The Gini coefficient is the most widely used measure of income inequality.
Yet, estimates on its standard error are rarely published because the cost
of computing it is prohibitively expensive. We present a method to compute
the jackknife variance estimator of the Gini coefficient which is very effi
cient. The standard error may be computed with the second pass through the
data.