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.

Sprache
Englisch

Erschienen in
Series: Discussion Papers ; No. 192

Klassifikation
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
Thema
nonparametric regression
instrumental variables
nonlinear inverse problems
iterative regularization

Ereignis
Geistige Schöpfung
(wer)
Dunker, Fabian
Ereignis
Veröffentlichung
(wer)
Georg-August-Universität Göttingen, Courant Research Centre - Poverty, Equity and Growth (CRC-PEG)
(wo)
Göttingen
(wann)
2015

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

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Objekttyp

  • Arbeitspapier

Beteiligte

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

Entstanden

  • 2015

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