I am trying to replicate the results provided by the Stata command xtscc in R with package plm but I am having some trouble to see the same standard errors
I am using a dataset from the package plm also in Stata for replication purposes.
# code to obtain dataset
library(lmtest)
library(car)
library(tidyverse)
data("Produc", package="plm")
write.dta(Produc,"test.dta")
My aim is to run a two way-fixed effect panel model estimation with Driscoll and Kraay standard errors. The routine in Stata is the following
use "test.dta", clear \\ to import data
** i declare the panel
xtset state year
* create the dummies for the time fixed effects
quietly tab year, gen(yeardum)
* run a two way fixed effect regression model with Driscoll and Kraay standard errors
xi: xtscc gsp pcap emp unemp yeardum*,fe
* results are the following
Coef. Std. Err. t P>|t| [95% Conf. Interval]
pcap | -.1769881 .265713 -0.67 0.515 -.7402745 .3862983
emp | 40.61522 2.238392 18.14 0.000 35.87004 45.3604
unemp | 23.59849 85.10647 0.28 0.785 -156.8192 204.0161
In R I use the following routine:
# I declare the panel
Produc <- pdata.frame(Produc, index = c("state","year"), drop.index = FALSE)
# run a two way fixed effect model
femodel <- plm(gsp~pcap+emp+unemp, data=Produc,effect = "twoway",
index = c("iso3c","year"), model="within")
# compute Driscoll and Kraay standard errors using vcovSCC
coeftest(femodel, vcovSCC(femodel))
pcap -0.17699 0.25476 -0.6947 0.4874
emp 40.61522 2.14610 18.9252 <2e-16 ***
unemp 23.59849 81.59730 0.2892 0.7725
While point estimates are the same that in Stata, standard errors are different.
To check whether I am using the "wrong" small sample adjustment for standard errors, I also tryed running the coeftest with all available adjustments, but none yields the same values as xtscc.
library(purrr)
results <- map(c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),~coeftest(femodel, vcovSCC(femodel,type = .x)))
walk(results,print)
# none of the estimated standard errors is the same as xtscc
Does anyone know how I can replicate the results of Stata in R?
Since plm version 2.4, its function within_intercept(., return.model = TRUE) can return the full model of a within model with the intercept as in Stata. With this, it is possible to exactly replicate the result of Stata's user contributed command xtscc.
The way xtscc seems to work is by estimating the twoway FE model as a one-way FE model + dummies for the time dimension. So let's replicate that with plm:
data("Produc", package="plm")
Produc <- pdata.frame(Produc, index = c("state","year"), drop.index = FALSE)
femodel <- plm(gsp ~ pcap + emp + unemp + factor(year), data = Produc, model="within")
femodelint <- within_intercept(femodel, return.model = TRUE)
lmtest::coeftest(femodelint, vcov. = function(x) vcovSCC(x, type = "sss"))
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -6547.68816 3427.47163 -1.9104 0.0564466 .
# pcap -0.17699 0.26571 -0.6661 0.5055481
# emp 40.61522 2.23839 18.1448 < 0.00000000000000022 ***
# unemp 23.59849 85.10647 0.2773 0.7816356
# [...]