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Predicting a Country’s Growth: A First Look

In: Machine-learning Techniques in Economics

Author

Listed:
  • Atin Basuchoudhary

    (Virginia Military Institute)

  • James T. Bang

    (St. Ambrose University)

  • Tinni Sen

    (Virginia Military Institute)

Abstract

In this chapter, we run different algorithm techniques to identify the algorithms that best predict growth. We show how machine learning can be used to validate different growth models. We suggest that validated algorithms enhance the confidence academics should place on any given theoretical growth model. We then show how machine learning can help researchers understand what kinds of concepts may make theoretical growth models more complete.

Suggested Citation

  • Atin Basuchoudhary & James T. Bang & Tinni Sen, 2017. "Predicting a Country’s Growth: A First Look," SpringerBriefs in Economics, in: Machine-learning Techniques in Economics, chapter 0, pages 29-36, Springer.
    • Handle: RePEc:spr:spbchp:978-3-319-69014-8_4
    DOI: 10.1007/978-3-319-69014-8_4
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