Modeling Income Distributions and Lorenz Curves

1. Front Matter

   Pages i-xiv

   PDF

2. Collection of influential papers

   1. A New Model of Personal Income Distribution: Specification and Estimation

      • Camilo Dagum

      Pages 3-25

   2. A Function for Size Distribution of Incomes

      • S. K. Singh, G. S. Maddala

      Pages 27-35

   3. Some Generalized Functions for the Size Distribution of Income

      • James B. McDonald

      Pages 37-55

   4. Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations

      • N. C. Kakwani, N. Podder

      Pages 57-70

   5. Distribution and Mobility of Wealth of Nations

      • Richard Paap, Herman K. van Dijk

      Pages 71-94

3. Survey papers on Lorenz functions and the generalizations and extensions of income distributions

   1. A Guide to the Dagum Distributions

      • Christian Kleiber

      Pages 97-117

   2. Pareto and Generalized Pareto Distributions

      • Barry C. Arnold

      Pages 119-145

   3. The Generalized Beta Distribution as a Model for the Distribution of Income: Estimation of Related Measures of Inequality

      • James B. McDonald, Michael Ransom

      Pages 147-166

   4. Parametric Lorenz Curves: Models and Applications

      • José María Sarabia

      Pages 167-190

4. Current research

   1. Maximum Entropy Estimation of Income Distributions from Bonferroni Indices

      • Hang Keun Ryu

      Pages 193-210

   2. New Four- and Five-Parameter Models for Income Distributions

      • William J. Reed, Fan Wu

      Pages 211-223

   3. Fuzzy Monetary Poverty Measures under a Dagum Income Distributive Hypothesis

      • Gianni Betti, Antonella D’Agostino, Achille Lemmi

      Pages 225-240

   4. Modelling Lorenz Curves: Robust and Semi-parametric Issues

      • Frank A. Cowell, Maria-Pia Victoria-Feser

      Pages 241-253

   5. Modelling Inequality with a Single Parameter

      • J. M. Henle, N. J. Horton, S. J. Jakus

      Pages 255-269

   6. Lorenz Curves and Generalised Entropy Inequality Measures

      • Nicholas Rohde

      Pages 271-283

   7. Estimating Income Distributions Using a Mixture of Gamma Densities

      • Duangkamon Chotikapanich, William E. Griffiths

      Pages 285-302

   8. Inequality in Multidimensional Indicators of Well-Being: Methodology and Application to the Human Development Index

      • Quentin Wodon, Shlomo Yitzhaki

      Pages 303-317

5. Back Matter

   Pages 319-322

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Jean-Jacques Rousseau wrote in the Preface to his famous Discourse on Inequality that “I consider the subject of the following discourse as one of the most interesting questions philosophy can propose, and unhappily for us, one of the most thorny that philosophers can have to solve. For how shall we know the source of inequality between men, if we do not begin by knowing mankind?” (Rousseau, 1754). This citation of Rousseau appears in an article in Spanish where Dagum (2001), in the memory of whom this book is published, also cites Socrates who said that the only useful knowledge is that which makes us better and Seneca who wrote that knowing what a straight line is, is not important if we do not know what rectitude is. These references are indeed a good illustration of Dagum’s vast knowledge, which was clearly not limited to the ?eld of Economics. For Camilo the ?rst part of Rousseau’s citation certainly justi?ed his interest in the ?eld of inequality which was at the centre of his scienti?c preoccupations. It should however be stressed that for Camilo the second part of the citation represented a “solid argument in favor of giving macroeconomic foundations to microeconomic behavior” (Dagum, 2001). More precisely, “individualism and methodological holism complete each other in contributing to the explanation of individual and social behavior” (Dagum, 2001).

• Gini coefficient
• Lorenz Curve
• development economics
• income distribution
• income inequality
• modeling

From the reviews:

“Chotikapanich has done an excellent job in her introduction to the volume of describing each paper’s content in a substantive way. … This is an excellent book and I recommend it strongly to anyone interested in this field and urge you to read it. … all these papers are interesting, all … were innovative and expanded our understanding of approximating and describing empirical income distribution data, and all illustrate an important lesson for (and particularly relevant to) the young researcher in this field … .”­­­ (Daniel Slottje, The Journal of Economic Inequality, Vol. 8, 2010)

• Department of Econometrics and Business Statistics, Monash University, Caulfield East, Australia

  Duangkamon Chotikapanich

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