Iterative estimation of solutions to noisy nonlinear operator equations in nonparametric instrumental regression

Dunker, Fabian, Florens, Jean-Pierre, Hohage, Thorsten, Johannes, Jan and Mammen, Enno (2014) Iterative estimation of solutions to noisy nonlinear operator equations in nonparametric instrumental regression. Journal of Econometrics, vol. 178 (n° 3). pp. 444-455.

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Official URL: http://tse-fr.eu/pub/28225

Abstract

This paper discusses the solution of nonlinear integral equations with noisy integral kernels as they appear in nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence rate results. A particular emphasis is on instrumental regression models where the usual conditional mean assumption is replaced by a stronger independence assumption. We demonstrate for the case of a binary instrument that our approach allows the correct estimation of regression functions which are not identifiable with the standard model. This is illustrated in computed examples with simulated data.

Item Type: Article
Language: English
Date: January 2014
Refereed: Yes
Uncontrolled Keywords: Ill-posed integral equation, Landweber iteration, IV quantile, Kernel smoothing
JEL codes: C13 - Estimation
C14 - Semiparametric and Nonparametric Methods
C30 - General
C31 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Subjects: B- ECONOMIE ET FINANCE
Divisions: Toulouse School of Economics - TSE
Site: UT1
Date Deposited: 09 Jul 2014 17:45
Last Modified: 18 Oct 2017 15:12
OAI ID: oai:tse-fr.eu:28225
URI: http://publications.ut-capitole.fr/id/eprint/15929

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