Income distribution in the European Union versus in the United States

Jagielski, Maciej; Duczmal, R.; Kutner, Ryszard

doi:10.1016/j.physa.2015.03.071

Cited by 8 publications

(5 citation statements)

References 27 publications

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“…325-327; Gregorini, 2015, pp. 447-449; Jagielski et al , 2015, p. 39; Baliamoune–Lutz and McGillivray, 2015, pp. 9-10).…”

Section: Literature Reviewmentioning

confidence: 99%

Education expenditures and income distribution: an empirical analysis on European countries

Çelikay

Şengür

2016

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Purpose This study aims to examine the relationship between public sector education expenditure and the GINI coefficient as a measure of injustice in income distribution. Design/methodology/approach Data from 31 European countries gathered from 2004 to 2011 were analyzed using panel error correction models. Findings According to the study’s findings, a relationship between education expenditures and the GINI coefficient exists. There is a 1 per cent increase for the European countries examined in this study in their rate of education expenditure in gross domestic product (GDP), which raises the GINI coefficient by 0.20 per cent in the short-term and decreases it by 0.22 per cent in the long-term, as expected. Thus, an increase in the proportion of education expenditures in GDP affects the GINI coefficient in a statistically significant, negative way over the long-term. Originality/value This study fills a gap in the literature by determining whether the interaction between education expenditure and GINI coefficient changes in the short- and long-term. The results show that education expenditure generates positive results particularly by lowering income inequality in the long-term. This interaction can be more clearly observed in developing countries. So this conclusion adds an important empirical evidence to the literature and it may contribute in forming policies toward reducing income inequality.

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“…325-327; Gregorini, 2015, pp. 447-449; Jagielski et al , 2015, p. 39; Baliamoune–Lutz and McGillivray, 2015, pp. 9-10).…”

Section: Literature Reviewmentioning

confidence: 99%

Education expenditures and income distribution: an empirical analysis on European countries

Çelikay

Şengür

2016

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“…Since the publication of Vilfredo Pareto's pioneering work on income distribution in the late nineteenth century many additional studies have been carried out to empirically verify the Pareto law for both individuals and households. These analyses were carried out for the United States [3][4][5][6][7][8][9][10][11], the European Union [6,11,12], the UK [3,5,7,8,13], Germany [3], Italy [14,15], France [7], Switzerland [16], Sweden [8], Japan [9,[17][18][19][20], Australia [14,21], Canada [22], India [22,23], Sri Lanka [22], Peru [16], Egypt [22], South Korea [24], Romania [25], Portugal [22], Poland [6,26], and for the world as a whole [27,28].…”

Section: Introductionmentioning

confidence: 99%

Income and wealth distribution of the richest Norwegian individuals: An inequality analysis

Jagielski

Czyżewski

Kutner

et al. 2017

Physica A: Statistical Mechanics and its Applications

Self Cite

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“…Oancea et al (2017) presented a study as a part of their research on the allocation of personal income and the inequality in this allocation in Romania, processing individual tax income data using non-parametric and parametric methods. Jagielski et al (2015) also did a similar comparison on the distribution of income in the European Union and the United States in their work. The works on income inequality by other authors discuss differences in income between individuals or families or even between different population groups, regions or countries (Perron, 1998;Wood, 1995;Townsend, 1993;Ahluwalia, 1976).…”

Section: Literature Reviewmentioning

confidence: 88%

The Impact of Economic, Demographic, and Infrastructural Factors on Income Inequality and Poverty in Russia

Groznykh¹,

Ignatieva

Mariev

et al. 2020

PEB

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The prime objective of the research is to examine the factors influencing both the alteration in the income distribution and the relative change in the incidence of poverty in the regions of Russia. The list of the identified factors/determinants includes economic, demographic, and infrastructural factors. An econometric model, indicating the relationship between the explanatory variables with both the income inequality index and the relative poverty proportions in Russian regions has been provided in this article. The determinants that cause variations in the income inequality and poverty of a country such as social mobility, average life expectancy of urban women, life expectancy of rural men, the number of university graduates, etc. have also been specified in this study. The analysis was executed based on a dataset of 72 Russian regions for the period between 2012-2017.

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Income distribution in the European Union versus in the United States

Cited by 8 publications

References 27 publications

Education expenditures and income distribution: an empirical analysis on European countries

Education expenditures and income distribution: an empirical analysis on European countries

Income and wealth distribution of the richest Norwegian individuals: An inequality analysis

The Impact of Economic, Demographic, and Infrastructural Factors on Income Inequality and Poverty in Russia

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