The wild cluster bootstrap provides another new option for robust inference when researchers have data with a few clusters, an uneven number of observations across clusters, or both.
The new wildbootstrap command computes wild cluster bootstrap p-values and confidence intervals for tests of simple and composite linear hypotheses about parameters from linear regression models. You can type
. wildbootstrap regress y x1 x2 …
or
. wildbootstrap areg y x1 x2 …, absorb(x3)
or
. xtset id
. wildbootstrap xtreg y x1 x2 …
to fit a linear regression model, a linear regression model with a large dummy-variable set, or a fixed-effects linear regression model for panel data, respectively, and to obtain the wild cluster bootstrap statistics.