  This paper focuses on the estimation of the concentration curve of a finite
population, when data are collected according to a complex sampling design with
different inclusion probabilities. A (design-based) Hajek type estimator for
the Lorenz curve is proposed, and its asymptotic properties are studied. Then,
a resampling scheme able to approximate the asymptotic law of the Lorenz curve
estimator is constructed. Applications are given to the construction of (i) a
confidence band for the Lorenz curve, (ii) confidence intervals for the Gini
concentration ratio, and (iii) a test for Lorenz dominance. The merits of the
proposed resampling procedure are evaluated through a simulation study.
