Quantile Regression with Classical Additive Measurement Errors
This note derives the bias of the quantile regression estimator in the presence of classical additive measurement error, and show its connection to least squares models. The bias structure suggests that the instrumental variables estimator proposed for least squares can be applied to the quantile regression case.
Volume (Year): 31 (2011)
Issue (Month): 4 ()
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