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Regression quantiles with errors-in-variables


  • Ioannides, D. A.
  • Matzner-Lober, E.


In a lot of situations, variables are measured with errors. While this problem has been previously studied in the kontext of kernel regression, no work has been done in quantile regression. To estimate this function we use deconvoluting kernel estimators. The asymptotic behaviour of these estimators depends on the smoothness of the noise distribution.

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  • Ioannides, D. A. & Matzner-Lober, E., 2003. "Regression quantiles with errors-in-variables," SFB 373 Discussion Papers 2003,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:200332

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    1. Bishop, John A & Formby, John P & Thistle, Paul D, 1992. "Convergence of the South and Non-South Income Distributions, 1969-1979," American Economic Review, American Economic Association, vol. 82(1), pages 262-272, March.
    2. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    3. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-1193, September.
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