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Author: Shlomo Yitzhaki Publisher: Springer ISBN: 9781461447214 Category : Mathematics Languages : en Pages : 548
Book Description
Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
Author: Shlomo Yitzhaki Publisher: Springer ISBN: 9781461447214 Category : Mathematics Languages : en Pages : 548
Book Description
Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
Author: Shlomo Yitzhaki Publisher: Springer Science & Business Media ISBN: 1461447208 Category : Mathematics Languages : en Pages : 549
Book Description
Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
Author: Nitis Mukhopadhyay Publisher: CRC Press ISBN: 1000349128 Category : Mathematics Languages : en Pages : 276
Book Description
"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.
Author: Amit Shelef Publisher: ISBN: Category : Languages : en Pages : 26
Book Description
The objective of this paper is to suggest a visual method for identifying departures from normality of the innovations in times series models. The method is based on replacing the variance by the Gini as the measure of variability. The Gini methodology is a rank-based methodology, which takes into account both the variate values and the ranks. It relies only on first order moment assumptions hence it is valid for a wider range of distributions. The key idea lies in the fact that there are two Gini-autocorrelation functions for each pair of variables, which are not necessarily equal. The difference between them, when it exists, can be informative and may assist to identify models with underlying heavy tailed and non-normal innovations. We suggest using Gini-correlograms, a simple graphical tool, to check the symmetry assumption which is natural in the existing methodology. We illustrate the suggested methodology using simulations.
Author: Edna Schechtman Publisher: ISBN: Category : Languages : en Pages : 7
Book Description
The connection between the area under the ROC curve (AUC), which is frequently used in the diagnosis and classification literature, and the Gini terminology, which is mainly used in the economic literature, is clarified. It is shown that AUC is related to the covariance between Yi, the number of 1's until the ith 0, and F(Ti), the empirical rank of the ith 0, ordered by the predictive probability.
Author: A. B. Atkinson Publisher: OUP Oxford ISBN: 0191500887 Category : Business & Economics Languages : en Pages : 984
Book Description
A rapidly growing area of economic research investigates the top of the income distribution using data from income tax records. This volume brings together studies of top incomes for twelve countries from around the world, including China, India, Japan, Argentina and Indonesia. Together with the first volume, published in 2007, the studies cover twenty two countries. They have a long time span, the earliest data relating to 1875 (for Norway), allowing recent developments to be placed in historical perspective. The volume describes in detail the source data and the methods employed. It will be an invaluable reference source for researchers in the field. Individual country chapters deal with the specific nature of the data for each of the countries, and describe the long-term evolution of top income shares. In the countries as a whole, dramatic changes have taken place at the top of the income distribution. Over the first part of the century, top income shares fell markedly. This largely took the form of a reduction in capital incomes. The different authors examine the impact of the First and Second World Wars, contrasting countries that were and were not engaged. They consider the impact of depressions and banking crises, and pay particular attention to the impact of progressive taxation. In the last 30 years, the shares of top incomes have increased markedly in the US and other Anglo-Saxon countries, reflecting the increased dispersion of earnings. The volume includes statistics on the much-discussed top pay and bonuses, providing a global perspective that discusses important differences between countries such as the lesser increase in Continental Europe. This book, together with volume 1, documents this interesting development and explores the underlying causes. The findings are brought together in a final summary chapter by Atkinson, Piketty and Saez.
Author: Daniel J. Slottje Publisher: Springer Science & Business Media ISBN: 3642936415 Category : Business & Economics Languages : en Pages : 392
Book Description
Articles on econometric methodology with special reference to the quantification of poverty and economic inequality are presented in this book. Poverty and inequality measurement present special problems to the econometrician, and most of these papers analyze how to attack those problems. The topics and contributions in the book are a very good representation of Camilo Dagum's astounding diversity of interests and overall eclecticism. Several of the authors are leading pioneers in econometric methodology. Several others are pioneers in economic theory and others are the leading applied economists in income distribution analysis in the world. The topics accurately reflect Camilo Dagum's breadth of understanding across varios economic sub-fields, all complex in nature.
Author: Frank Alan Cowell Publisher: ISBN: 9780191808654 Category : Income distribution Languages : en Pages : 233
Book Description
This text 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.
Author: Shlomo Yitzhaki
Author: Shlomo Yitzhaki
Author: Shlomo Yitzhaki
Author: Nitis Mukhopadhyay
Author: Amit Shelef
Author: Edna Schechtman
Author: J. J. Thompson
Author: A. B. Atkinson
Author: Oyugi Aseto
Author: Daniel J. Slottje
Author: Frank Alan Cowell