In this article, we estimate the shape and scale parameters, Lorenz curve and Gini-index for the power function distribution using quasi-likelihood and quasi-Bayesian methods. Quasi-Bayes estimators have been developed under squared error loss function as well as under LINEX loss function. We demonstrate the use of the proposed estimation procedure with the U. S. income data for the period 1913-2010. Our proposed quasi-likelihood and quasi-Bayesian estimators are compared with the ML estimators proposed by Belzunce et al. (1998).