Efficiency in Public Sector: A Neural Network Approach
Here artificial neural networks (ANNs) are employed for efficiency purposes. First, the main features of ANNs are presented. Then, common techniques of the efficiency literature are reviewed: parametric (deterministic and stochastic) and non-parametric (Data Envelopment Analysis [DEA] and Free Disposal Hull [FDH]). ANNs are proposed for frontier approximation. Their advantages and drawbacks in the efficiency context are examined. Finally, these various methodologies are applied to refuse collection services using a sample of Spanish (Catalonian) municipalities. The results are compared with PearsonÂ´s correlation and Spearman rank-correlation coefficients
|Date of creation:||11 Aug 2004|
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- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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