Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative

Joel L Horowitz*, Sokbae Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This paper is concerned with inference about a function g that is identified by a conditional quantile restriction involving instrumental variables. The paper presents a test of the hypothesis that g belongs to a finite-dimensional parametric family against a nonparametric alternative. The test is not subject to the ill-posed inverse problem of nonparametric instrumental variable estimation. Under mild conditions, the test is consistent against any alternative model. In large samples, its power is arbitrarily close to 1 uniformly over a class of alternatives whose distance from the null hypothesis is proportional to n- 1 / 2, where n is the sample size. Monte Carlo simulations illustrate the finite-sample performance of the test.

Original languageEnglish (US)
Pages (from-to)141-152
Number of pages12
JournalJournal of Econometrics
Volume152
Issue number2
DOIs
StatePublished - Oct 1 2009

Keywords

  • Consistent testing
  • Hypothesis test
  • Instrumental variables
  • Quantile estimation
  • Specification testing

ASJC Scopus subject areas

  • Economics and Econometrics
  • Applied Mathematics
  • History and Philosophy of Science

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