Neural Network Based Models for Efficiency Frontier Analysis: An Application to East Asian Economies’ Growth Decomposition
| Autor: | Thomas Weyman-Jones, Hailin Liao, Bin Wang |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Artificial neural network
Computer Science::Neural and Evolutionary Computation Efficient frontier Piecewise linear function Stochastic frontier analysis Economy Political Science and International Relations Economics Data envelopment analysis Econometrics Production (economics) Business and International Management General Economics Econometrics and Finance Total factor productivity Parametric statistics |
| Zdroj: | Global Economic Review. 36:361-384 |
| ISSN: | 1744-3873 1226-508X |
| Popis: | There 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 pro... |
| Databáze: | OpenAIRE |
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