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Author (up) Banker, R.D.; Chang, H.; Cooper, W.W. doi  openurl
  Title A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity Type
  Year 2004 Publication European Journal of Operational Research Abbreviated Journal  
  Volume 153 Issue 3 Pages 624-640  
  Keywords Production function; Inefficiency estimators; Heteroscedasticity; Simulation study  
  Abstract This paper studies the effects of heteroscedasticity on the following five types of estimators: (1) Data Envelopment Analysis (DEA) per se as well as DEA joined to regression forms, (2) Corrected Ordinary Least Squares based on maximum residual (COLS-R), (3) Corrected Ordinary Least Squares based on moments of residuals (COLS-M), (4) Maximum Likelihood Estimation (MLE), and (5) Goal Programming with one-sided deviations as in Aigner and Chu (AandC). This is accomplished with simulated data in an experiment designed around a single output-single input production function which is piecewise Cobb-Douglas. Robustness of results is confirmed with another experiment employing a shifted smooth Cobb-Douglas production function. The model has a composed error term consisting of two components – one for measurement error and the other for inefficiency. The simulation results indicate that heteroscedasticity does not have an adverse impact on DEA-based estimators and that DEA-based estimators are the best estimators of efficient output even under heteroscedasticity.  
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  Notes Approved  
  Call Number Admin @ admin @ BankerChangCooper2004 Serial 2520  
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