Abstract
The asymptotic distribution of the extreme regression quantile in the linear regression model is derived under exponentially tailed density of errors and under mild conditions on the regressors. The asymptotic distribution of the intercept component differs from that of the sample extreme in the i.i.d. case only in that it involves the hat matrix of the regressors.
The rate of consistency is in accord with the maximal domain of attraction of the errors.