I have heteroscedastic and autocorrelated residuals in my multivariate quantile regression model.
What's the quantile regression standard error estimator that's robust to this? Something hopefully like HAC Newey West but for quantile regression, or perhaps a bootstrap.
Best Answer
You're definitely going to want to bootstrap. Have you looked at the R package "quantreg"?
http://cran.r-project.org/web/packages/quantreg/quantreg.pdf
There's a function, boot.rq, for bootstrapping a standard quantile regression. For B bootstrap replications, the function gives you B estimates for each parameter. The standard error for each parameter estimate is just the standard deviation of the B estimates.