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
Link To Document