Generalized Lambda Distributions of Household‘s Incomes

A new approach to statistical modelling with inverse distribution functions, known as quantile functions, provides further opportunities for describing the probability distributions. Two general theoretically elaborated types of the quantile modelling are to fit the data by a known highly elastic generalized form and to build up an adequate quantile model for a special case. The aim of this article is to present the first approach to statistical modelling of probability distributions with help of the generalized lambda distributions (GLD). A technique of identification, estimation and validation of quantile probability models from family of RS GLD is discussed. Quantile modelling of income distribution is applied using a data sample of yearly net real income, collected from 1566 households in Households‘ Budgets Survey of Statistical Office of Slovak Republic. Some conclusions about application of about mentioned methods in case of heavy-tailed or long-tailed continuous probability distributions will hopefully contribute to the development of generalized quantile model fitting.