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A Test for Endogeneity in Conditional Quantiles

  • Tae-Hwan Kim


    (School of Economics, Yonsei University - Yonsei University)

  • Christophe Muller


    (AMSE - Aix-Marseille School of Economics - EHESS - École des hautes études en sciences sociales - Centre national de la recherche scientifique (CNRS) - Ecole Centrale Marseille (ECM) - AMU - Aix-Marseille Université)

In this paper, we develop a test to detect the presence of endogeneity in conditional quantiles. Our test is a Hausman-type test based on the distance between two estimators, of which one is consistent only under no endogeneity while the other is consistent regardless of the presence of endogeneity in conditional quantile models. We derive the asymptotic distribution of the test statistic under the null hypothesis of no endogeneity. The finite sample properties of the test are investigated through Monte Carlo simulations, and it is found that the test shows good size and power properties in finite samples. As opposed to the test based on the IVQR estimator of Chernozhukov and Hansen (2006) in the case of more than a couple of variables, our approach does not imply an infeasible computation time. Finally, we apply our approach to test for endogeneity in conditional quantile models for estimating Engel curves using UK consumption and expenditure data. The pattern of endogeneity in the Engel curve is found to vary substantially across quantiles

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Paper provided by HAL in its series Working Papers with number halshs-00854527.

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Date of creation: Aug 2013
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Handle: RePEc:hal:wpaper:halshs-00854527
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  12. Tae-Hwan Kim, & Christophe Muller, 2012. "Bias Transmission and Variance Reduction in Two-Stage Quantile Regression," AMSE Working Papers 1221, Aix-Marseille School of Economics, Marseille, France.
  13. Alberto Abadie & Joshua Angrist & Guido Imbens, 1999. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Working papers 99-16, Massachusetts Institute of Technology (MIT), Department of Economics.
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  16. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
  17. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2009. "The Taylor Principle and Monetary Policy Approaching a Zero Bound on Nominal Rates: Quantile Regression Results for the United States and Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1705-1723, December.
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