RobustSETutorial.R

## -------------------------------------- ##
## R Tutorial on Robust Standard Errors   ##
## Author: Tony Cookson                   ##
## -------------------------------------- ##

## Read Data
library(foreign)
ed = read.dta("C://R//edudat2.dta")

## Obtain regression object
educ.lm = lm(log(wage)~gender + educ + pareduc, data=ed)

## Summarize Output Assuming Homoskedasticity
summary(educ.lm)

## Need to load the car library
library(car)

## If you don't have car installed you'll need to install it
## Use this command:
## install.packages("car", dependencies = TRUE)
## Then, run the library command library(car)
## Robust Standard errors

summaryR(educ.lm)           ## Special Function written by John Fox

## Can Specify Type of Heteroskedasticity correction

summaryR(educ.lm, type="hc0")    ## White SE
summaryR(educ.lm, type="hc1")    ## Stata's Default
summaryR(educ.lm, type="hc2")    ## Unbiased under homoskedasticity
summaryR(educ.lm, type="hc3")    ## Default (conservative)

## Test using linearHypothesis

linearHypothesis(educ.lm, "educ+pareduc =1", white.adjust="hc3")
linearHypothesis(educ.lm, "educ+pareduc =1", white.adjust="hc0")