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A Python-based undergraduate course in computational macroeconomics

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  • Brian C. Jenkins

Abstract

The author of this article describes a new undergraduate course where students use Python programming for macroeconomic data analysis and modeling. Students develop basic familiarity with dynamic optimization and simulating linear dynamic models, basic stochastic processes, real business cycle models, and New Keynesian business cycle models. Students also gain familiarity with the popular Python libraries NumPy, Matplotlib, and pandas and make extensive use of the Jupyter Notebook. For many students in the course, this is their first experience with computer programming in any language. Feedback from students suggests that, regardless of prior programming experience, they find the course to be valuable, interesting, and enjoyable.

Suggested Citation

  • Brian C. Jenkins, 2022. "A Python-based undergraduate course in computational macroeconomics," The Journal of Economic Education, Taylor & Francis Journals, vol. 53(2), pages 126-140, March.
    • Handle: RePEc:taf:jeduce:v:53:y:2022:i:2:p:126-140
    DOI: 10.1080/00220485.2022.2038322
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    Cited by:

    1. Bongers, Anelí & Molinari, Benedetto & Torres, José L., 2022. "Computers, Programming and Dynamic General Equilibrium Macroeconomic Modeling," MPRA Paper 112505, University Library of Munich, Germany.

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