Skip to main content
Log in

Teaching Computational Economics in an Applied Economics Program

  • Published:
Computational Economics Aims and scope Submit manuscript

Abstract

Effective teaching of computational methods to economists in an introductory graduate-level course requires difficult choices regarding the material to be covered, the level at which the material will be covered, and the role of assigned exercises, laboratory sessions, and required readings. In this paper, I discuss the goals that I set and the pedagogical choices that I make in teaching computational methods to doctoral students in economics in a quarter-length course. The discussion is based on 15 years of teaching computational methods to students with a broad range of research interests and professional objectives. I also discuss some of the pedagogical obstacles that I often face when teaching the course and how I address them. I hope that the discussion will provide a useful starting point for instructors wishing to develop computational methods courses in other economics graduate programs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Atkinson, K.E. (1989). An Introduction to Numerical Analysis, 2nd edn. Wiley, New York.

    Google Scholar 

  • Cheney, W. and Kincaid, D. (1985). Numerical Mathematics and Computers, 3rd edn. Brooks/Cole, Pacific Grove, CA.

    Google Scholar 

  • Cottle, R.W., Pang, J.-S. and Stone, R.E. (1992). The Linear Complementarity Problem. Academic Press, San Diego.

    Google Scholar 

  • Dennis, J.E., Jr. and Schnabel, R.B. (1983). Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Dixit, A.K. and Pindyck, R.S. (1994). Investment Under Uncertainty. Princeton University Press, Princeton, NJ.

    Google Scholar 

  • Ferris, M.C. and Pang, J.S. (1997). Engineering and economic applications of complementarity problems. SIAM Review, 39, 669–713.

    Article  Google Scholar 

  • Fletcher, C.A.J. (1984). Computational Galerkin Techniques. Springer-Verlag, New York.

    Google Scholar 

  • Gill, P.E., Murray, W. and Wright, M.H. (1981). Practical Optimization. Academic Press, New York.

    Google Scholar 

  • Judd, K.L. (1992). Projection methods for solving aggregate growth models. Journal of Economic Theory, 58, 410–452.

    Article  Google Scholar 

  • Judd, K.L. (1994). Approximation, perturbation, and projection methods in economic analysis. In H. Amman, D.A. Kendrick and J. Rust (eds.), Handbook of Computational Economics, Vol. 1, 509–586. North-Holland, New York.

    Google Scholar 

  • Judd, K.L. (1998). Numerical Methods in Economics. MIT Press, Cambridge, MA.

    Google Scholar 

  • Kincaid, D. and Cheney, W. (1991). Numerical Analysis: Mathematics of Scientific Computing. Brooks/Cole, Pacific Grove, CA.

    Google Scholar 

  • Miranda, M.J. and Fackler, P.W. (2002). Applied Computational Economics and Finance. MIT Press, Cambridge, MA.

    Google Scholar 

  • Ortega, J.M. and Rheinboldt, W.C. (1970). Iterative Solution of Nonlinear Equations in Several Variables. Academic Press, New York.

    Google Scholar 

  • Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (1992). Numerical Recipes, 2nd edn. Cambridge University Press, Cambridge.

    Google Scholar 

  • Rivlin, T.J. (1990). Chebyshev Polynomials: From Approximation Theory to Algebra and Number Theory, 2nd edn. Wiley, New York.

    Google Scholar 

  • Sargent, T.J. (1987). Dynamic Macroeconomic Theory. Harvard University Press, Cambridge, MA.

    Google Scholar 

  • Stokey, N.L. and Lucas, R.E. (1989). Recursive Methods in Economic Dynamics. Harvard University Press, Cambridge, MA.

    Google Scholar 

  • Turnovsky, S.J. (2000). Methods of Macroeconomic Dynamics, 2nd edn. MIT Press, Cambridge, MA.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Miranda, M.J. Teaching Computational Economics in an Applied Economics Program. Comput Econ 25, 229–254 (2005). https://doi.org/10.1007/s10614-005-2207-x

Download citation

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10614-005-2207-x

KeyWords

Navigation