Coverart for item
The Resource The Distribution of Income and Wealth : Parametric Modeling with the m-Generalized Family, by Fabio Clementi, Mauro Gallegati, (electronic resource)

The Distribution of Income and Wealth : Parametric Modeling with the m-Generalized Family, by Fabio Clementi, Mauro Gallegati, (electronic resource)

Label
The Distribution of Income and Wealth : Parametric Modeling with the m-Generalized Family
Title
The Distribution of Income and Wealth
Title remainder
Parametric Modeling with the m-Generalized Family
Statement of responsibility
by Fabio Clementi, Mauro Gallegati
Creator
Contributor
Subject
Language
eng
Summary
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 "m-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
Member of
http://library.link/vocab/creatorName
Clementi, Fabio
Image bit depth
0
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Gallegati, M.
Series statement
  • Springer eBooks.
  • New Economic Windows,
http://library.link/vocab/subjectName
  • Game theory
  • Sociophysics
  • Econophysics
  • Statistics
  • Econometrics
  • Economic sociology
Label
The Distribution of Income and Wealth : Parametric Modeling with the m-Generalized Family, by Fabio Clementi, Mauro Gallegati, (electronic resource)
Link
http://ezproxy.eui.eu/login?url=http://dx.doi.org/10.1007/978-3-319-27410-2
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Introduction -- The Revived Interest in the Problems of Income and Wealth Distribution -- Re-incorporating Distributional Issues Into the Main Body of Economic Analysis -- Aim and Contents of this Book -- The Parametric Approach to Income and Wealth Distributional Analysis -- The Idea of a Parametric Model for Income and Wealth Distributions -- Brief History of the Models for Studying Income and Wealth Distributions -- The m-Generalized Distribution -- Underlying Stochastic Process -- Empirical Results and Comparisons to Alternative Income Distributions -- The m-Generalized Mixture Model for the Size Distribution of Wealth -- Motivation -- Model Specification -- Moments of the m-Generalized Mixture Model for Net Wealth Distribution -- The Lorenz Curve and the Gini Index of the Net Wealth Distribution Model -- Empirical Results and Comparison of Finite Mixture Models for Net Wealth Distribution -- Four-Parameter Extensions of the m-Generalized Distribution -- Definitions and Basic Properties -- Population Characteristics -- Empirical Results and Comparisons to Alternative Four-Parameter Statistical Distributions -- Conclusions -- Appendices -- References -- Author Index -- Subject Index
Control code
978-3-319-27410-2
Dimensions
unknown
Edition
1st ed. 2016.
Extent
1 online resource (xvi, 177 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9783319274102
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other control number
10.1007/978-3-319-27410-2
Other physical details
24 illustrations in color.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)993118847
Label
The Distribution of Income and Wealth : Parametric Modeling with the m-Generalized Family, by Fabio Clementi, Mauro Gallegati, (electronic resource)
Link
http://ezproxy.eui.eu/login?url=http://dx.doi.org/10.1007/978-3-319-27410-2
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Introduction -- The Revived Interest in the Problems of Income and Wealth Distribution -- Re-incorporating Distributional Issues Into the Main Body of Economic Analysis -- Aim and Contents of this Book -- The Parametric Approach to Income and Wealth Distributional Analysis -- The Idea of a Parametric Model for Income and Wealth Distributions -- Brief History of the Models for Studying Income and Wealth Distributions -- The m-Generalized Distribution -- Underlying Stochastic Process -- Empirical Results and Comparisons to Alternative Income Distributions -- The m-Generalized Mixture Model for the Size Distribution of Wealth -- Motivation -- Model Specification -- Moments of the m-Generalized Mixture Model for Net Wealth Distribution -- The Lorenz Curve and the Gini Index of the Net Wealth Distribution Model -- Empirical Results and Comparison of Finite Mixture Models for Net Wealth Distribution -- Four-Parameter Extensions of the m-Generalized Distribution -- Definitions and Basic Properties -- Population Characteristics -- Empirical Results and Comparisons to Alternative Four-Parameter Statistical Distributions -- Conclusions -- Appendices -- References -- Author Index -- Subject Index
Control code
978-3-319-27410-2
Dimensions
unknown
Edition
1st ed. 2016.
Extent
1 online resource (xvi, 177 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9783319274102
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other control number
10.1007/978-3-319-27410-2
Other physical details
24 illustrations in color.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)993118847

Library Locations

    • Badia FiesolanaBorrow it
      Via dei Roccettini 9, San Domenico di Fiesole, 50014, IT
      43.803074 11.283055
Processing Feedback ...