QRPROCESS: stata module for quantile regression: fast algorithm, pointwise and uniform inference
Files
Code and help files
Date
2020-04-01
DOI
Authors
Fernandez-Val, Ivan
Chernozhukov, Victor
Melly, Blaise
Version
OA Version
First author draft
Citation
Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2020. "QRPROCESS: Stata module for quantile regression: fast algorithm, pointwise and uniform inference," Statistical Software Components S458763, Boston College Department of Economics.
Abstract
This package offers fast estimation and inference procedures for the linear quantile regression model. First, qrprocess implements new algorithms that are much quicker than the built-in Stata commands, especially when a large number of quantile regressions or bootstrap replications must be estimated. Second, the commands provide analytical estimates of the variance-covariance matrix of the coefficients for several quantile regressions allowing for weights, clustering and stratification. Third, in addition to traditional pointwise confidence intervals, this command also provides functional confidence bands and tests of functional hypotheses. Fourth, predict called after qrprocess can generate monotone estimates of the conditional quantile and distribution functions obtained by rearrangement. Fifth, the new command plotprocess conveniently plots the estimated coefficients with their confidence intervals and uniform bands.