Closed-form estimation of nonparametric models with non-classical measurement errors

DOI10.1016/j.jeconom.2014.11.004zbMath1331.62231OpenAlexW2171354914MaRDI QIDQ2343817

Yuya Sasaki, Yingyao Hu

Publication date: 6 May 2015

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2014.11.004

zbMATH Keywords

closed formnonparametric regressionsnon-classical measurement errors

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (11)

The econometrics of unobservables: applications of measurement error models in empirical industrial organization and labor economics ⋮ Nonparametric estimation of additive models with errors-in-variables ⋮ IDENTIFICATION OF PAIRED NONSEPARABLE MEASUREMENT ERROR MODELS ⋮ CLOSED-FORM IDENTIFICATION OF DYNAMIC DISCRETE CHOICE MODELS WITH PROXIES FOR UNOBSERVED STATE VARIABLES ⋮ A generalization of Lemma 1 in Kotlarski (1967) ⋮ On the identification of joint distributions using marginals and aggregates ⋮ Uniform confidence bands for nonparametric errors-in-variables regression ⋮ IDENTIFICATION OF LINEAR REGRESSIONS WITH ERRORS IN ALL VARIABLES ⋮ Measurement errors in quantile regression models ⋮ Inference on distribution functions under measurement error ⋮ Inference on local average treatment effects for misclassified treatment

Cites Work

• Identification and estimation of nonlinear models with misclassification error using instrumental variables: a general solution
• Nonparametric regression with errors in variables
• Robust and consistent estimation of nonlinear errors-in-variables models
• Identification and Estimation of Regression Models with Misclassification
• NONPARAMETRIC REGRESSION IN THE PRESENCE OF MEASUREMENT ERROR
• Estimation of Average Treatment Effects with Misclassification
• Instrumental Variable Treatment of Nonclassical Measurement Error Models
• Estimation of Nonlinear Models with Measurement Error
• Measurement Error in Nonlinear Models
• Measurement Error Models with Auxiliary Data
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