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Bootstrapping Quantile Regression Estimators Author info | Abstract | Publisher info | Download info | Related research | Statistics Hahn, Jinyong
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.
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Article provided by Cambridge University Press in its journal Econometric Theory .
Volume (Year): 11 (1995)
Issue (Month): 01 (February)
Pages: 105-121
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Handle: RePEc:cup:etheor:v:11:y:1995:i:01:p:105-121_00Contact details of provider: Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK Fax: +44 (0)1223 325150 Email: Web page: http://journals.cambridge.org/jid_ECT
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