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.
Full text not available from this repository.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 |
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Language: | English |
Date: | January 2014 |
Refereed: | Yes |
Uncontrolled Keywords: | Ill-posed integral equation, Landweber iteration, IV quantile, Kernel smoothing |
JEL Classification: | 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: | TSE-R (Toulouse) |
Site: | UT1 |
Date Deposited: | 09 Jul 2014 17:45 |
Last Modified: | 02 Apr 2021 15:48 |
OAI Identifier: | oai:tse-fr.eu:28225 |
URI: | https://publications.ut-capitole.fr/id/eprint/15929 |