Econometrica Vol. 75 No. 1 2007
Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models
Abstract
This paper establishes that instruments enable the identification of nonparametric regression models in the presence of measurement error by providing a closed form solution for the regression function in terms of Fourier transforms of conditional expectations of observable variables. For parametrically specified regression functions, we propose a root n consistent and asymptotically normal estimator that takes the familiar form of a generalized method of moments estimator with a plugged-in nonparametric kernel density estimate. Both the identification and the estimation methodologies rely on Fourier analysis and on the theory of generalized functions. The finite-sample properties of the estimator are investigated through Monte Carlo simulations.
- DOI
- 10.1111/j.1468-0262.2007.00736.x
- Volume
- 75
- Issue
- 1
- Pages
- 201-239
- Language
- en
- Sources
- bibtex:phds-export.bib openalex crossref