A consistent nonparametric bootstrap test of exogeneity

Jinhyun Lee

    Research output: Working paper

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    This paper proposes a novel way of testing exogeneity of an explanatory variable without any parametric assumptions in the presence of a "conditional" instrumental variable. A testable implication is derived that if an explanatory variable is endogenous, the conditional distribution of the outcome given the endogenous variable is not independent of its instrumental variable(s). The test rejects the null hypothesis with probability one if the explanatory variable is endogenous and it detects alternatives converging to the null at a rate n^{-1/2}. We propose a consistent nonparametric bootstrap test to implement this testable implication. We show that the proposed bootstrap test can be asymptotically justified in the sense that it produces asymptotically correct size under the null of exogeneity, and it has unit power asymptotically. Our nonparametric test can be applied to the cases in which the outcome is generated by an additively non-separable structural relation or in which the outcome is discrete, which has not been studied in the literature.
    Original languageEnglish
    PublisherUniversity of St Andrews
    Number of pages37
    Publication statusPublished - Sept 2013

    Publication series

    NameSchool of Economics & Finance Discussion Paper 1316
    PublisherUniversity of St. Andrews
    ISSN (Print)0962-4031
    ISSN (Electronic)2055-303X


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