Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroscedasticity. (Comment by R.D.Banker, H.S.Chang, and W.W.Cooper)

DOI10.1016/S0377-2217(97)00101-XzbMath0970.90046MaRDI QIDQ1296012

Antonio N. Bojanic, Jon M. Ford, Steven B. Caudill

Publication date: 23 September 1999

Published in: European Journal of Operational Research (Search for Journal in Brave)

zbMATH Keywords

data envelopment analysisregressionstochastic frontier

Mathematics Subject Classification ID

Inference from stochastic processes (62M99) Operations research and management science (90B99)

Related Items (4)

A Monte Carlo study of old and new frontier methods for efficiency measurement ⋮ Comparative performance analysis of frontier-based efficiency measurement methods -- a Monte Carlo simulation ⋮ Dynamic firm performance and estimator choice: a comparison of dynamic panel data estimators ⋮ A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity.

Cites Work

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• A Monte Carlo study of estimators of stochastic frontier production functions
• Formulation and estimation of stochastic frontier production function models
• A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis
• Biases in frontier estimation due to heteroscedasticity
• Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
• Estimating the Efficiency of Production

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