Title: Quantiles and inequality indices estimation from heavy-tailed distribution
Authors: Emmanuel Flachaire - Aix-Marseille University (France) [presenting]
Arthur Charpentier - University of Rennes 1 (France)
Abstract: Quantiles and inequality indices are estimated from a nonparametric density estimation based on transformed data. A parametric cumulative distribution function is initially used to transform the data into values over the unit interval, from which a non-parametric density estimation is obtained. Finally, an estimation of the density of the original sample is obtained by back-transformation. This approach may be particularly useful to estimate heavy-tailed distributions. We discuss its implementation and its finite sample properties for density estimation, and for estimation and inference with quantiles and inequality indices.