Combining DEA and stochastic frontier models: an empirical Bayes approach.

DOI10.1016/S0377-2217(02)00248-5zbMath1037.90549OpenAlexW2010364288MaRDI QIDQ1873000

Efthymios G. Tsionas

Publication date: 19 May 2003

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)00248-5

zbMATH Keywords

Bayesian analysisData envelopment analysisEmpirical Bayes proceduresApplied probabilityEfficiency measurementStochastic frontier model

Mathematics Subject Classification ID

Stochastic programming (90C15) Management decision making, including multiple objectives (90B50) Stochastic models in economics (91B70) Special problems of linear programming (transportation, multi-index, data envelopment analysis, etc.) (90C08)

Related Items (10)

Estimating output targets to evaluate output-specific efficiencies: A statistical framework ⋮ On a high-dimensional model representation method based on copulas ⋮ Minimax regret priors for efficiency estimation ⋮ On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process ⋮ Optimal combinations of stochastic frontier and data envelopment analysis models ⋮ Profitability analysis using IDEA-DA framework ⋮ Globally flexible functional forms: the neural distance function ⋮ Combining data envelopment analysis and stochastic frontiers via a LASSO prior ⋮ Performance estimation when the distribution of inefficiency is unknown ⋮ A coherent approach to Bayesian data envelopment analysis

Uses Software

• DEAP

Cites Work

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• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error

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