You may use plm::vcovHC.plm
which is implemented in the plm:::summary.plm()
method. Use specific options method=
and type=
. Example:
library(plm)
data("Produc", package="plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
data=Produc, index=c("state", "year"), method="within", effect="twoways")
## normal SE
summary(zz)$coe
# Estimate Std. Error t-value Pr(>|t|)
# log(pcap) -0.030176057 0.026936544 -1.120265 2.629606e-01
# log(pc) 0.168828035 0.027656339 6.104497 1.655450e-09
# log(emp) 0.769306196 0.028141794 27.336786 1.275556e-114
# unemp -0.004221093 0.001138837 -3.706493 2.256597e-04
## heteroscedasticity-robust SE
summary(zz, vcov=vcovHC(zz, method="white1", type="HC1"))$coe
# Estimate Std. Error t-value Pr(>|t|)
# log(pcap) -0.030176057 0.029880301 -1.009898 3.128707e-01
# log(pc) 0.168828035 0.038079746 4.433539 1.065916e-05
# log(emp) 0.769306196 0.038808010 19.823387 1.301129e-70
# unemp -0.004221093 0.001357489 -3.109486 1.945209e-03
Read ?vcovHC.plm
for further information on method=
and type=
.