Convergence of the risk for nonparametric IV quantile regression and nonparametric IV regression with full independence

Fabian Dunker
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引用次数: 3

Abstract

In econometrics some nonparametric instrumental regression models and nonparametric demand models with endogeneity lead to nonlinear integral equations with unknown integral kernels. We prove convergence rates of the risk for the iteratively regularized Newton method applied to these problems. Compared to related results we relay on a weaker non-linearity condition and have stronger convergence results. We demonstrate by numerical simulations for a nonparametric IV regression problem with continuous instrument and regressor that the method produces better results than the standard method.
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非参数IV分位数回归和完全独立的非参数IV回归风险的收敛性
在计量经济学中,一些具有内生性的非参数工具回归模型和非参数需求模型会导致具有未知积分核的非线性积分方程。我们证明了迭代正则牛顿法在这些问题上的收敛速度。与相关结果相比,我们所依赖的非线性条件较弱,收敛性较强。通过对具有连续仪器和回归器的非参数IV回归问题的数值模拟,证明了该方法比标准方法产生更好的结果。
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