DocumentCode :
2728178
Title :
Genetic programming in economic modelling
Author :
Duyvesteyn, Korneel ; Kaymak, Uzay
Author_Institution :
Econometric Inst., Erasmus Univ. Rotterdam, Netherlands
Volume :
2
fYear :
2005
fDate :
2-5 Sept. 2005
Firstpage :
1025
Abstract :
Typically, economists develop models by first selecting a model structure based on theoretical considerations and equilibrium conditions, followed by parameter estimation from available data. As more and more data become available about economic processes, the question arises whether it is possible to obtain models in which "data speak for themselves", where both the model structure and the parameter values are identified directly from the data. In this paper, we discuss how genetic programming might be used for this purpose. We propose a framework to formulate a genetic programming search for suitable economic models. We also study a simple case and discuss future directions of research for developing the genetic programming methodology for economic modelling.
Keywords :
economics; genetic algorithms; parameter estimation; search problems; economic modelling; genetic programming search; parameter estimation; Chaos; Decision making; Econometrics; Economic forecasting; Environmental economics; Equations; Genetic programming; Parameter estimation; Power generation economics; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
Type :
conf
DOI :
10.1109/CEC.2005.1554803
Filename :
1554803
Link To Document :
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