Modeling Income Distributions and Lorenz Curves

The parameterization of income distributions and Lorenz Curves is a useful approach for representing how income is distributed within a given population. It provides a way of describing how the data are generated, why the level of inequality is what it is, and what happens to the poorer sections of...

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Bibliographic Details
Other Authors: Chotikapanich, Duangkamon (Editor)
Format: eBook
Published: New York, NY Springer New York 2008, 2008
Edition:1st ed. 2008
Series:Economic Studies in Inequality, Social Exclusion and Well-Being
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Collection of influential papers
  • A New Model of Personal Income Distribution: Specification and Estimation
  • A Function for Size Distribution of Incomes
  • Some Generalized Functions for the Size Distribution of Income
  • Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations
  • Distribution and Mobility of Wealth of Nations
  • Survey papers on Lorenz functions and the generalizations and extensions of income distributions
  • A Guide to the Dagum Distributions
  • Pareto and Generalized Pareto Distributions
  • The Generalized Beta Distribution as a Model for the Distribution of Income: Estimation of Related Measures of Inequality
  • Parametric Lorenz Curves: Models and Applications
  • Current research
  • Maximum Entropy Estimation of Income Distributions from Bonferroni Indices
  • New Four- and Five-Parameter Models for Income Distributions
  • Fuzzy Monetary Poverty Measures under a Dagum Income Distributive Hypothesis
  • Modelling Lorenz Curves: Robust and Semi-parametric Issues
  • Modelling Inequality with a Single Parameter
  • Lorenz Curves and Generalised Entropy Inequality Measures
  • Estimating Income Distributions Using a Mixture of Gamma Densities
  • Inequality in Multidimensional Indicators of Well-Being: Methodology and Application to the Human Development Index