IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v25y2005i3p229-254.html
   My bibliography  Save this article

Teaching Computational Economics in an Applied Economics Program

Author

Listed:
  • Mario Miranda

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. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Mario Miranda, 2005. "Teaching Computational Economics in an Applied Economics Program," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 229-254, June.
    • Handle: RePEc:kap:compec:v:25:y:2005:i:3:p:229-254
    DOI: 10.1007/s10614-005-2207-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-005-2207-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-005-2207-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    2. Stephen J. Turnovsky, 2000. "Methods of Macroeconomic Dynamics, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262201232, December.
    3. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    4. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Heshmati, Almas & Lenz-Cesar, Flávio, 2013. "Determinants and Policy Simulation of Firms Cooperation in Innovation," IZA Discussion Papers 7487, Institute of Labor Economics (IZA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, December.
    2. Alejandro Mosiño, 2012. "Using Chebyshev Polynomials to Approximate Partial Differential Equations: A Reply," Computational Economics, Springer;Society for Computational Economics, vol. 39(1), pages 13-27, January.
    3. Posch, Olaf & Trimborn, Timo, 2013. "Numerical solution of dynamic equilibrium models under Poisson uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2602-2622.
    4. Dorothée Charlier & Alejandro Mosino & Aude Pommeret, 2011. "Energy-saving Technology Adoption under Uncertainty in the Residential Sector," Annals of Economics and Statistics, GENES, issue 103-104, pages 43-70.
    5. Franz Wirl, 2008. "Optimal maintenance and scrapping versus the value of back ups," Computational Management Science, Springer, vol. 5(4), pages 379-392, October.
    6. Mosiño, Alejandro & Pommeret, Aude, 2015. "Switching to clean(er) technologies in a stochastic environment," MPRA Paper 83841, University Library of Munich, Germany.
    7. Wirl, Franz, 2006. "Consequences of irreversibilities on optimal intertemporal CO2 emission policies under uncertainty," Resource and Energy Economics, Elsevier, vol. 28(2), pages 105-123, May.
    8. Andreas Lanz & Gregor Reich & Ole Wilms, 2022. "Adaptive grids for the estimation of dynamic models," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 179-238, June.
    9. Posch, Olaf, 2009. "Structural estimation of jump-diffusion processes in macroeconomics," Journal of Econometrics, Elsevier, vol. 153(2), pages 196-210, December.
    10. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
    11. Heer Burkhard & Maußner Alfred, 2011. "Value Function Iteration as a Solution Method for the Ramsey Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(4), pages 494-515, August.
    12. Letendre, Marc-Andre & Smith, Gregor W., 2001. "Precautionary saving and portfolio allocation: DP by GMM," Journal of Monetary Economics, Elsevier, vol. 48(1), pages 197-215, August.
    13. Miao, Jianjun & Wang, Neng, 2007. "Investment, consumption, and hedging under incomplete markets," Journal of Financial Economics, Elsevier, vol. 86(3), pages 608-642, December.
    14. Lilia Maliar & Serguei Maliar & John B. Taylor & Inna Tsener, 2020. "A tractable framework for analyzing a class of nonstationary Markov models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1289-1323, November.
    15. Lorenzo Bretscher & Alex Hsu & Andrea Tamoni, 2019. "Response of the Macroeconomy to Uncertainty Shocks:the Risk Premium Channel," 2019 Meeting Papers 1567, Society for Economic Dynamics.
    16. Salvador Ortigueira & Joana Pereira, 2016. "Lack of Commitment, Retroactive Tax Changes, and Macroeconomic Instability," Working Papers WP2016-05, University of Miami, Department of Economics.
    17. repec:mea:meawpa:13274 is not listed on IDEAS
    18. Pichler, Paul, 2011. "Solving the multi-country Real Business Cycle model using a monomial rule Galerkin method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 240-251, February.
    19. Jaakkola, Niko & van der Ploeg, Frederick, 2019. "Non-cooperative and cooperative climate policies with anticipated breakthrough technology," Journal of Environmental Economics and Management, Elsevier, vol. 97(C), pages 42-66.
    20. Stefan Franz Schubert & Udo Broll, 2015. "Consumption, inflation risk and dynamic hedging," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(2), June.
    21. Lohano, Heman Das, 2002. "A Stochastic Dynamic Programming Analysis of Farmland Investment and Financial Management," Faculty and Alumni Dissertations 309035, University of Minnesota, Department of Applied Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:25:y:2005:i:3:p:229-254. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.