Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/300391 
Year of Publication: 
2024
Series/Report no.: 
cemmap working paper No. CWP06/24
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
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.
Subjects: 
Nonparametric procedure
Statistical error
Regression analysis
Estimation theory
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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