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).

​This book presents a rigorous treatment of the mathematical instruments available for dealing with income distributions, in particular Lorenz curves and related methods. The methods examined allow us to analyze, compare and modify such distributions from an economic and social perspective. Though balanced income distributions are key to peaceful coexistence within and between nations, it is often difficult to identify the right kind of balance needed, because there is an interesting interaction with innovation and economic growth. The issue of justice, as discussed in Thomas Piketty’s bestseller “Capital in the Twenty-First Century” or in the important book “The Price of Inequality” by Nobel laureate Joseph Stiglitz, is also touched on. Further, there is a close connection to the issue of democracy in the context of globalization. One highlight of the book is its rigorous treatment of the so-called Atkinson theorem and some extensions, which help to explain under which type of societal utility functions nations tend to operate either in the direction of more balance or less balance. Finally, there are some completely new insights into changing the balance pattern of societies and the kind of coalitions between richer and poorer parts of society to organize political support in democracies in either case. Oxford University's Sir Tony Atkinson, well known for his so-called Atkinson theorem, writes in his foreword to the book: “[The authors] contribute directly to t he recent debates that are going on in politics. [...] with this book the foundation of arguments concerning a proper balance in income distribution in the sense of identifying an ‘efficient inequality range’ has got an additional push from mathematics, which I appreciate very much.”

Distribution Models Theory is a revised edition of papers specially selected by the Scientific Committee for the Fifth Workshop of Spanish Scientific Association of Applied Economy on Distribution Models Theory held in Granada (Spain) in September 2005. The contributions offer a must-have point of reference on models theory. This book has been selected for coverage in: . OCo Index to Scientific & Technical Proceedings- (ISTP-/ISI Proceedings). OCo Index to Scientific & Technical Proceedings (ISTP CDROM version/ISI Proceedings). Sample Chapter(s). Chapter 1: Modeling Income Distributions Using Elevated Distributions on a Bounded Domain (313 KB). Contents: Modeling Income Distributions Using Elevated Distributions on a Bounded Domain; Making Copulas Under Uncertainty; Valuation Method of the Two Survival Functions; Weighting Tools and Alternative Techniques to Generate Weighted Probability Models in Valuation Theory; On Generating and Characterizing Some Discrete and Continuous Distributions; Some Stochastic Properties in Sampling from the Normal Distribution; Generating Function and Polarization; A New Measure of Dissimilarity Between Distributions: Application to the Analysis of Income Distributions Convergence in the European Union; Using the Gamma Distribution to Fit Fecundity Curves for Application in Andalusia (Spain); Classes of Bivariate Distributions with Normal and Lognormal Conditionals: A Brief Revision; Inequality Measures, Lorenz Curves and Generating Functions; Extended Waring Bivariate Distribution; Applying a Bayesian Hierarchical Model in Actuarial Science: Inference and Ratemaking; Analysis of the Empirical Distribution of the Residuals Derived from Fitting the Heligman and Pollard Curve to Mortality Data; Measuring the Efficiency of the Spanish Banking Sector: Super-Efficiency and Profitability. Readership: Upper undergraduates, graduates, academics, and professionals in mathematics, economics, statistics, and engineering."

This book looks at the distribution of income and wealth and the effects that this has on the macroeconomy, and vice versa. Is a more equal distribution of income beneficial or harmful for macroeconomic growth, and how does the distribution of wealth evolve in a market economy? Taking stock of results and methods developed in the context of the 1990s revival of growth theory, the authors focus on capital accumulation and long-run growth. They show how rigorous, optimization-based technical tools can be applied, beyond the representative-agent framework of analysis, to account for realistic market imperfections and for political-economic interactions. The treatment is thorough, yet accessible to students and nonspecialist economists, and it offers specialist readers a wide-ranging and innovative treatment of an increasingly important research field. The book follows a single analytical thread through a series of different growth models, allowing readers to appreciate their structure and crucial assumptions. This is particularly useful at a time when the literature on income distribution and growth has developed quickly and in several different directions, becoming difficult to overview.

Economic inequality has become a focus of prime interest for economic analysts and policy makers. This book provides an integrated approach to the topics of inequality and personal income distribution. It covers the practical and theoretical bases for inequality analysis, applications to real world problems and the foundations of theoretical approaches to income distribution. It also analyses models of the distribution of labour earnings and of income from wealth. The long-run development of income - and wealth - distribution over many generations is also examined. Special attention is given to an assessment of the merits and weaknesses of standard economic models, to illustrating the implications of distributional mechanisms using real data and illustrative examples, and to providing graphical interpretation of formal arguments. Examples are drawn from US, UK and international sources.

A comprehensive account of economic size distributions around the world and throughout the years In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences. Statistical Size Distributions in Economics and Actuarial Sciences is the first collection to systematically investigate a wide variety of parametric models that deal with income, wealth, and related notions. Christian Kleiber and Samuel Kotz survey, compliment, compare, and unify all of the disparate models of income distribution, highlighting at times a lack of coordination between them that can result in unnecessary duplication. Considering models from eight languages and all continents, the authors discuss the social and economic implications of each as well as distributions of size of loss in actuarial applications. Specific models covered include: Pareto distributions Lognormal distributions Gamma-type size distributions Beta-type size distributions Miscellaneous size distributions Three appendices provide brief biographies of some of the leading players along with the basic properties of each of the distributions. Actuaries, economists, market researchers, social scientists, and physicists interested in econophysics will find Statistical Size Distributions in Economics and Actuarial Sciences to be a truly one-of-a-kind addition to the professional literature.

Deals with income distribution methods and their economic applications.

Modelling Lorenz curves (LC) for stochastic dominance comparisons is central to the analysis of income distribution. It is conventional to use non-parametric statistics based on empirical income cumulants which are in the construction of LC and other related second-order dominance criteria. However, although attractive because of its simplicity and its apparent flexibility, this approach suffers from important drawbacks. While no assumptions need to be made regarding the data-generating process (income distribution model), the empirical LC can be very sensitive to data particularities, especially in the upper tail of the distribution. This robustness problem can lead in practice to 'wrong' interpretation of dominance orders. A possible remedy for this problem is the use of parametric or semi-parametric models for the datagenerating process and robust estimators to obtain parameter estimates. In this paper, we focus on the robust estimation of semi parametric LC and investigate issues such as sensitivity of LC estimators to data contamination (Cowell and Victoria-Feser 2002), trimmed LC (Cowell and Victoria-Feser 2006) and inference for trimmed LC (Cowell and Victoria-Feser 2003), robust semi-parametric estimation for LC (Cowell and Victoria-Feser 2007) selection of optimal thresholds for (robust) semi parametric modelling (Dupuis and Victoria-Feser 2006) and use both simulations and real data to illustrate these points.

This book is a printed edition of the Special Issue "Econometrics and Income Inequality" that was published in Econometrics