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Parameter approximations for quantile regressions with measurement error

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  • Andrew Chesher

    ()
    (Institute for Fiscal Studies and University College London)

Abstract

The impact of covariate measurement error on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related, a key factor being the distribution of the error free covariate. Exact calculations probe the accuracy of the approximation. The order of the approxiamtion error is unchanged if the error free covariate density is replaced by the error contaminated density. It is then possible to use the approximation to investigate the sensitivity of estimates to varying amounts of measurement error.

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File URL: http://cemmap.ifs.org.uk/wps/cwp0102.pdf
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Bibliographic Info

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP02/01.

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Length: 30 pp.
Date of creation: Jul 2001
Date of revision:
Handle: RePEc:ifs:cemmap:02/01

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Cited by:
  1. Gabriel Montes-Rojas, 2011. "Quantile Regression with Classical Additive Measurement Errors," Economics Bulletin, AccessEcon, vol. 31(4), pages 2863-2868.
  2. Yingyao Hu & Susanne Schennach, 2006. "Identification and estimation of nonclassical nonlinear errors-in-variables models with continuous distributions using instruments," CeMMAP working papers CWP17/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Eren, Ozkan & Ozbeklik, Serkan, 2013. "The effect of noncognitive ability on the earnings of young men: A distributional analysis with measurement error correction," Labour Economics, Elsevier, vol. 24(C), pages 293-304.
  4. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, 01.
  5. Schmidt, Christoph M. & Tauchmann, Harald, 2011. "Heterogeneity in the intergenerational transmission of alcohol consumption: A quantile regression approach," Journal of Health Economics, Elsevier, vol. 30(1), pages 33-42, January.

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