This book deals with the following issues: the analysis, estimation and assessment of alternatived models of income distribution, the specification and evaluation of income inequality measures the analysis and measurement of poverty and its rationale, the scope and methodological power of the social accounting matrix (SAM) in the analysis of the functional and personal distribution of income and the family income multiplier, the study of the source and reliability of income distribution data, the decomposition of income inequality measures, the asymptotic distributions and inferential analysis of income inequalities, and an inquiry on the income distribution and income inequality of Eastern European Countries under socialism. New models on income and wealth distribution are specified and their corresponding properties and goodness of fit are discussed. A multivariate approach to the measurement of poverty is developed and applied, and a compact survey of the literature is presented. The book can be used as a text in advanced undergraduate and graduate courses dealing with the theory, model specifications, methods and applications of income and wealth distribution, income inequality and poverty assessment in measurement and the use of SAMs in the analysis of income distribution.
Camilo Dagum & Michele Zenga
Income and Wealth Distribution, Inequality and Poverty [PDF ebook]
Proceedings of the Second International Conference on Income Distribution by Size: Generation, Distribution, Measurement and Applications, Held at the University of Pavia, Italy, September 28-30, 1989
Income and Wealth Distribution, Inequality and Poverty [PDF ebook]
Proceedings of the Second International Conference on Income Distribution by Size: Generation, Distribution, Measurement and Applications, Held at the University of Pavia, Italy, September 28-30, 1989
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Language English ● Format PDF ● ISBN 9783642842504 ● Editor Camilo Dagum & Michele Zenga ● Publisher Springer Berlin Heidelberg ● Published 2012 ● Downloadable 3 times ● Currency EUR ● ID 6334903 ● Copy protection Adobe DRM
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