Between 2010 and 2022, Brazil's data on the degree of inequality in wealth distribution based on the Gini coefficient reached 52.9. That year, Brazil was deemed the most unequal country in Latin America. Prior to 2010, wealth distribution in Brazil had shown signs of improvement, with the Gini coefficient decreasing in the previous three reporting periods.

The Gini coefficient measures the deviation of the distribution of income (or consumption) among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality.

Brazil Gini Coefficient: Household Income: per Capita: Northeast: Bahia data was reported at 0.599 % in 2017. This records an increase from the previous number of 0.548 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Bahia data is updated yearly, averaging 0.574 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.599 % in 2017 and a record low of 0.548 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Bahia data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

Based on the degree of inequality in income distribution measured by the Gini coefficient, Brazil was the most unequal country in Latin America as of 2022. Brazil's Gini coefficient amounted to 52.9. Dominican Republic recorded the lowest Gini coefficient at 38.5, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America.

The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time.

What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 38 and 54 points according to the latest available data from the reporting period 2010-2021. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

In 2023, the gini coefficient for urban areas in Brazil did not change in comparison to the previous observation. The gini coefficient for urban areas remained at 0.51 points. For more insights about the gini coefficient for urban areas consider different countries: In 2023, in comparison to Brazil, the gini coefficient in Costa Rica was lower, while it was higher in Colombia.

Brazil Gini Coefficient: Household Income: per Capita: Southeast: Rio de Janeiro data was reported at 0.521 % in 2017. This records a decrease from the previous number of 0.524 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Southeast: Rio de Janeiro data is updated yearly, averaging 0.522 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.524 % in 2016 and a record low of 0.521 % in 2017. Brazil Gini Coefficient: Household Income: per Capita: Southeast: Rio de Janeiro data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

The gini coefficient for rural areas in Brazil decreased by 0.02 points (-4.17 percent) in 2023 in comparison to the previous observation.

Brazil Gini Coefficient: Household Income: per Capita: Northeast: Ceará data was reported at 0.560 % in 2017. This records an increase from the previous number of 0.553 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Ceará data is updated yearly, averaging 0.556 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.560 % in 2017 and a record low of 0.553 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Ceará data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

Brazil Gini Coefficient: Household Income: per Capita: Central West: Mato Grosso data was reported at 0.469 % in 2017. This records an increase from the previous number of 0.457 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Central West: Mato Grosso data is updated yearly, averaging 0.463 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.469 % in 2017 and a record low of 0.457 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: Central West: Mato Grosso data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

Brazil Gini Coefficient: Household Income: per Capita: Southeast: Minas Gerais data was reported at 0.506 % in 2017. This records an increase from the previous number of 0.504 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Southeast: Minas Gerais data is updated yearly, averaging 0.505 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.506 % in 2017 and a record low of 0.504 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: Southeast: Minas Gerais data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

Abstract This paper analyzes how the earnings of women and men affect the per capita household income (PCHI) distribution in Brazil, highlighting the individual earnings of the wife and husband of the couples, which include the household´s reference person. For this it is relevant to analyze what happens with the correlation between the husband´s and wife´s schooling, since level of schooling is a basic determinant of their earnings. Income from pensions is also analyzed, distinguishing income received by the husband, the wife, other men and other women. Data from a National Annual Household Survey for the period 1992-2015 are used. The correlation between the husband´s and wife´s schooling in 2015 is lower than in 1995. Decomposing the reduction of the Gini index from 1995 to 2015 (ΔG = -0,086), it is verified that the four components related to earnings and the four components formed by pensions contributed to the reduction in inequality.

Brazil Gini Coefficient: Working Age Population: Southeast: Rio de Janeiro data was reported at 0.465 % in 2017. This records a decrease from the previous number of 0.484 % for 2016. Brazil Gini Coefficient: Working Age Population: Southeast: Rio de Janeiro data is updated yearly, averaging 0.475 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.484 % in 2016 and a record low of 0.465 % in 2017. Brazil Gini Coefficient: Working Age Population: Southeast: Rio de Janeiro data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF002: Gini Coefficient: Working Age Population: by Region and State.

Income InequalityThe level of income inequality among households in a county can be measured using the Gini index. A Gini index varies between zero and one. A value of one indicates perfect inequality, where only one household in the county has any income. A value of zero indicates perfect equality, where all households in the county have equal income.The United States, as a country, has a Gini Index of 0.47 for this time period. For comparision in this map, the purple counties have greater income inequality, while orange counties have less inequality of incomes. For reference, Brazil has an index of 0.58 (relatively high inequality) and Denmark has an index of 0.24 (relatively low inequality).The 5-year Gini index for the U.S. was 0.4695 in 2007-2011 and 0.467 in 2006-2010. Appalachian Regional Commission, September 2013Data source: U.S. Census Bureau, 5-Year American Community Survey, 2006-2010 & 2007-2011

Brazil Gini Coefficient: Household Income: per Capita: Northeast: Paraíba data was reported at 0.563 % in 2017. This records an increase from the previous number of 0.540 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Paraíba data is updated yearly, averaging 0.551 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.563 % in 2017 and a record low of 0.540 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: Northeast: Paraíba data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

The gini coefficient for rural areas in Peru increased by 0.01 points (+2.63 percent) compared to the previous observation. In total, the gini coefficient amounted to 0.39 points in 2023. This increase was preceded by a declining gini coefficient.For more insights about the gini coefficient for rural areas consider different countries: In 2023, in comparison to Peru, the gini coefficient in Brazil was higher, while it was lower in the Dominican Republic.

Brazil Gini Coefficient: Household Income: per Capita: North: Amazonas data was reported at 0.604 % in 2017. This records an increase from the previous number of 0.572 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: North: Amazonas data is updated yearly, averaging 0.588 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.604 % in 2017 and a record low of 0.572 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: North: Amazonas data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF003: Gini Coefficient: Household Income: by Region.

Out of the G20 countries, South Africa, Brazil, and Mexico have the highest levels of income inequality while France, the Republic of Korea, and Germany have the lowest levels of inequality. Other G20 countries in the middle have Gini coefficients between 32.5 and 42.0. The Gini coefficient measures the level of income inequality worldwide, where a higher score indicates a higher level of income inequality.

The gini coefficient for urban areas in El Salvador increased by 0.02 points (+5.26 percent) compared to the previous observation. In total, the gini coefficient amounted to 0.4 points in 2023. This increase was preceded by a declining gini coefficient.For more insights about the gini coefficient for urban areas consider different countries: In 2023, in comparison to El Salvador, the gini coefficient in Colombia as well as in Brazil was higher.

Brazil Gini Coefficient: Working Age Population: Central West: Mato Grosso do Sul data was reported at 0.480 % in 2017. This records an increase from the previous number of 0.470 % for 2016. Brazil Gini Coefficient: Working Age Population: Central West: Mato Grosso do Sul data is updated yearly, averaging 0.475 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.480 % in 2017 and a record low of 0.470 % in 2016. Brazil Gini Coefficient: Working Age Population: Central West: Mato Grosso do Sul data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAF002: Gini Coefficient: Working Age Population: by Region and State.

In 2023, the gini coefficient for urban areas in Paraguay did not change in comparison to the previous observation. The gini coefficient for urban areas remained at 0.43 points. For more insights about the gini coefficient for urban areas consider different countries: In 2023, in comparison to Paraguay, the gini coefficient in the Dominican Republic was lower, while it was higher in Brazil.

This data file includes the Gini coefficient calculated for different wealth welfare aggregates constructed for all Luxembourg Wealth Study (LWS) datasets in all waves (as of March 2022). It includes Gini coefficients calculated on: • Disposable Net Worth • Value of Principal residence • Financial Assets

This project sought to renew the ESRC's invaluable financial support to LIS (formerly the Luxembourg Income Study) for a period of five more years. LIS is an independent, non-profit cross-national data archive and research institute located in Luxembourg. LIS relies on financial contributions from national science foundations, other research institutions and consortia, data-providing agencies, and supranational organisations to support data harmonisation and enable free and unlimited data access to researchers in the participating countries and to students world-wide. LIS' primary activity is to make harmonised household microdata available to researchers, thus enabling cross-national, interdisciplinary primary research into socio-economic outcomes and their determinants. Users of the Luxembourg Income Study Database and Luxembourg Wealth Study Database come from countries around the globe, including the UK. LIS has four goals: 1) to harmonise microdatasets from high- and middle-income countries that include data on income, wealth, employment, and demography; 2) to provide a secure method for researchers to query data that would otherwise be unavailable due to country-specific privacy restrictions; 3) to create and maintain a remote-execution system that sends research query results quickly back to users at off-site locations; and 4) to enable, facilitate, promote and conduct crossnational comparative research on the social and economic wellbeing of populations across countries. LIS contains the Luxembourg Income Study (LIS) Database, which includes income data, and the Luxembourg Wealth Study (LWS) Database, which focuses on wealth data. LIS currently includes microdata from 46 countries in Europe, the Americas, Africa, Asia and Australasia. LIS contains over 250 datasets, organised into eight time "waves," spanning the years 1968 to 2011. Since 2007, seventeen more countries have been added to LIS, including the BRICS countries (Brazil, Russia, India, China, South Africa), Japan, South Korea and a number of other Latin American countries. LWS contains 20 wealth datasets from 12 countries, including the UK, and covers the period 1994 to 2007. All told, LIS and LWS datasets together cover 86% of world GDP and 64% of world population. Users submit statistical queries to the microdatabases using a Java-based job submission interface or standard email. The databases are especially valuable for primary research in that they offer access to cross-national data at the micro-level - at the level of households and persons. Users are economists, sociologists, political scientists, and policy analysts, among others, and they employ a range of statistical approaches and methods. LIS also provides extensive documentation - metadata - for both LIS and LWS, concerning technical aspects of the survey data, the harmonisation process, and the social institutions of income and wealth provision in participating countries. In the next five years, for which support is sought, LIS will: - expand LIS, adding Waves IX (2013) and X (2016), and add new middle-income countries; - develop LWS, adding another wave of datasets to existing countries; acquire new wealth datasets for 14 more countries in cooperation with the European Central Bank (based on the Household Finance and Consumption Survey); - create a state-of-the-art metadata search and storage system; - maintain international standards in data security and data infrastructure systems; - provide high-quality harmonised household microdata to researchers around the world; - enable interdisciplinary cross-national social science research covering 45+ countries, including the UK; - aim to broaden its reach and impact in academic and non-academic circles through focused communications strategies and collaborations.