scholarly journals Getting to a feasible income equality

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249204
Author(s):  
Ji-Won Park ◽  
Chae Un Kim

Income inequality is known to have negative impacts on an economic system, thus has been debated for a hundred years past or more. Numerous ideas have been proposed to quantify income inequality, and the Gini coefficient is a prevalent index. However, the concept of perfect equality in the Gini coefficient is rather idealistic and cannot provide realistic guidance on whether government interventions are needed to adjust income inequality. In this paper, we first propose the concept of a more realistic and ‘feasible’ income equality that maximizes total social welfare. Then we show that an optimal income distribution representing the feasible equality could be modeled using the sigmoid welfare function and the Boltzmann income distribution. Finally, we carry out an empirical analysis of four countries and demonstrate how optimal income distributions could be evaluated. Our results show that the feasible income equality could be used as a practical guideline for government policies and interventions.

2021 ◽  
Vol 66 (2) ◽  
pp. 16-32
Author(s):  
Grzegorz Przekota ◽  

Determining the level of income inequality requires the adoption of a specific measurement methodology. The aim of the study was to review and discuss the methodologies used to measure income inequality. Four measures are presented, each based on different assumptions. These measures were the Gini coefficient, Theil coefficient, Kukuła coefficient and unevenness coefficient. The first three measures, and in particular the Gini coefficient, are commonly described in the literature, while the unevenness coefficient is the author’s proposal for measuring income inequality. The empirical material for the research consists of data on the distribution of disposable income by decile groups in households in Poland for the years 2005–2017. The most important issue in practice regarding the measurement of income inequality was the transfer principle. Depending on the methodology adopted, the transfer of income is treated differently. The Gini, Theil and Kukula coefficients respond to any change in the income distribution, while the unevenness coefficient only to changes above the average. In a situation where the Gini coefficient (Theil and Kukula) decreases (increases), the level of inequality decreases (increases), but it is not known which transfers led to such a result. The decreasing (growing) unevenness coefficient means that these were transfers from groups with shares in income above (below) the average for groups with shares below (above) the average.


2018 ◽  
Vol 10 (2) ◽  
pp. 28
Author(s):  
Cassandra E. DiRienzo ◽  
Jayoti Das

This study seeks to close the gap between the theoretical rationale for the role of income inequality in human trafficking and lack of empirical evidence supporting this relationship. It is argued that differences in income, especially the income of the poorest in the population, is a significant push factor encouraging individuals to undertake risky migration. Nonetheless, the Gini coefficient, which is typically used in human trafficking research, does not accurately capture the theoretical rationale for why difference in population income, especially the income of the poorest in the population, should matter. A different metric for measuring income inequality – one that is tied to the theoretical underpinnings -- is introduced. Empirical evidence supporting the role that income plays on the poorest in the population on human trafficking outflows is offered. Specifically, as the poorest in the population become marginally better off, there is an increase in human trafficking outflows at the country level.


Humanomics ◽  
2016 ◽  
Vol 32 (3) ◽  
pp. 248-257
Author(s):  
Ferdi Celikay ◽  
Mehmet Sengur

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.


2015 ◽  
Vol 9 (6) ◽  
pp. 79-82 ◽  
Author(s):  
Morteza Nemati ◽  
Ghasem Raisi

Nowadays, improvement in income distribution and poverty eradication and hence low inequality are served as the main objectives of economic and social development strategy even prior than primary tasks of governments. to manifest importance of income distribution, some economists adopt income inequality and income distribution in society as criteria for economic system of the community, although these criteria and measures are theoretical for the economic system and this varies from the perspective of different people, however, it denotes on  importance of income distribution among individuals. The main objective of this study was to evaluate the effect of economic growth on income inequality in the selection of low-income developing countries.To this end, using panel data and data for 28 developing countries over the period 1990-2010 the relationship between GDP and the Gini coefficient was examined. The results indicate that as per hypothesis Kuznets in the early stages of growth, income inequality increases and then it declines in later stage.


e-Finanse ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. 20-32
Author(s):  
Grzegorz Golebiowski ◽  
Piotr Szczepankowski ◽  
Dorota Wisniewska

Abstract The article examines the impact of financialization on income inequality between 2004 and 2013, through a panel analysis of seven European countries. Moreover, it attempts to examine differences in the perception of the phenomenon between the selected European countries belonging to the G-7 and countries from Central and Eastern Europe. The results demonstrate the existence of individual effects, which means that the level of inequality under examination is influenced predominantly by country-specific factors. The most significant correlation is noticeable between the level of unemployment and the degree of income inequality. An increase in unemployment is accompanied by a rise in the disproportions in the level of income that individual citizens have at their disposal whereas a decrease in the unemployment level contributes to an improvement of the GINI coefficient. Simultaneously, the results confirm the existence of significant correlations between the level of the GINI coefficient and such financialization indicators as the share of employment in finance in total employment and the contribution of the financial sector to total value added creation. The most prominent dependency was discovered when a constructed synthetic indicator was adopted as an indicator of financialization. At the same time, analysis of the synthetic country financialization indicator points to a conclusion that the level of financialization is higher in European countries belonging to the G-7 (especially Great Britain) than in countries from Central and Eastern Europe.


Author(s):  
Andrew Smithers

Living standards change in line with GDP per head only if the distribution of incomes is unchanged. If incomes become less equally distributed the living standards of most people will fall even if GDP per head is stable. The Gini Coefficient is the most widely used indicator designed to measure the distribution of income. UK inequality, on this measure, has risen since 1977, stabilized since 1987, and fallen in recent years. In the US there has been a long-term increase in income inequality. Unless this US trend for increased income inequality halts, it is quite likely that even if GDP per head rises in the US, the living standard of the average voter will fall. The recent data suggest that changes in income inequality pose less of a threat to living standards in the UK then they do to those in the US.


Author(s):  
W. Henry Chiu

Abstract This paper defines and characterizes the concept of an increase in inverse downside inequality and show that, when the Lorenz curves of two income distributions intersect, how the change from one distribution to the other is judged by an inequality index exhibiting inverse downside inequality aversion often depends on the relative strengths of its aversion to inverse downside inequality and inequality aversion. For the class of linear inequality indices, of which the Gini coefficient is a member, a measure characterizing the strength of an index’s aversion to inverse downside inequality against its own inequality aversion is shown to determine the ranking by the index of two distributions whose Lorenz curves cross once. The precise condition under which the same result generalizes to the case of multiple-crossing Lorenz curves is also identified.


2005 ◽  
Vol 08 (01) ◽  
pp. 159-167 ◽  
Author(s):  
HAI-BO HU ◽  
LIN WANG

The Gini coefficient, which was originally used in microeconomics to describe income inequality, is introduced into the research of general complex networks as a metric on the heterogeneity of network structure. Some parameters such as degree exponent and degree-rank exponent were already defined in the case of scale-free networks also as a metric on the heterogeneity. In scale-free networks, the Gini coefficient is proved to be equivalent to the parameters mentioned above, and moreover, a classification of infinite scale-free networks is given according to the value of the Gini coefficient.


Author(s):  
Yusuf Munandar

One measure of income inequality that is often used is the Gini Coefficient. In Central Java Province, the income inequality in March 2019 was increasing compared to income inequality in September 2018. To reduce this income inequality, the government is focusing on increasing government spending in the field of social assistance, including Non-Cash Food Assistance (Bantuan Pangan Non Tunai/BPNT). Thus, this study aims to calculate and obtain a reduction in the Gini Coefficient as a result of the implementation of the BPNT program in the Central Java Province of Indonesia. This study uses the Counter Factual Analysis (CFA) method and the March 2019 Susenas data. This study concludes that the implementation of the BPNT program in 2019 is quite effective in reducing the level of income inequality in the Central Java Province of Indonesia, which is able to reduce the Gini Coefficient of Central Java Province by -1.20%. The implementation of the BPNT program was able to make the expenditure of the lower class population increase faster than the expenditure of upper and middle class population. The implementation of the BPNT program changes the map of the income inequality level of 35 districts/cities in the Central Java Province of Indonesia but does not change the map of the level of income inequality between urban and rural areas in the Central Java Province of Indonesia. In addition, the implementation of the BPNT program in the Central Java Province of Indonesia has not been able to change the category of income inequality in the Central Java Province of Indonesia, namely that it remains in the moderate category. This study recommends improvements in terms of the target recipients of BPNT, the quality of the human resources of the companions, the time for receiving assistance, the quality of rice, and the readiness of e-warong in 35 districts/cities in the Province of Central Java, Indonesia.


2021 ◽  
Author(s):  
Jan Priesmann ◽  
Saskia Spiegelburg ◽  
Reinhard Madlener ◽  
Aaron Praktiknjo

Abstract Energy systems are decidedly the largest emitters of greenhouse gases. Therefore, transitioning them from fossil to renewable systems is a top priority for societies committed to reducing greenhouse gas emissions. However, such transitions involve substantial costs. In many cases, these costs are proportionally passed on to final energy consumers through levies on their electricity consumption. In our paper, we investigate the impacts of renewable support levies on social justice or, more specifically, on income inequality. For our study, we chose Germany where inflation-adjusted electricity prices for private households increased substantially because of such a levy for renewables. We base our analyses on representative household panel data with over 40,000 households from 2003 to 2018. Our results indicate that indiscriminate renewable support levies on electricity consumption increase income inequality and energy poverty. For our case in 2018, renewable support levies alone led to a relative increase of ~0.23% of the Gini coefficient and ~11.31% of the high cost low income (HCLI) energy poverty indicator measuring energy poverty intensity. Based on our findings, we propose a reform of the renewable support levy and analyze three options: (1) the abolition of the levy, (2) levies which are income-progressive proportionally to the income taxes, and (3) a high and flat levy in conjunction with an income-degressive compensation payment. Our ex-post analyses for 2018 indicate that a reformed levy system would have slightly decreased overall income inequality with relative decreases of ~0.23%, ~0.32%, and ~0.59% of the Gini coefficient for options (1), (2), and (3), respectively. But more importantly, such a system would have substantially decreased energy poverty by ~11.31%, ~30.45%, and ~31.45% for the HCLI energy poverty indicator for options (1), (2), and (3), respectively.


Sign in / Sign up

Export Citation Format

Share Document