A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity.
From MaRDI portal
Publication:1420389
DOI10.1016/S0377-2217(02)00699-9zbMath1099.90534OpenAlexW1983161011MaRDI QIDQ1420389
Rajiv D. Banker, Hsihui Chang, William W. Cooper
Publication date: 2 February 2004
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0377-2217(02)00699-9
Applications of statistics to actuarial sciences and financial mathematics (62P05) Management decision making, including multiple objectives (90B50) Production models (90B30)
Related Items (4)
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 ⋮ DEA-based hypothesis tests for comparing two groups of decision making units ⋮ Contributions of Professor William W. Cooper in operations research and management science
Cites Work
- Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
- A Monte Carlo study of estimators of stochastic frontier production functions
- Maximum likelihood estimation of econometric frontier functions
- A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis
- 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)
- Simulation studies of efficiency, returns to scale and misspecification with nonlinear functions in DEA
- Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
- Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
- Estimating the Efficiency of Production
This page was built for publication: A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity.
