Maitre Assistant, High Institute of Commerce of Sfax, University of Sfax, P.O.Box 1081-3018, Sfax, Tunisia
Abstract
This paper investigates the performances of artificial neural networks approximation, the Translog and the Fourier flexible functional forms for the cost function, when different production technologies are used. Using simulated data bases, the author provides a comparison in terms of capability to reproduce input demands and in terms of the corresponding input elasticities of substitution estimates. The results suggest that ANN provide a better approximation than other traditional functional forms only when a single technology is used. However, when elasticities of substitution are calculated, the Translog approximate batters the true technology in both single and mixed technology.
Feki, R. (2007). Comparison of the performances of neural networks specification, the Translog and the Fourier flexible forms when different production technologies are used. Journal of Industrial Engineering, International, 3(5), 53-60.
MLA
R Feki. "Comparison of the performances of neural networks specification, the Translog and the Fourier flexible forms when different production technologies are used". Journal of Industrial Engineering, International, 3, 5, 2007, 53-60.
HARVARD
Feki, R. (2007). 'Comparison of the performances of neural networks specification, the Translog and the Fourier flexible forms when different production technologies are used', Journal of Industrial Engineering, International, 3(5), pp. 53-60.
VANCOUVER
Feki, R. Comparison of the performances of neural networks specification, the Translog and the Fourier flexible forms when different production technologies are used. Journal of Industrial Engineering, International, 2007; 3(5): 53-60.
)