A Comparative Approximate Economic Behavior Analysis of Support Vector Machines and Neural Networks Models

Amin Gharipour (), Morteza Sameti and Ali Yousefian ()
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Morteza Sameti: Economic Dep., University of Isfahan, Iran

Iranian Economic Review (IER), 2010, vol. 15, issue 2, 17-40

Abstract: The application of the artificial neural networks in economics and business goes back to 1950s, while the main part of the applications has been developed in more recent years. Reviewing this research indicates that the development and applications of neural network are not limited to a specific application area as it spans a wide variety of fields from prediction to classification, as most of the applications in economics primarily focus on the predictive power of the neural networks. Many researches using statistical and Neural Networks (NNs) models in economics but few involved support vector machines in their studies. In this paper for the first time we compare the approximate economic behavior ability of artificial neural networks (ANN) and support vector machines using a set of data on some Middle East countries.

Keywords: Artificial Neural Networks; Forecasting; Support Vector Machines; Gross Domestic Product (GDP). (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eut:journl:v:15:y:2010:i:2:p:17

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