Arbeitspapier

Nonparametric instrumental variables estimation of a quantile regression model

We consider nonparametric estimation of a regression function that is identified by requiring a specified quantile of the regression error conditional on an instrumental variable to be zero. The resulting estimating equation is a nonlinear integral equation of the first kind, which generates an ill-posed-inverse problem. The integral operator and distribution of the instrumental variable are unknown and must be estimated nonparametrically. We show that the estimator is mean-square consistent, derive its rate of convergence in probability, and give conditions under which this rate is optimal in a minimax sense. The results of Monte Carlo experiments show that the estimator behaves well in finite samples.

Language
Englisch

Bibliographic citation
Series: cemmap working paper ; No. CWP09/06

Classification
Wirtschaft
Estimation: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Subject
Statistical inverse , endogenous variable , instrumental variable , optimal rate , nonlinear integral equation , nonparametric regression

Event
Geistige Schöpfung
(who)
Horowitz, Joel
Lee, Sokbae
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2006

DOI
doi:10.1920/wp.cem.2006.0906
Handle
Last update
20.09.2024, 8:22 AM CEST

Data provider

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Object type

  • Arbeitspapier

Associated

  • Horowitz, Joel
  • Lee, Sokbae
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2006

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