Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative |
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Authors: | Joel L. Horowitz Sokbae Lee |
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Affiliation: | aDepartment of Economics, Northwestern University, Evanston, IL 60208-2600, USA;bDepartment of Economics, University College London, London, WC1E 6BT, United Kingdom |
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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. |
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Keywords: | Hypothesis test Quantile estimation Instrumental variables Specification testing Consistent testing |
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