Nonparametric identification and estimation with non-classical errors-in-variables

This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and easy-to-interpret conditions on the instrumental variable. The paper also provides nonparametric estimators of the regression function and derives their rates of convergence.

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Year of publication:	2024
Authors:	Evdokimov, Kirill S. ; Zeleneev, Andrei
Publisher:	London : Centre for Microdata Methods and Practice (cemmap)
Subject:	Nichtparametrisches Verfahren \| Statistischer Fehler \| Regressionsanalyse \| Schätztheorie \| Nonparametric procedure \| Statistical error \| Regression analysis \| Estimation theory

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Series:	cemmap working paper ; CWP06/24
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.47004/wp.cem.2024.0624 [DOI] 1885797273 [GVK]
Source:	EconStor

Persistent link: https://www.econbiz.de/10014581847