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Bootstrapping Quantile Regression Estimators

Published online by Cambridge University Press:  11 February 2009

Jinyong Hahn
Jinyong Hahn
Affiliation:
University of Pennsylvania
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Abstract

The asymptotic variance matrix of the quantile regression estimator depends on the density of the error. For both deterministic and random regressors, the bootstrap distribution is shown to converge weakly to the limit distribution of the quantile regression estimator in probability. Thus, the confidence intervals constructed by the bootstrap percentile method have asymptotically correct coverage probabilities.

Type
Articles
Information
Econometric Theory , Volume 11 , Issue 1 , February 1995 , pp. 105 - 121
Copyright
Copyright © Cambridge University Press 1995

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References

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