Nonparametric inference methods for probability weighted moments (PWM) are proposed. This approach extends the classical Empirical Likelihood (EL) technique. An asymptotic extension of a nonparametric version of Wilks theorem is derived. The novel EL nonparametric confidence interval estimation of the PWM is obtained. The proposed methodology is applied towards inference of the Gini index.