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 :
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