Neural Network Based Models For Efficiency Frontier Analysis: An Application To East Asian Economies~ Growth Decomposition

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 functions. 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 ANNs' ability to assess the performance of production units.