EconPapers    
Economics at your fingertips  
 

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

Abstract: 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.

Date: 2004
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)
http://www.tandfonline.com/doi/abs/10.1080/0003684042000217661 (text/html)
Access to full text is restricted to subscribers.

Related works:
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:taf:applec:v:36:y:2004:i:6:p:627-635

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

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 ().

 
Page updated 2020-01-07
Handle: RePEc:taf:applec:v:36:y:2004:i:6:p:627-635