語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
The distribution of Income and wealt...
~
Gallegati, Mauro.
The distribution of Income and wealth = parametric modeling with the κ-generalized family /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
The distribution of Income and wealth/ by Fabio Clementi, Mauro Gallegati.
其他題名:
parametric modeling with the κ-generalized family /
作者:
Clementi, Fabio.
其他作者:
Gallegati, Mauro.
出版者:
Cham :Springer International Publishing : : 2016.,
面頁冊數:
xvi, 177 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Income distribution - Mathematical models. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-27410-2
ISBN:
9783319274102
The distribution of Income and wealth = parametric modeling with the κ-generalized family /
Clementi, Fabio.
The distribution of Income and wealth
parametric modeling with the κ-generalized family /[electronic resource] :by Fabio Clementi, Mauro Gallegati. - Cham :Springer International Publishing :2016. - xvi, 177 p. :ill., digital ;24 cm. - New economic windows,2039-411X. - New economic windows..
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 κ-Generalized Distribution -- Underlying Stochastic Process -- Empirical Results and Comparisons to Alternative Income Distributions -- The κ-Generalized Mixture Model for the Size Distribution of Wealth -- Motivation -- Model Specification -- Moments of the κ-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 κ-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.
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.
ISBN: 9783319274102
Standard No.: 10.1007/978-3-319-27410-2doiSubjects--Topical Terms:
669670
Income distribution
--Mathematical models.
LC Class. No.: HB523
Dewey Class. No.: 330
The distribution of Income and wealth = parametric modeling with the κ-generalized family /
LDR
:03471nam a2200325 a 4500
001
861489
003
DE-He213
005
20160811145201.0
006
m d
007
cr nn 008maaau
008
170720s2016 gw s 0 eng d
020
$a
9783319274102
$q
(electronic bk.)
020
$a
9783319274089
$q
(paper)
024
7
$a
10.1007/978-3-319-27410-2
$2
doi
035
$a
978-3-319-27410-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HB523
072
7
$a
KCH
$2
bicssc
072
7
$a
BUS021000
$2
bisacsh
082
0 4
$a
330
$2
23
090
$a
HB523
$b
.C626 2016
100
1
$a
Clementi, Fabio.
$3
1103935
245
1 4
$a
The distribution of Income and wealth
$h
[electronic resource] :
$b
parametric modeling with the κ-generalized family /
$c
by Fabio Clementi, Mauro Gallegati.
260
$a
Cham :
$c
2016.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xvi, 177 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
New economic windows,
$x
2039-411X
505
0
$a
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 κ-Generalized Distribution -- Underlying Stochastic Process -- Empirical Results and Comparisons to Alternative Income Distributions -- The κ-Generalized Mixture Model for the Size Distribution of Wealth -- Motivation -- Model Specification -- Moments of the κ-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 κ-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.
520
$a
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.
650
0
$a
Income distribution
$x
Mathematical models.
$3
669670
650
0
$a
K-distribution (Probability theory)
$3
1103937
650
0
$a
Wealth
$x
Mathematical models.
$3
576522
650
0
$a
Game theory.
$3
556918
650
1 4
$a
Economics.
$3
555568
650
2 4
$a
Econometrics.
$3
556981
650
2 4
$a
Socio- and Econophysics, Population and Evolutionary Models.
$3
785051
650
2 4
$a
Organizational Studies, Economic Sociology.
$3
881674
650
2 4
$a
Statistics for Business/Economics/Mathematical Finance/Insurance.
$3
669275
650
2 4
$a
Game Theory, Economics, Social and Behav. Sciences.
$3
669497
700
1
$a
Gallegati, Mauro.
$3
1103936
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
New economic windows.
$3
1020475
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-27410-2
950
$a
Economics and Finance (Springer-41170)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入