Estimations of Income Distribution Parameters for Individual Observations by Maximum Likelihood Method

Tachibanaki, Toshiaki; Suruga, Terukazu; Atoda, Naosumi

doi:10.14490/jjss1995.27.191

Cited by 9 publications

(12 citation statements)

References 10 publications

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“…This is due to the dissimilar features of income distribution in various countries and regions during different periods; that is, no distribution function was universal. For example, Tachibanaki et al [51] employed six commonly used distribution functions to research the income distribution of residents in Japan. McDonald [42] and McDonald and Xu [52] 1970,1975,1980,1985,1990, and 1995.…”

Section: Journal Of Applied Mathematicsmentioning

confidence: 99%

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

Chen

Fuqian

Hou

et al. 2015

Journal of Applied Mathematics

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Data insufficiency has become the primary factor affecting research on income disparity in China. To resolve this issue, this paper explores Chinese income distribution and income inequality using distribution functions. First, it examines 20 sets of grouped data on family income between 2005 and 2012 by theChina Yearbook of Household Surveys, 2013,and compares the fitting effects of eight distribution functions. The results show that the generalized beta distribution of the second kind has a high fitting to the income distribution of urban and rural residents in China. Next, these results are used to calculate the Chinese Gini ratio, which is then compared with the findings of relevant studies. Finally, this paper discusses the influence of urbanization on income inequality in China and suggests that accelerating urbanization can play an important role in narrowing the income gap of Chinese residents.

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Section: Journal Of Applied Mathematicsmentioning

confidence: 99%

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

Chen

Fuqian

Hou

et al. 2015

Journal of Applied Mathematics

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“…An alternative three-parameter approach that giving a good representation of income distributions in practice is provided by the Pareto-Lévy class (Mandelbrot 1960, Dagsvik et al 2013; unfortunately, except in a few cases, the probability distributions associated with this class cannot be represented in closed form. Dagum (1977Dagum ( , 1980Dagum ( , 1983, McDonald (1984), Butler and McDonald (1989), Majumder and Chakravarty (1990), McDonald and Xu (1995), Bantilan et al (1995), Victoria-Feser (1995, Brachmann et al (1996), Bordley et al (1997), Tachibanaki et al (1997) and Bandourian et al (2003). In most of these empirical studies, the generalized beta of the second kind, the Singh-Maddala and the Dagum distributions perform better than other two/three parameter distributions.…”

Section: Generalized Betamentioning

confidence: 97%

Statistical Methods for Distributional Analysis

Cowell

Flachaire

2015

Handbook of Income Distribution

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“…where a, b, q > 0 and r < 1 2q . When r = 0 (and a = α, b = β, q = 1 2κ ) the EκG1 quantile function is equivalent to that of the κ-generalized distribution-compare with (43).…”

Section: Four-parameter Extensions Of the κ-Generalized Distributionmentioning

confidence: 99%

κ-generalized models of income and wealth distributions: A survey

Clementi

Gallegati

Kaniadakis

et al. 2016

Eur. Phys. J. Spec. Top.

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The paper provides a survey of results related to the "κ-generalized distribution", a statistical model for the size distribution of income and wealth. Topics include, among others, discussion of basic analytical properties, interrelations with other statistical distributions as well as aspects that are of special interest in the income distribution field, such as the Gini index and the Lorenz curve. An extension of the basic model that is most able to accommodate the special features of wealth data is also reviewed. The survey of empirical applications given in this paper shows the κ-generalized models of income and wealth to be in excellent agreement with the observed data in many cases.

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Estimations of Income Distribution Parameters for Individual Observations by Maximum Likelihood Method

Cited by 9 publications

References 10 publications

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

Statistical Methods for Distributional Analysis

κ-generalized models of income and wealth distributions: A survey

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