Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096142 | Journal of Econometrics | 2014 | 46 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Fabian Dunker, Jean-Pierre Florens, Thorsten Hohage, Jan Johannes, Enno Mammen,