On relaxing the distributional assumption of stochastic frontier models

DOI10.1007/S42952-019-00011-1zbMath1485.62165OpenAlexW3009366935WikidataQ114687003 ScholiaQ114687003MaRDI QIDQ2131879

Hohsuk Noh, Ingrid Van Keilegom

Publication date: 27 April 2022

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/642905

zbMATH Keywords

measurement errorstochastic frontier modelsproductivity analysisfrontier functioninefficiency distribution

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Cites Work

• Estimation and testing for partially linear single-index models
• Nonparametric stochastic frontiers: a local maximum likelihood approach
• On the optimal rates of convergence for nonparametric deconvolution problems
• Estimation and testing in a partial linear regression model under long-memory dependence
• Efficiency measurement in the stochastic frontier model
• Properties of technical efficiency estimators in the stochastic frontier model
• Frontier estimation in the presence of measurement error with unknown variance
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
• Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error
• Semiparametric Stochastic Frontier Estimation via Profile Likelihood
• Efficiency Analysis: A Primer on Recent Advances
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