Neural Network Based Models for Efficiency Frontier Analysis: An Application to East Asian Economies' Growth Decomposition
AbstractThere has been a long tradition in business and economics to use frontier analysis to assess a production unit's performance. The first attempt utilized the data envelopment analysis (DEA) which is based on a piecewise linear and mathematical programming approach, whilst the other employed the parametric approach to estimate the stochastic frontier function. Both approaches have their advantages as well as limitations. This paper sets out to use an alternative approach, i.e. artificial neural networks (ANNs) for measuring efficiency and productivity growth for seven East Asian economies at manufacturing level, for the period 1963 to 1998, and the relevant comparisons are carried out between DEA and ANN, and stochastic frontier analysis (SFA) and ANN in order to test the ability of ANNs to assess the performance of production units. The results suggest that ANNs are a promising alternative to traditional approaches, to approximate production functions more accurately and measure efficiency and productivity under non-linear contexts, with minimum assumptions.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Global Economic Review.
Volume (Year): 36 (2007)
Issue (Month): 4 ()
Contact details of provider:
Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=111729
Other versions of this item:
- Hailin Liao & Bin Wang & Tom Weyman-Jones, 2007. "Neural Network Based Models for Efficiency Frontier Analysis: An Application to East Asian Economies' Growth Decomposition," Discussion Paper Series 2007_24, Department of Economics, Loughborough University, revised Nov 2007.
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
- O53 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
- L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.