Efficient semiparametric seemingly unrelated quantile regression estimation

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We propose an efficient semiparametric estimator for the coefficients of a multivariate linear regression modelwith a conditional quantile restriction for each equationin which the conditional distributions of errors given regressors are unknown. The procedure can be used to estimate multiple conditional quantiles of the same regression relationship. The proposed estimator is asymptotically as efficient as if the true optimal instruments were known. Simulation results suggest that the estimation procedure works well in practice and dominates an equation-by-equation efficiency correction if the errors are dependent conditional on the regressors.

Original languageEnglish (US)
Pages (from-to)1392-1414
Number of pages23
JournalEconometric Theory
Issue number5
StatePublished - Oct 2009

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Economics and Econometrics


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