Frontier estimation in the presence of measurement error with unknown variance
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Publication:2343753
DOI10.1016/j.jeconom.2014.09.012zbMath1331.62478OpenAlexW1972238797MaRDI QIDQ2343753
Alois Kneip, Léopold Simar, Ingrid Van Keilegom
Publication date: 6 May 2015
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://lirias.kuleuven.be/handle/123456789/569712
Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Statistical methods; economic indices and measures (91B82)
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Cites Work
- Unnamed Item
- Unnamed Item
- Semi-Nonparametric Maximum Likelihood Estimation
- ASYMPTOTICS AND CONSISTENT BOOTSTRAPS FOR DEA ESTIMATORS IN NONPARAMETRIC FRONTIER MODELS
- Nonparametric stochastic frontiers: a local maximum likelihood approach
- Frontier estimation and extreme value theory
- Consistent density deconvolution under partially known error distribution
- Data-driven boundary estimation in deconvolution problems
- Asymptotic distribution of conical-hull estimators of directional edges
- Likelihood functions for generalized stochastic frontier estimation
- The tail of the convolution of densities and its application to a model of HIV-latency time
- Formulation and estimation of stochastic frontier production function models
- Convergence rate of sieve estimates
- On methods of sieves and penalization
- Estimating the endpoint of a distribution in the presence of additive observation errors
- Minimax estimation of the noise level and of the deconvolution density in a semiparametric convolution model
- Efficient estimation of monotone boundaries
- Adaptivity in convolution models with partially known noise distribution
- Deconvolving compactly supported densities
- THE FDH ESTIMATOR FOR PRODUCTIVITY EFFICIENCY SCORES
- Support estimation via moment estimation in presence of noise
- Identification and Estimation of Regression Models with Misclassification
- Large Sample Approximation of the Distribution for Convex-Hull Estimators of Boundaries
- Estimating the Upper Support Point in Deconvolution
- Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
- Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
- Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error
- On Estimation of Monotone and Concave Frontier Functions
- Instrumental Variable Treatment of Nonclassical Measurement Error Models