As of 2022, Portugal was the EU country with the most respondents agreeing that income differences between citizens have become too great, with almost ** percent of respondents either agreeing or strongly agreeing with the statement. Other countries which had high shares of respondents agreeing with the statement included Bulgaria, Hungary, and Lithuania, all post-communist countries which have experienced sharp upticks in inequality over recent decades. Interestingly, in Germany there is a relatively large divergence between eastern and western Germany on this issue, as the former communist East had the joint highest amount of people agreeing, with almost ********** strongly agreeing. On the other hand in the West, * percent less of respondents agreed with the statement, illustrating that 33 years since German reunification, there are still significant differences in opinion, especially concerning inequality. The three countries which agree with the statement the least were the three Nordic member states of the EU, Denmark, Finland, and Sweden. Their disagreement with the statement is likely related to the tradition of the 'Nordic model' of the welfare state in these countries, which provides comprehensive welfare support to citizens and acts to reduce inequalities. Whilst this model has come under pressure in recent decades, it is still clear tha it has resulted in the citizens of these countries viewing inequality as a much lesser problem than in other EU member states.

As of 2021, the countries in Europe with the greatest share of national wealth taken by the top 10 percent of wealthy people were Russia, Turkey, and Hungary, with over two-thirds of wealth in Russia being owned by the wealthiest decile. On the other hand, the Netherlands, Slovakia, and Denmark were the countries with the smallest share of national wealth going to the top 10 percent, with more than half of wealth in the Netherlands going to the bottom 90 percent. Ireland, Poland, and Greece stand out, as in these countries the 50 percent of people who own the least wealth in fact have negative net wealth, meaning that the value of their debt is greater than the value of their gross wealth.

The average for 2021 based on 31 countries was 31.37 index points. The highest value was in Turkey: 44.4 index points and the lowest value was in Slovakia: 24.1 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

This article analyzes the impact of tax policy on income inequality in the European Union (EU). Each EU member-state has adopted a distinct set of fiscal policies. Although most member-states have coordinated their tax systems to promote economic growth, EU countries hold politically divergent views about income inequality and the power of taxation to redress inequality. This research applies linear regression methods incorporating regularization as well as fixed and random effects. Stacking generalization produces a composite model that dramatically improves predictive accuracy while aggregating causal inferences from simpler models. Social contributions, income taxes, and consumption taxes ameliorate inequality. Government spending, however, exacerbates inequality.

The ratio of total income received by the 20 % of the population with the highest income (top quintile) to that received by the 20 % of the population with the lowest income (lowest quintile). Income must be understood as equivalised disposable income. Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

In 2024, the European Union scored 88.6 points for health in terms of gender equality. The most unequal indicator was power, with an index of 61.4. The Gender Equality Index benchmarks national gender gaps on economic, political, education, and health-based criteria among the countries of the European Union. A score of 0 indicates that there is no gender equality, while 100 points indicate that gender equality is achieved. Sweden was the most equal country among the 28 countries of the European Union that year.

Policies attempting to mitigate the effects of urban inequality, often disregard affected citizens’ experiences, and thus fail to achieve maximum impact. By incorporating these perspectives into the policy design process, the project "Urban PoLicy Innovation to address inequality with and for Future generaTions" (UPLIFT), funded under the EU Horizon 2020 program aims to find innovative interventions in a bottom-up approach. The aims of UPLIFT project are to understand patterns and trends of inequality across Europe and to understand how individuals experience and adapt to inequality through participatory research. Moreover the project will together with the communities in four locations, co-design a policy tool aimed at addressing and reducing inequality and socio-economic divisions. The activity and results of the project can be followed at https://www.uplift-youth.eu/. Deliverable 2.4 (Synthesis report: socioeconomic inequalities in different urban contexts) is the final deliverable of work package 2 of the UPLIFT project, which aims to synthetize the main outcomes of the urban reports that described the policy environment around vulnerable individuals in the fields of education, employment and housing in 16 functional urban areas of the EU. In addition section 6.2 "Statistical analysis of linkages between economic development of cities, their public policy performance and inequality outcomes" of the report provides a statistical analysis of how local economic competitiveness and the local policy context affect urban deprivation and inequality among the young in European cities. The analysis is based on data from 2006, 2009, 2012, 2015 and 2019 of the Quality of Life in European Cities survey.

Why is the difference in redistribution preferences between the rich and the poor high in some countries and low in others? In this paper we argue that it has a lot to do with the rich and very little to do with the poor. We contend that while there is a general relative income effect on redistribution preferences, the preferences of the rich are highly dependent on the macro-level of inequality. The reason for this effect is not related to immediate tax and transfer considerations but to a negative externality of inequality: crime. We will show that the rich in more unequal regions in Western Europe are more supportive of redistribution than the rich in more equal regions because of their concern with crime. In making these distinctions between the poor and the rich, the arguments in this paper challenge some influential approaches to the politics of inequality.

Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of existing inequality datasets: greater coverage across countries and over time is available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to overcome these limitations. A custom missing-data algorithm was used to standardize the United Nations University's World Income Inequality Database and data from other sources; data collected by the Luxembourg Income Study served as the standard. The SWIID provides comparable Gini indices of gross and net income inequality for 192 countries for as many years as possible from 1960 to the present along with estimates of uncertainty in these statistics. By maximizing comparability for the largest possible sample of countries and years, the SWIID is better suited to broadly cross-national research on income inequality than previously available sources: it offers coverage double that of the next largest income inequality dataset, and its record of comparability is three to eight times better than those of alternate datasets.

The indicator is a measure of the inequality of income distribution. It is calculated as the ratio of total income received by the 20 % of the population with the highest income (the top quintile) to that received by the 20 % of the population with the lowest income (the bottom quintile).

The research, which dealt with the problem of social inequality in students, originated from the Faculty of Economics Boris Kidrič in Ljubljana. At the beginning of the academic year 1981/82, which aimed to shed light primarily on the socio-economic situation of their students, it was carried out when new students were enrolled at the Faculty of Economics. This was based on the assumption that students were at risk in the difficult economic situation. In fact, students' incomes corresponded only to "hand-to-mouth" livelihoods. However, since the student is economically dependent on his parents, because he lives in a foreign place and has to eat elsewhere, it was necessary to take into account that the student’s (ability to) save is therefore very small. Our faculty (FSPN) also recorded an encouraging example next year, as we did not care about the conditions in which our students live and work. Greater sociological emphasis was placed on the entire research, especially on the problem of social inequality. On the other hand, we were interested in the material conditions of students and factors related to study success, which affect the overall study success. The underlying problem is therefore how social inequality affects the attainment of higher education, which is at the same time a process of restoring inequality. From a practical point of view, we were also interested in preventing the reoccurrence of inequalities, where scholarships in particular play an important role. The research was carried out in such a way that the data were comparable with the data of the Faculty of Economics Boris Kidrič.

The World Income Inequality database is part of the United Nations University World Institute for Development Economics Research (UNU-WIDER) and contains information on income inequality for 189 developed, developing and transition countries.

The operation Poverty and Social Inequality Survey reports on the situation regarding poverty in households in the Basque Country. The objective is the knowledge, study and evaluation of the different situations of poverty, as well as the obtaining and analysis of parameters such as indicators of poverty of maintenance and accumulation, indicators of precariousness, social inequality or covert poverty.

In 2023, Bulgaria had the highest Gini Index score in the European Union at 37.2, implying that the country had the highest level of inequality among European countries. The Gini Index is a measure of inequality within economies, a lower score indicates more equality, and a higher score less equality. Slovakia had the lowest score among EU countries for 2023 with a score of 21.6, suggesting that it is the most egalitarian society in Europe.

The Leiden LIS Sectoral Income Inequality Dataset provides information on multiple indicators of earnings inequality and employment within 9 economic sectors and 12 subsectors for 12 developed countries for the period 1969-2005. The dataset is drawn upon microdata from the Luxembourg Income Study (LIS).

This article advances the literature on the spatial patterns of EU support by arguing that the relationship between regional inequality and EU trust is not linear. We posit that, to fully understand this relationship, we should systematically investigate three dimensions of regional inequality, i.e., regional wealth status, regional wealth growth, and regional wealth growth at different levels of wealth status. Using individual-level survey data for EU27 countries and the UK from 11 Eurobarometer waves (2015-2019), we show that a non-linear association exists whereby poor and rich European regions tend to trust the EU more compared to middle-income regions, and that within-region over-time growth is associated with higher levels of EU trust. We demonstrate that the association between growth and EU trust is more pronounced among poor and middle-income regions compared to rich regions. Our findings have implications about the nature of public Euroscepticism and the ways in which to address it.

The Layer shows the households disposable income at the nation level for the household. The frequency is annual. The Unit of measure is GINI. GINI is a measure of statistical dispersion intended to represent the income inequality or wealth inequality within a nation or any other group of people. The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income). A Gini coefficient of zero expresses perfect equality, where all values are the same (for example, where everyone has the same income). A Gini coefficient of one (or 100%) expresses maximal inequality among values (e.g., for a large number of people where only one person has all the income or consumption and all others have none, the Gini coefficient will be nearly one).

Most equivalence scales that are applied in research on inequality do not depend on income, even though there is strong empirical evidence that equivalence scales are actually income-dependent. This paper explores the consistency of results derived from income-independent and income-dependent scales. We show that applying income-independent scales when income-dependent scales would be appropriate leads to violations of the transfer principle. Surprisingly, there are some exceptions, but these require unrealistic and strong assumptions. Thus, the use of income-dependent equivalence scales almost always leads to different assessments of inequality than the use of income-independent equivalence scales. Two examples illustrate our findings.

The Gini coefficient is a measure of income inequality, where a value of 0 would indicate perfect equality in the income distribution (i.e. everyone earns the same) and a value of 100 would indicate perfect inequality (one person earns everything). The Gini coefficient in both the European Union as a whole, as well as the Eurozone currency area, has been on a downward trajectory since its previous peak in 2014, when it reached a peak of 30.9 in both. As of 2023, the Gini coefficient in the EU and Eurozone has hit a new low, with values of 29.6 and 29.8 respectively, indicating that income inequality has fallen in the blocs over the past decade.

The Gender Equality Index was initially created by the European Institute for Gender Equality. It measures how far (or close) the EU-27 and its Member States were from achieving complete gender equality in 2010. It provides results at both Member States and EU-27 level. It synthesises the complexity of gender equality in an easily interpretable measure.The Index consists of six core domains:workmoneyknowledgetimepowerhealthFor this reuse, we did not took the two satellite domains (intersecting inequalities and violence) into account. Feel free to look at the original dataset to explore these two additional categories. The Gender Equality Index assigns scores for Member States, between 1, total inequality and 100, full equality. It also provides results for each domain and sub-domain.