A non-parametric test of exogeneity

Richard Blundell*, Joel L. Horowitz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

This paper presents a test for exogeneity of explanatory variables that minimizes the need for auxiliary assumptions that are not required by the definition of exogeneity. It concerns inference about a non-parametric function g that is identified by a conditional moment restriction involving instrumental variables (IV). A test of the hypothesis that g is the mean of a random variable Y conditional on a covariate X is developed that is not subject to the ill-posed inverse problem of non-parametric IV estimation. The test is consistent whenever g differs from E (Y X) on a set of non-zero probability. The usefulness of this new exogeneity test is displayed through Monte Carlo experiments and an application to estimation of non-parametric consumer expansion paths.

Original languageEnglish (US)
Pages (from-to)1035-1058
Number of pages24
JournalReview of Economic Studies
Volume74
Issue number4
DOIs
StatePublished - Oct 2007

Funding

Acknowledgements. We thank Xiaohong Chen, James J. Heckman, the editor, and two anonymous referees for comments. Part of this research was carried out while Joel Horowitz was a visitor at the Centre for Microdata Methods and Practice, University College London and Institute for Fiscal Studies. Horowitz’s research was also supported in part by NSF Grant SES 0352675. Richard Blundell thanks the ESRC Centre for the Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies for financial support.

ASJC Scopus subject areas

  • Economics and Econometrics

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