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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).
"Prof. Nitis Mukhopadhyay and Prof. Partha Pratim Sengupta, who edited this volume with great attention and rigor, have certainly carried out noteworthy activities." - Giovanni Maria Giorgi, University of Rome (Sapienza) "This book is an important contribution to the development of indices of disparity and dissatisfaction in the age of globalization and social strife." - Shelemyahu Zacks, SUNY-Binghamton "It will not be an overstatement when I say that the famous income inequality index or wealth inequality index, which is most widely accepted across the globe is named after Corrado Gini (1984-1965). ... I take this opportunity to heartily applaud the two co-editors for spending their valuable time and energy in putting together a wonderful collection of papers written by the acclaimed researchers on selected topics of interest today. I am very impressed, and I believe so will be its readers." - K.V. Mardia, University of Leeds Gini coefficient or Gini index was originally defined as a standardized measure of statistical dispersion intended to understand an income distribution. It has evolved into quantifying inequity in all kinds of distributions of wealth, gender parity, access to education and health services, environmental policies, and numerous other attributes of importance. Gini Inequality Index: Methods and Applications features original high-quality peer-reviewed chapters prepared by internationally acclaimed researchers. They provide innovative methodologies whether quantitative or qualitative, covering welfare economics, development economics, optimization/non-optimization, econometrics, air quality, statistical learning, inference, sample size determination, big data science, and some heuristics. Never before has such a wide dimension of leading research inspired by Gini's works and their applicability been collected in one edited volume. The volume also showcases modern approaches to the research of a number of very talented and upcoming younger contributors and collaborators. This feature will give readers a window with a distinct view of what emerging research in this field may entail in the near future.
What do we mean by inequality comparisons? If the rich just get richer and the poor get poorer, the answer might seem easy. But what if the income distribution changes in a complicated way? Can we use mathematical or statistical techniques to simplify the comparison problem in a way that has economic meaning? What does it mean to measure inequality? Is it similar to National Income? Or a price index? Is it enough just to work out the Gini coefficient? Measuring Inequality tackles these questions and examines the underlying principles of inequality measurement and its relation to welfare economics, distributional analysis, and information theory. The book covers modern theoretical developments in inequality analysis, as well as showing how the way we think about inequality today has been shaped by classic contributions in economics and related disciplines. Formal results and detailed literature discussion are provided in two appendices. The principal points are illustrated in the main text, using examples from US and UK data, as well as other data sources, and associated web materials provide hands-on learning. Measuring Inequality is designed to appeal to both undergraduate and post-graduate students, and academic economists. Its emphasis on practical application means that it will also be useful to policy analysts and advisors.
Amartya Sen "Equality," I spoke the word As if a wedding vow Ah, but I was so much older then, I am younger than that now. Thus sang Bob Dylan in 1964. Approbation of equality varies not only with our age (though it is not absolutely clear in which direction the values may shift over one's life time), but also with the spirit of the times. The 1960s were good years for singing in praise of equality. The spirit of the present times would probably be better reflected by melodies in admiration of the Federal Reserve System. And yet the technical literature on the evaluation and measurement of economic inequality has grown remarkably over the last three decades. Even as actual economic policies (especially in North America and Europe) have tended to move towards focusing on virtues other than the avoidance of economic inequality, the professional literature on assessing and gauging economic inequality has taken quite a jump forward. A great many different problems have been addressed and effectively sorted out, and new problems continue to be posed and analyzed. The Contents: A Review Jacques Silber has done a great service to the subject by producing this collection of admirablyhelpful and illuminating papers on different aspects of the measurement of income inequality. The reach of this collection is quite remarkable. Along with a thorough overview from the editor himself, the major areas in this complex field have been carefully examined and accessibly discussed.
A bibliography on stochastic orderings. Was there a real need for it? In a time of reference databases as the MathSci or the Science Citation Index or the Social Science Citation Index the answer seems to be negative. The reason we think that this bibliog raphy might be of some use stems from the frustration that we, as workers in the field, have often experienced by finding similar results being discovered and proved over and over in different journals of different disciplines with different levels of mathematical so phistication and accuracy and most of the times without cross references. Of course it would be very unfair to blame an economist, say, for not knowing a result in mathematical physics, or vice versa, especially when the problems and the languages are so far apart that it is often difficult to recognize the analogies even after further scrutiny. We hope that collecting the references on this topic, regardless of the area of application, will be of some help, at least to pinpoint the problem. We use the term stochastic ordering in a broad sense to denote any ordering relation on a space of probability measures. Questions that can be related to the idea of stochastic orderings are as old as probability itself. Think for instance of the problem of comparing two gambles in order to decide which one is more favorable.