Back to preview
  • GINI coefficient (income distribution) GINI coefficient (income distribution) (Line chart)
  • GINI coefficient (income distribution) GINI coefficient (income distribution) (Map)
Data set notes
European Health for All database

Indicators: 565
Updated: 18 October 2024

The following abbreviations are used in the indicator titles:
•    SDR: age-standardized death rates (see HFA-DB user manual/Technical notes, page 13, for details)
•    FTE: full-time equivalent
•    PP: physical persons
•    PPP$: purchasing power parities expressed in US $, an internationally comparable scale reflecting the relative domestic purchasing powers of currencies.

Joint Monitoring Framework (JMF)


The joint monitoring framework (JMF) is used for reporting on indicators under three monitoring frameworks: the Sustainable Development Goals (SDGs), Health 2020 and the Global Action Plan for the Prevention and Control of Noncommunicable Diseases (NCDs) 2013–2020. The Regional Committee for Europe adopted the JMF in September 2018.

The majority of JMF indicators in the Gateway are linked to existing databases in the Gateway.

Background documents

EUR/RC68/10 Rev.1 Briefing note on the expert group deliberations and recommended common set of indicators for a joint monitoring framework
http://www.euro.who.int/en/about-us/governance/regional-committee-for-europe/past-sessions/68th-session/documentation/working-documents/eurrc6810-

EUR/RC68(1): Joint monitoring framework in the context of the roadmap to implement the 2030 Agenda for Sustainable Development, building on Health 2020, the European policy for health and well-being
http://www.euro.who.int/en/about-us/governance/regional-committee-for-europe/past-sessions/68th-session/documentation/resolutions/eurrc68d1

Developing a common set of indicators for the joint monitoring framework for SDGs, Health 2020 and the Global NCD Action Plan (2017)
http://www.euro.who.int/en/health-topics/health-policy/health-2020-the-european-policy-for-health-and-well-being/publications/2018/developing-a-common-set-of-indicators-for-the-joint-monitoring-framework-for-sdgs,-health-2020-and-the-global-ncd-action-plan-2017
Indicator notes

The methodology behind the GINI coefficient is rooted in the Lorenz curve, a graphical representation of income or wealth distribution. It's here that the GINI coefficient graph and GINI index graph become indispensable visual tools. They plot the cumulative percentage of total or national income against the population, making it easier to grasp the depths of inequality in incomes.

The GINI coefficient, often referred to as the GINI index or GINI score, is a measure of income inequality or wealth inequality within a country. This metric, conceptualized by the Italian statistician Corrado Gini, is extensively utilized in the field of science for its ability to depict the income gap within nations. This Gini indicator spans a range from 0 to 100, with 0 representing perfect equality and 100 showcasing maximum inequality.

What is a Gini Coefficient

The global indicator used as well by  European countries, the GINI coefficient offers a standardized measure to assess income distribution disparities, facilitating comparisons across different nations. This measure, upheld by organizations like the World Bank, monitors income inequality trends and influences policies centered on narrowing the income gap. Here, individual factors and national strategies play a significant role.

While the GINI coefficient measures inequality, it doesn't signify the absolute levels of income or wealth. For instance, two nations might have the same GINI coefficient, yet their national income levels can differ. This is where understanding the gini by country is pivotal.

GINI coefficient (income distribution)

Indicator code: GINI

Feature of Gini Index

The GINI coefficient's features, like the gini index map, make it an invaluable tool for gauging income distribution. This measure focuses on the distribution rather than absolute income levels. It gives insight into the disparity levels in countries irrespective of their economic growth stage. Its foundation on the Lorenz curve, particularly the GINI coefficient graph, enables stakeholders to visually understand and address inequality in incomes.

Limitations and Exceptions of Gini Ratio

While the GINI coefficient is prominent in capturing the essence of income disparity, it does have limitations. It solely represents the financial aspect, sidelining other inequality facets like education and health disparities. Moreover, in regions with a pronounced informal economy, the gini index by country might not fully encapsulate the true income disparity.

Countries with the Highest and Lowest Gini Coefficients

When looking at the countries with the highest GINI coefficients by country, some notable examples include South Africa, Namibia, and Eswatini. These countries have consistently ranked among the countries with the highest income inequality in the world. High levels of income inequality can have serious social and economic consequences, including lower levels of social mobility, increased poverty rates, and heightened social tensions.

On the other end of the spectrum, countries with the lowest GINI coefficients include countries like Denmark, Sweden, and Norway. These countries have consistently ranked among the countries with the lowest income inequality in the world. Low levels of income inequality are often associated with higher levels of social cohesion, better access to social services, and overall better quality of life for all citizens.

It is important to note that the GINI coefficient is not the only measure of income distribution and should be used in conjunction with other measures and indicators to obtain a comprehensive understanding of inequality. Different measures may highlight different aspects of inequality and provide valuable insights for policymakers and researchers.

In conclusion, the GINI coefficient is a widely used measure of income inequality that provides a standardized way to assess the degree of income distribution within a country. It is a simple and easy-to-understand measure that can be readily calculated from income data. However, it is important to remember that the GINI coefficient measures inequality in the distribution of income or wealth and does not capture other dimensions of inequality. It is just one useful tool among many that policymakers and researchers can use to analyze and address income inequality.

GINI coefficient rates for (AUT, BEL, BUL, SWI, CYP, CZH, DEU, DEN, EST, SPA, FIN, FRA, CRO, HUN, IRE, ICE, ITA, LTU, LUX, LVA, FYM, MAT, NET, NOR, POL, POR, ROM, SRB, SWE, SVN, SVK, TUR) have been extracted from Eurostat. Rates for (AND, ALB, ARM, AZE, BIH, BLR, UNK, GEO, GRE, ISR, KGZ, KAZ, MON, MDA, MNE, RUS, SMR, TJK, TKM, UKR, UZB) have been extracted from the World Bank. World Bank estimates are in average 7% higher than Eurostat rates. Rates starting in 1995 have been included.

Data source: Gini coefficient of equalized disposable income (source: SILC, Eurostat) and GINI index (World Bank estimate).

Country/Area notes
No information