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Bayesian Bootstrap of the Quantile Regression Estimator: A Large Sample Study

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Author Info
Hahn, Jinyong
Abstract

The large sample property of the Bayesian bootstrap distribution of the quantile regression estimator is investigated. When the pair of dependent and independent variables are resampled, the Bayesian bootstrap is shown to converge weakly in probability to the limiting distribution of the quantile regression estimator. The Bayesian bootstrap thus has the same asymptotic distribution as the Frequentist bootstrap. In addition, the median of the Bayesian bootstrap distribution has the same asymptotic distribution as the quantile regression estimator. Copyright 1997 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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Publisher Info
Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 38 (1997)
Issue (Month): 4 (November)
Pages: 795-808
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Handle: RePEc:ier:iecrev:v:38:y:1997:i:4:p:795-808

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  1. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics. [Downloadable!]
  2. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society. [Downloadable!]
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