Sociophysics of income distributions modeled by deformed fermi-dirac distributions

Author(s):  
Emre Dil ◽  
Elif Dil
Keyword(s):  
2015 ◽  
Vol 27 (02) ◽  
pp. 1630001 ◽  
Author(s):  
Dietrich Stauffer

Capital usually leads to income and income is more accurately and easily measured. Thus, we summarize income distributions in USA, Germany, etc.


Author(s):  
Alex Cobham ◽  
William Davis ◽  
Gamal Ibrahim ◽  
Andy Sumner

AbstractA recent innovation in measuring inequality is the incorporation of adjustments to top incomes using data from tax authorities, revealing higher inequality. The thesis of this paper is that the incorporation of estimates of income from illicit financial flows (IFF), reflecting untaxed capital, may be as significant to national inequality – but with greater variation across countries. We propose a method of adjusting national inequality data for illicit flows, and present preliminary results. These estimates suggest that untaxed illicit flows could be as important as (taxed) top incomes to estimates of inequality – highlighting the importance of improving estimates of underlying illicit flows.


Econometrica ◽  
1982 ◽  
Vol 50 (5) ◽  
pp. 1337 ◽  
Author(s):  
Anthony F. Shorrocks
Keyword(s):  

Demography ◽  
1989 ◽  
Vol 26 (1) ◽  
pp. 149 ◽  
Author(s):  
Lois Fonseca ◽  
Jeff Tayman

2020 ◽  
Vol 26 (4) ◽  
pp. 433-447
Author(s):  
Francesca Greselin ◽  
Alina Jȩdrzejczak

AbstractHigh-income inequality, accompanied by substantial regional differentiation, is still a great challenge for social policymakers in many European countries. One of the important elements of this phenomenon is the inequality between income distributions of men and women. Using data from the European Union Statistics on Income and Living Conditions, the distributions of income for Italy and Poland were compared, and the gender gap in these countries was assessed. No single metric can capture the full range of experiences, so a set of selected tools were adopted. The Dagum model was fitted to each distribution, summary measures, like the Gini and Zenga inequality indices, were evaluated, and the Zenga curve was employed to detect changes at each income quantile. Afterward, empirical distributions were compared through a relative approach, providing an analytic picture of the gender gap for both countries. The analysis moved beyond the typical focus on average or median earnings differences, towards a focus on how the full distribution of women’s earnings relative to men’s compares. The analysis was performed in the different macroregions of the two countries, with a discussion of the results. The study revealed that income inequality in Poland and Italy varies across gender and regions. In Italy, the highest inequality was observed in the poorest region, i.e. the islands. On the contrary, in Poland, the highest inequality occurred in the richest region, the central one. The relative distribution method was a powerful tool for studying the gender gap.


2020 ◽  
Vol 63 (3) ◽  
pp. 210-232
Author(s):  
Julia Włodarczyk ◽  

The paper presents results of a descriptive analysis of income distributions as well as top income inequality among women and men in Poland. The analysis is based on the dataset provided by the Council for Social Monitoring (2019). Throughout 2003–2015 their panel survey included, for example, a question on individual net monthly income in the past three months. In order to reduce differences associated with the age of entering and exiting the labour market on declared income levels (especially pensions), the calculations include only women and men aged 25–60 years. The analysis of income distributions of women and men in Poland is based on standard measures such as mean income, median income and related measures, as well as the Gini coefficient, Theil index and entropy index. It is supplemented by kernel density estimates and results of simultaneous quantile regressions that demonstrate differences between women and men across income groups. The analysis of top income inequality includes comparisons of subsamples consisting of top 3% earners in each group. The share of women in the top percentiles is then calculated and discussed. The analysis shows different dynamics related to the incomes of women and men, which provides support for including business cycle considerations in the analysis of income inequalities and their gender aspects.


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