Rank-dominance in income distributions

Public Choice ◽  
1981 ◽  
Vol 36 (1) ◽  
Author(s):  
Rubin Saposnik
1991 ◽  
Vol 35 (7) ◽  
pp. 1399-1409 ◽  
Author(s):  
John A. Bishop ◽  
John P. Formby ◽  
Paul D. Thistle

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Manoj Kumar Sinha

Since 1991, India has cautiously and slowly opened almost all the sectors, except a few related to strategic importance, for foreign investors. Degree of openness of various industrial sectors for FDI has been increased to the extent of 100 percent by consistently liberalizing industrial policies of the sectors. The purpose of the paper is to study pattern and trends of sectoral distribution of FDI within the background of the first generation reforms and liberalized industrial policies during 1991-2001. The paper has used series of the dynamics and stylistic indices and statistical tools such as three level indices, index of rank dominance, and correlation matrices for explaining the pattern of FDI distribution across sectors during 1991-2001. The results show that electrical, transportation, chemical, telecommunication, and service sectors are most dominating sectors and represent almost 75 percent of total FDI received during 1991-2001. Index of rank dominance indicates distribution of FDI across the sectors is top heavy.


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.


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