  In this paper we tackle the problem of estimating the power-law tail exponent
of income distributions by using the Hill's estimator. A subsample
semi-parametric bootstrap procedure minimising the mean squared error is used
to choose the power-law cutoff value optimally. This technique is applied to
personal income data for Australia and Italy.
