Arbeitspapier

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

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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.

Language
Englisch

Bibliographic citation
Series: Discussion Papers ; No. 192

Classification
Wirtschaft
Estimation: General
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Instrumental Variables (IV) Estimation
Subject
nonparametric regression
instrumental variables
nonlinear inverse problems
iterative regularization

Event
Geistige Schöpfung
(who)
Dunker, Fabian
Event
Veröffentlichung
(who)
Georg-August-Universität Göttingen, Courant Research Centre - Poverty, Equity and Growth (CRC-PEG)
(where)
Göttingen
(when)
2015

Handle
Last update
10.03.2025, 11:43 AM CET

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Object type

  • Arbeitspapier

Associated

  • Dunker, Fabian
  • Georg-August-Universität Göttingen, Courant Research Centre - Poverty, Equity and Growth (CRC-PEG)

Time of origin

  • 2015

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