• DocumentCode
    3071617
  • Title

    Economic policy making using neural networks

  • Author

    Mostaghimi, Mehdi ; Yu, Winnie

  • Author_Institution
    Dept. of Portfolio Anal., Pfizer Central Res., Groton, CT, USA
  • fYear
    1997
  • fDate
    5-7 Oct 1997
  • Firstpage
    356
  • Lastpage
    358
  • Abstract
    Neural networks are introduced for economic policy making. A desirable property of a policy instrument is its speedy impact on the economic system. Monetary policy is generally recognized as the one, relative to the fiscal policy, which is easier to implement and its impact is faster to realize. An application of the simultaneous perturbation stochastic approximation-based neural networks to monetary policy formulation for the US economy shows that its policy is faster to respond to sudden changes in the dynamic of the system than a traditional linear feedback policy
  • Keywords
    approximation theory; economic cybernetics; feedback; neural nets; US economy; economic policy making; fiscal policy; monetary policy; policy instrument; simultaneous perturbation stochastic approximation-based neural networks; Computer science; Decision making; Econometrics; Economic forecasting; Finance; Government; Instruments; Mathematical model; Neural networks; Portfolios;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications, 1997., Proceedings of the 1997 IEEE International Conference on
  • Conference_Location
    Hartford, CT
  • Print_ISBN
    0-7803-3876-6
  • Type

    conf

  • DOI
    10.1109/CCA.1997.627576
  • Filename
    627576