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. Copyright 2007 The Review of Economic Studies Limited.
Authors
CPP Co-Director
Richard is Co-Director of the Centre for the Microeconomic Analysis of Public Policy (CPP) and Senior Research Fellow at IFS.
Northwestern University
Journal article details
- DOI
- 10.1111/j.1467-937X.2007.00458.x
- Publisher
- Oxford University Press
- Issue
- October 2007
Suggested citation
Blundell, R and Horowitz, J. (2007). 'A nonparametric test of exogeneity' (2007)
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