The Distribution of Income and Wealth: Parametric Modeling with the -Generalized Family
Springer | Econometrics, Statistics | January 20, 2016 | ISBN-10: 3319274082 | 177 pages | pdf | 4.1 mb
Authors: Clementi, Fabio, Gallegati, Mauro
Offers a compendium of original contributions on the parametric modeling of income and wealth distribution
Thoroughly discusses the κ-generalized distribution and describes the advantages of this parametric model
Contains many up-to-date applications to income and wealth data
K-generalized distribution and describes the advantages of this parametric model
Contains many up-to-date applications to income and wealth data
This book presents a systematic overview of cutting-edge research in the field of parametric modeling of personal income and wealth distribution, which allows one to represent how income/wealth is distributed within a given population. The estimated parameters may be used to gain insights into the causes of the evolution of income/wealth distribution over time, or to interpret the differences between distributions across countries. Moreover, once a given parametric model has been fitted to a data set, one can straightforwardly compute inequality and poverty measures. Finally, estimated parameters may be used in empirical modeling of the impact of macroeconomic conditions on the evolution of personal income/wealth distribution. In reviewing the state of the art in the field, the authors provide a thorough discussion of parametric models belonging to the "κ-generalized" family, a new and fruitful set of statistical models for the size distribution of income and wealth that they have developed over several years of collaborative and multidisciplinary research. This book will be of interest to all who share the belief that problems of income and wealth distribution merit detailed conceptual and methodological attention.
Number of Illustrations and Tables
24 in colour
Topics
Econometrics
Socio- and Econophysics, Population and Evolutionary Models
Organizational Studies, Economic Sociology
Statistics for Business, Economics, Mathematical Finance, Insurance
Game Theory, Economics, Social and Behav. Sciences
More info and Hardcover at Springer
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