On the Approximation of Production Functions: A Comparison of Artificial Neural Networks Frontiers and Efficiency Techniques

Daniel Santín

No 2004/03, Efficiency Series Papers from University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG)

Abstract: The aim of this paper is to show how artificial neural networks (ANN) is a valid semi-parametric alternative for fitting production functions and measuring technical efficiency. To do this a Monte Carlo experiment is carried out on a simulated smooth production technology for assessing efficiency results of ANN compared with Data Envelopment Analysis (DEA) and Corrected Ordinary Least Squares (COLS). As ANN provides average production function estimations this paper proposes a so-called thick frontier strategy to transform average estimations into a productive frontier. Main advantages of ANN are in contexts where the production function is smooth, completely unknown, contains non-linear relationships among variables and the quantity of noise and efficiency in data is moderate. Under this scenario, the results display that an ANN algorithm can detect, better than traditional tools, the underlying shape of the production function from observed data.

Keywords: Neural networks; production function; technical efficiency (search for similar items in EconPapers)
Pages: 18
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.unioviedo.es/oeg/ESP/esp_2004_03.pdf (application/pdf)

Related works:
Journal Article: On the approximation of production functions: a comparison of artificial neural networks frontiers and efficiency techniques (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oeg:wpaper:2004/03

Access Statistics for this paper

More papers in Efficiency Series Papers from University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG) Departamento de Economía, Facultad de Economía y Empresa, Universidad de Oviedo, Avenida del Cristo, s/n. 33006 Oviedo - SPAIN. Contact information at EDIRC.
Bibliographic data for series maintained by Luis Orea () and David Roibas ().