The measurement of technical efficiency: a neural network approach
Daniel Santín (),
Francisco Delgado () and
Aurelia Valiño Castro ()
Applied Economics, 2004, vol. 36, issue 6, 627-635
The main purpose of this paper is to provide an introduction to artificial neural networks (ANNs) and to review their applications in efficiency analysis. Finally, a comparison of efficiency techniques in a non-linear production function is carried out. The results suggest that ANNs are a promising alternative to traditional approaches, econometric models and non-parametric methods such as data envelopment analysis, to fit production functions and measure efficiency under non-linear contexts.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:36:y:2004:i:6:p:627-635
Ordering information: This journal article can be ordered from
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().