IDEAS home Printed from
   My bibliography  Save this article

Using Dynamic Forecasting Genetic Programming (Dfgp) To Forecast United States Gross Domestic Product (Us Gdp) With Military Expenditure As An Explanatory Variable


  • Neal Wagner
  • Jurgen Brauer


Classic time-series forecasting models can be divided into exponential smoothing, regression, ARIMA, threshold, and GARCH models. Functional form is investigator-specified, and all methods assume that the data generation process across all segments of the examined time-series is constant. In contrast, the aim of heuristic methods is to automate the discovery of functional form and permit different segments of a time-series to stem from different underlying data generation processes. These methods are categorized into those based on neural networks (NN) and those based on evolutionary computation, the latter further divided into genetic algorithms (GA), evolutionary programming (EP), and genetic programming (GP). However, the duration of the time-series itself is still investigator determined. This paper uses a dynamic forecasting version of GP (DFGP), where even the length of the time-series is automatically discovered. The method is applied to an examination of US GDP that includes military expenditure among its determinants and is compared to a regression-based forecast. We find that DFGP and a regression-based forecast yield comparable results but with the significant proviso that DFGP does not make any prior assumption about functional form or the time-span from which forecasts are produced.

Suggested Citation

  • Neal Wagner & Jurgen Brauer, 2007. "Using Dynamic Forecasting Genetic Programming (Dfgp) To Forecast United States Gross Domestic Product (Us Gdp) With Military Expenditure As An Explanatory Variable," Defence and Peace Economics, Taylor & Francis Journals, vol. 18(5), pages 451-466.
  • Handle: RePEc:taf:defpea:v:18:y:2007:i:5:p:451-466 DOI: 10.1080/10242690701455508

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    1. Erich Weede, 1992. "Some Simple Calculations on Democracy and War Involvement," Journal of Peace Research, Peace Research Institute Oslo, vol. 29(4), pages 377-383, November.
    2. repec:ucp:bkecon:9780226422534 is not listed on IDEAS
    3. Albert O. Hirschman & Michael Rothschild, 1973. "The Changing Tolerance for Income Inequality in the Course of Economic DevelopmentWith A Mathematical Appendix," The Quarterly Journal of Economics, Oxford University Press, vol. 87(4), pages 544-566.
    4. Lindert, Peter H. & Williamson, Jeffrey G., 1985. "Growth, equality, and history," Explorations in Economic History, Elsevier, vol. 22(4), pages 341-377, October.
    5. Simon Kuznets & Elizabeth Jenks, 1953. "Shares of Upper Income Groups in Income and Savings," NBER Books, National Bureau of Economic Research, Inc, number kuzn53-1.
    6. Hirschman, Albert O., 1973. "The changing tolerance for income inequality in the course of economic development," World Development, Elsevier, vol. 1(12), pages 29-36, December.
    7. Erich Weede, 1984. "Democracy and War Involvement," Journal of Conflict Resolution, Peace Science Society (International), pages 649-664.
    8. J. L. Van Zanden, 1995. "Tracing the beginning of the Kuznets curve: western Europe during the early modern period," Economic History Review, Economic History Society, vol. 48(4), pages 643-664, November.
    9. Stuart A. Bremer, 1992. "Dangerous Dyads," Journal of Conflict Resolution, Peace Science Society (International), pages 309-341.
    10. Acemoglu,Daron & Robinson,James A., 2009. "Economic Origins of Dictatorship and Democracy," Cambridge Books, Cambridge University Press, number 9780521671422, December.
    11. Simon Kuznets, 1950. "Shares of Upper Income Groups in Income and Savings," NBER Books, National Bureau of Economic Research, Inc, number kuzn50-1.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:taf:defpea:v:18:y:2007:i:5:p:451-466. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.