Semiparametric maximum likelihood estimation of stochastic frontier model with errors-in-variables

DOI10.1016/j.jkss.2015.09.006zbMath1381.62059OpenAlexW2111098210MaRDI QIDQ287396

Byungtae Seo, Seok-Oh Jeong

Publication date: 26 May 2016

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

Full work available at URL: https://doi.org/10.1016/j.jkss.2015.09.006

zbMATH Keywords

measurement errorerrors-in-variablesmixture modelconstrained Newton methodproductivity analysissemiparametric maximum likelihood estimationstochastic frontier model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric estimation (62G05)

Cites Work

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• Asymptotic distribution of conical-hull estimators of directional edges
• The geometry of mixture likelihoods: A general theory
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• A Semiparametric Mixture Approach to Case-Control Studies With Errors in Covariables
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• An Algorithm for Computing the Nonparametric MLE of a Mixing Distribution
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
• Stochastic Frontier Analysis
• A universally consistent modification of maximum likelihood
• A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem
• On Fast Computation of the Non-Parametric Maximum Likelihood Estimate of a Mixing Distribution
• Nonparametric multivariate density estimation using mixtures

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