Between 2010 and 2023, Brazil's data on the degree of inequality in wealth distribution based on the Gini coefficient reached 52. That year, Brazil was deemed one of 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 3 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 BR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 52.000 % in 2022. This records a decrease from the previous number of 52.900 % for 2021. Brazil BR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 56.400 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 63.300 % in 1989 and a record low of 48.900 % in 2020. Brazil BR: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Poverty and Inequality. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Brazil: Gini income inequality index: The latest value from 2022 is 52 index points, a decline from 52.9 index points in 2021. In comparison, the world average is 38.33 index points, based on data from 28 countries. Historically, the average for Brazil from 1981 to 2022 is 56.28 index points. The minimum value, 48.9 index points, was reached in 2020 while the maximum of 63.2 index points was recorded in 1989.

Brazil Gini Coefficient: Household Income: per Capita: North data was reported at 0.544 % in 2017. This records an increase from the previous number of 0.539 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: North data is updated yearly, averaging 0.542 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.544 % in 2017 and a record low of 0.539 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: North 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.

In 2023, the gini coefficient for urban areas in Brazil amounted to approximately 0.51 points. Between 2001 and 2023, the figure dropped by around 0.05 points, though the decline followed an uneven course rather than a steady trajectory.

In 2023, the gini coefficient for rural areas in Brazil was approximately 0.46 points. Between 2001 and 2023, the figure dropped by around 0.04 points, though the decline followed an uneven course rather than a steady trajectory.

Historical dataset showing Brazil income inequality - gini coefficient by year from N/A to N/A.

Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, 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 37 and 55 points according to the latest available data from the reporting period 2010-2023. 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.

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.

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.

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.

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.

ABSTRACT This paper analyzed the inequality of non-labor income shares in relation to total per capita household income (RDPC) based on data from the National Household Sample Survey (PNAD). To this end, the participation of these shares in RDPC formation, the concentration ratio, and the composition and concentration effects were estimated using the dynamic and static decomposition technique of the Gini index. Results suggest that 83.71% of total non-labor income is composed of retirement and pension income. Between 2001 and 2015, the fall in inequality associated with non-labor income was 42.36%, with the concentration effect having the largest share (35.91%). Of the shares analyzed, retirements and pensions of up to one minimum wage and government income transfers had the largest contributions to reduce inequality-11.91% and 15.92%, respectively. From 2012 to 2020, the results of the PNAD Contínua shows that retirements and pensions are regressive and that the Gini index, which had been growing since 2016, fell in 2020 due to the increased share of emergency aid in total income.

ABSTRACT This article presents an estimation of the Brazilian Gross Value Added (GVA) for 127 employment shares and 64 economic activities, based on the year of 2015. Continuous National Household Sample Survey (PNAD) microdata was reconciled with National Accounts data by means of the World Inequality Database (WID). Disaggregation was achieved for 64-economic-activity after applying a RAS biproportional balancing procedure, which considered, on the one hand, the distribution of GVA by activity of Brazilian Tables of Resources and Uses, and, on the other hand, the distribution by population shares from WID. From the results, it was possible to analyze the relative distribution of the employment shares in the value added for each and every economic activity, to construct a ranking of economic activities by degree of progressivity, to simulate the trajectory of inequality between 2012 and 2019 - assuming constant concentration ratios and changing the participation of each activity in the value added - and to calculate, separately for each final demand component and each economic activity, the Gini index that would prevail if the final demand were comprised of each component of the demand or of each economic activity exclusively.

Out of the G20 countries, South Africa, Brazil, and Turkey have the highest levels of income inequality, while France, Canada, and Germany have the lowest levels of inequality. Other G20 countries in the middle have Gini coefficients between 32.5 and 44.0. The Gini coefficient measures the level of income inequality worldwide, where a higher score indicates a higher level of income inequality.

Brazil Gini Coefficient: Household Income: per Capita: North: Roraima data was reported at 0.546 % in 2017. This records a decrease from the previous number of 0.547 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: North: Roraima data is updated yearly, averaging 0.546 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.547 % in 2016 and a record low of 0.546 % in 2017. Brazil Gini Coefficient: Household Income: per Capita: North: Roraima 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: North: Acre data was reported at 0.566 % in 2017. This records a decrease from the previous number of 0.575 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: North: Acre data is updated yearly, averaging 0.571 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.575 % in 2016 and a record low of 0.566 % in 2017. Brazil Gini Coefficient: Household Income: per Capita: North: Acre 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 file contains data on Gini coefficients, cumulative quintile shares, explanations regarding the basis on which the Gini coefficient was computed, and the source of the information. There are two data-sets, one containing the "high quality" sample and the other one including all the information (of lower quality) that had been collected.

The database was constructed for the production of the following paper:

Deininger, Klaus and Lyn Squire, "A New Data Set Measuring Income Inequality", The World Bank Economic Review, 10(3): 565-91, 1996.

This article presents a new data set on inequality in the distribution of income. The authors explain the criteria they applied in selecting data on Gini coefficients and on individual quintile groups’ income shares. Comparison of the new data set with existing compilations reveals that the data assembled here represent an improvement in quality and a significant expansion in coverage, although differences in the definition of the underlying data might still affect intertemporal and international comparability. Based on this new data set, the authors do not find a systematic link between growth and changes in aggregate inequality. They do find a strong positive relationship between growth and reduction of poverty.

Geographic coverage

In what follows, we provide brief descriptions of main features for individual countries that are included in the data-base. Without being comprehensive, these notes are intended to indicate some of the considerations underlying our decision to include or exclude certain observations.

Argentina Various permanent household surveys, all covering urban centers only, have been regularly conducted since 1972 and are quoted in a wide variety of sources and years, e.g., for 1980 (World Bank 1992), 1985 (Altimir 1994), and 1989 (World Bank 1992). Estimates for 1963, 1965, 1969/70, 1970/71, 1974, 1975, 1980, and 1981 (Altimir 1987) are based only on Greater Buenos Aires. Estimates for 1961, 1963, 1970 (Jain 1975) and for 1970 (van Ginneken 1984) have only limited geographic coverage and do not satisfy our minimum criteria.

Despite the many urban surveys, there are no income distribution data that are representative of the population as a whole. References to national income distribution for the years 1953, 1959, and 1961(CEPAL 1968 in Altimir 1986 ) are based on extrapolation from national accounts and have therefore not been included. Data for 1953 and 1961 from Weisskoff (1970) , from Lecaillon (1984) , and from Cromwell (1977) are also excluded.

Australia Household surveys, the result of which is reported in the statistical yearbook, have been conducted in 1968/9, 1975/6, 1978/9, 1981, 1985, 1986, 1989, and 1990.

Data for 1962 (Cromwell, 1977) and 1966/67 (Sawyer 1976) were excluded as they covered only tax payers. Jain's data for 1970 was excluded because it covered income recipients only. Data from Podder (1972) for 1967/68, from Jain (1975) for the same year, from UN (1985) for 78/79, from Sunders and Hobbes (1993) for 1986 and for 1989 were excluded given the availability of the primary sources. Data from Bishop (1991) for 1981/82, from Buhman (1988) for 1981/82, from Kakwani (1986) for 1975/76, and from Sunders and Hobbes (1993) for 1986 were utilized to test for the effect of different definitions. The values for 1967 used by Persson and Tabellini and Alesina and Rodrik (based on Paukert and Jain) are close to the ones reported in the Statistical Yearbook for 1969.

Austria: In addition to data referring to the employed population (Guger 1989), national household surveys for 1987 and 1991 are included in the LIS data base. As these data do not include income from self-employment, we do not report them in our high quality data-set.

Bahamas Data for Ginis and shares are available for 1973, 1977, 1979, 1986, 1988, 1989, 1991, 1992, and 1993 in government reports on population censuses and household budget surveys, and for 1973 and 1975 from UN (1981). Estimates for 1970 (Jain 1975), 1973, 1975, 1977, and 1979 (Fields 1989) have been excluded given the availability of primary sources.

Bangladesh Data from household surveys for 1973/74, 1976/77, 1977/78, 1981/82, and 1985/86 are available from the Statistical Yearbook, complemented by household-survey based information from Chen (1995) and the World Development Report. Household surveys with rural coverage for 1959, 1960, 1963/64, 1965, 1966/67 and 1968/69, and with urban coverage for 1963/64, 1965, 1966/67, and 1968/69 are also available from the Statistical yearbook. Data for 1963/64 ,1964 and 1966/67, (Jain 1975) are not included due to limited geographic coverage, We also excluded secondary sources for 1973/74, 1976/77, 1981/82 (Fields 1989), 1977 (UN 1981), 1983 (Milanovic 1994), and 1985/86 due to availability of the primary source.

Barbados National household surveys have been conducted in 1951/52 and 1978/79 (Downs, 1988). Estimates based on personal tax returns, reported consistently for 1951-1981 (Holder and Prescott, 1989), had to be excluded as they exclude the non-wage earning population. Jain's figure (used by Alesina and Rodrik) is based on the same source.

Belgium Household surveys with national coverage are available for 1978/79 (UN 1985), and for 1985, 1988, and 1992 (LIS 1995). Earlier data for 1969, 1973, 1975, 1976 and 1977 (UN 1981) refer to taxable households only and are not included.

Bolivia The only survey with national coverage is the 1990 LSMS (World Development Report). Surveys for 1986 and 1989 cover the main cities only (Psacharopoulos et al. 1992) and are therefore not included. Data for 1968 (Cromwell 1977) do not refer to a clear definition and is therefore excluded.

Botswana The only survey with national coverage was conducted in 1985-1986 (Chen et al 1993); surveys in 74/75 and 85/86 included rural areas only (UN 1981). We excluded Gini estimates for 1971/72 that refer to the economically active population only (Jain 1975), as well as 1974/75 and 1985/86 (Valentine 1993) due to lack of national coverage or consistency in definition.

Brazil Data from 1960, 1970, 1974/75, 1976, 1977, 1978, 1980, 1982, 1983, 1985, 1987 and 1989 are available from the statistical yearbook, in addition to data for 1978 (Fields 1987) and for 1979 (Psacharopoulos et al. 1992). Other sources have been excluded as they were either not of national coverage, based on wage earners only, or because a more consistent source was available.

Bulgaria: Data from household surveys are available for 1963-69 (in two year intervals), for 1970-90 (on an annual basis) from the Statistical yearbook and for 1991 - 93 from household surveys by the World Bank (Milanovic and Ying).

Burkina Faso A priority survey has been undertaken in 1995.

Central African Republic: Except for a household survey conducted in 1992, no information was available.

Cameroon The only data are from a 1983/4 household budget survey (World Bank Poverty Assessment).

Canada Gini- and share data for the 1950-61 (in irregular intervals), 1961-81 (biennially), and 1981-91 (annually) are available from official sources (Statistical Yearbook for years before 1971 and Income Distributions by Size in Canada for years since 1973, various issues). All other references seem to be based on these primary sources.

Chad: An estimate for 1958 is available in the literature, and used by Alesina and Rodrik and Persson and Tabellini but was not included due to lack of primary sources.

Chile The first nation-wide survey that included not only employment income was carried out in 1968 (UN 1981). This is complemented by household survey-based data for 1971 (Fields 1989), 1989, and 1994. Other data that refer either only to part of the population or -as in the case of a long series available from World Bank country operations- are not clearly based on primary sources, are excluded.

China Annual household surveys from 1980 to 1992, conducted separately in rural and urban areas, were consolidated by Ying (1995), based on the statistical yearbook. Data from other secondary sources are excluded due to limited geographic and population coverage and data from Chen et al (1993) for 1985 and 1990 have not been included, to maintain consistency of sources..

Colombia The first household survey with national coverage was conducted in 1970 (DANE 1970). In addition, there are data for 1971, 1972, 1974 CEPAL (1986), and for 1978, 1988/89, and 1991 (World Bank Poverty Assessment 1992 and Chen et al. 1995). Data referring to years before 1970 -including the 1964 estimate used in Persson and Tabellini were excluded, as were estimates for the wage earning population only.

Costa Rica Data on Gini coefficients and quintile shares are available for 1961, 1971 (Cespedes 1973),1977 (OPNPE 1982), 1979 (Fields 1989), 1981 (Chen et al 1993), 1983 (Bourguignon and Morrison 1989), 1986 (Sauma-Fiatt 1990), and 1989 (Chen et al 1993). Gini coefficients for 1971 (Gonzalez-Vega and Cespedes in Rottenberg 1993), 1973 and 1985 (Bourguignon and Morrison 1989) cover urban areas only and were excluded.

Cote d'Ivoire: Data based on national-level household surveys (LSMS) are available for 1985, 1986, 1987, 1988, and 1995. Information for the 1970s (Schneider 1991) is based on national accounting information and therefore excluded

Cuba Official information on income distribution is limited. Data from secondary sources are available for 1953, 1962, 1973, and 1978, relying on personal wage income, i.e. excluding the population that is not economically active (Brundenius 1984).

Czech Republic Household surveys for 1993 and 1994 were obtained from Milanovic and Ying. While it is in principle possible to go back further, splitting national level surveys for the former Czechoslovakia into their independent parts, we decided not to do so as the same argument could be used to

Based on the degree of inequality in wealth distribution measured by the Gini coefficient, income inequality in Latin America and the Caribbean decreased significantly between 2002 and 2012, falling from a record of 52.8 index points to 47. However, from 2012 onwards the index stagnated above 46 points, which implies that inequality remains high in the region. In 2018, Brazil ranked as the Latin American country with the largest income inequality.

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 zero represents absolute equality, whereas 100 would be the highest possible degree of inequality.

Brazil Gini Coefficient: Household Income: per Capita: South data was reported at 0.477 % in 2017. This records an increase from the previous number of 0.473 % for 2016. Brazil Gini Coefficient: Household Income: per Capita: South data is updated yearly, averaging 0.475 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 0.477 % in 2017 and a record low of 0.473 % in 2016. Brazil Gini Coefficient: Household Income: per Capita: South 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.