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Teaching Computational Economics to Graduate Students

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  • David Kendrick

Abstract

The teaching of computational economics to graduate students has mostly been in a single course with a focus on algorithms and computer code. The shortcoming with this approach is that it neglects one of the most important aspects of computational economics - namely model development skills. These skills are the ability to conceptualize the science, engineering and economics of a problem and to convert that understanding first to a mathematical model and then to a computational representation in a software system. Thus we recommend that a two course sequence in computational economics be created for graduate students with the first course focusing on model development skills and the second course on algorithms and the speed and accuracy of computer codes. We believe that a model development course is most helpful to graduate students when it introduces the students to a wide variety of computational models created by past generations and ask them to first make small modification in order to better understand the models, the mathematics and the software. This is turn is followed by encouraging them to make more substantial modifications of the student’s own choosing so as to move the models in directions that permit the students to address current economic problems. We think that the key element of this process is it's enhancement of the creative abilities of our students.
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Suggested Citation

  • David Kendrick, 2007. "Teaching Computational Economics to Graduate Students," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 381-391, November.
    • Handle: RePEc:kap:compec:v:30:y:2007:i:4:p:381-391
    DOI: 10.1007/s10614-007-9099-x
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    2. Alfredo M. Navarro, 2019. "Relaciones entre la Economía y la Teoría de la Evolución," Asociación Argentina de Economía Política: Working Papers 4180, Asociación Argentina de Economía Política.
    3. Leigh Tesfatsion, 2017. "Elements of Dynamic Economic Modeling: Presentation and Analysis," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 192-216, March.
    4. repec:eur:ejfejr:25 is not listed on IDEAS
    5. mercado, p. ruben & porta, fernando, 2012. "Development planning in the xxi century? a note on old and new methods and tools," MPRA Paper 58610, University Library of Munich, Germany.

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    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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