economywide modeling in argentina," MPRA Paper 58611, University Library of Munich, Germany.
    6. Álvaro Andrés PERDOMO STRAUCH, 2008. "Modelo Estándar de Equilibrio General Computable," ARCHIVOS DE ECONOMÍA 004943, DEPARTAMENTO NACIONAL DE PLANEACIÓN.
    7. Halkos, George & Tsilika, Kyriaki, 2016. "Measures of correlation and computer algebra," MPRA Paper 70200, University Library of Munich, Germany.
    8. Buda, Rodolphe, 2001. "Les algorithmes de la modélisation : une analyse critique pour la modélisation économique," MPRA Paper 3926, University Library of Munich, Germany, revised Jul 2004.
    9. Rodolphe Buda, 2015. "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 325-357, August.
    10. Simon Peters & Ken Clark & Pascal Ekin & Anja Le Blanc & Stephen Pickles, 2007. "Grid Enabling Empirical Economics: A Microdata Application," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 349-370, November.

    More about this item

    Keywords

    Macroeconomics; learning; stochastic optimization; numerical experiments;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

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