# NOT RUN {
# Some data and estimation
data(trade)
est = fepois(Euros ~ log(dist_km) | Origin^Product + Year, trade)
#
# Coeftable/se/tstat/pvalue
#
# Default is clustering along Origin^Product
coeftable(est)
se(est)
tstat(est)
pvalue(est)
# Now with two-way clustered standard-errors
# and using ctable(), the alias to coeftable()
ctable(est, cluster = ~Origin + Product)
se(est, cluster = ~Origin + Product)
pvalue(est, cluster = ~Origin + Product)
tstat(est, cluster = ~Origin + Product)
# Or you can cluster only once:
est_sum = summary(est, cluster = ~Origin + Product)
ctable(est_sum)
se(est_sum)
tstat(est_sum)
pvalue(est_sum)
# You can use the arguments keep, drop, order
# to rearrange the results
base = iris
names(base) = c("y", "x1", "x2", "x3", "species")
est_iv = feols(y ~ x1 | x2 ~ x3, base)
tstat(est_iv, keep = "x1")
coeftable(est_iv, keep = "x1|Int")
coeftable(est_iv, order = "!Int")
# }
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