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).

In Brazil, from the total national wealth share in 2021, nearly 80 percent belonged to the top ten percent. Almost half of Brazil's wealth was held by top one percent. On the other hand, the bottom 50 percent had a total of -0.4 percent, that is, on average, this group had more debts than assets. That year, the average personal wealth of the bottom 50 percent was valued at -300 euros.

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.

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.

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

Using a factor decomposition of the Gini coefficient, we measure the contribution to inequality of direct monetary income flows to and from the Brazilian State. The income flows from the State include public sector workers' earnings, Social Security pensions, unemployment benefits, and Social Assistance transfers. The income flows to the State comprise direct taxes and employees' social security contributions. Data come from the Brazilian POF 2008–09. We do not measure indirect contributions to inequality of subsidies granted to and taxation of companies, nor the in-kind provision of goods and services. The results indicate that the State contributes to a large share of family per capita income inequality. Incomes associated with work in the public sector—wages and pensions—are concentrated and regressive. Components related to the private sector are also concentrated, but progressive. Contrary to what has been found in European countries, public spending associated with work and social policies is concentrated in an elite group of workers and, taken as a whole, tends to increase income inequality. Redistributive mechanisms that could reverse this inequality, such as taxes and social assistance, are very progressive but proportionally small. Consequently, their effect is completely offset by the regressive income flows from the State.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Brazil, IN, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,831, while the mean income for the highest quintile (20% of households with the highest income) is 165,454. This indicates that the top earners earn 11 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 300,151, which is 181.41% higher compared to the highest quintile, and 2023.81% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil median household income. You can refer the same here

In 2023, the percentage of income held by the richest 20 percent of the population in Brazil stood at 56.6 percent. Between 1981 and 2023, the figure dropped by 5.7 percentage points, though the decline followed an uneven course rather than a steady trajectory.

Brazil BR: Income Share Held by Highest 10% data was reported at 41.000 % in 2022. This records a decrease from the previous number of 41.600 % for 2021. Brazil BR: Income Share Held by Highest 10% data is updated yearly, averaging 44.550 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 51.100 % in 1989 and a record low of 39.500 % in 2020. Brazil BR: Income Share Held by Highest 10% 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. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.;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).

Abstract Contrary to the huge development of the Brazilian economy from the post-war to the end of the seventies, the eighties signified the rupture of this cycle and the combination of a chronic inflationary process, the economic stagnation and the worsening of income inequality. These factors together have not revealed to be neutral concerning the distributive aspect. Between 1981 and 1989, the income of the 10 per cent richer increased 14,2 per cent, while the income of the 20 per cent poorer decreased 26 per cent. This work presents some international comparisons, even on the functional as well as on the personal distribution of income and concludes that this distribution becomes a fundamental aspect to the stabilization and to the economic-social development recovering.

The statistic shows the wealth distribution in Brazil in 2015, based on share of national income. According to the source, the richest * percent of the Brazilian population concentrated ** percent of the country's national income.

Brazil BR: Income Share Held by Third 20% data was reported at 12.300 % in 2022. This records an increase from the previous number of 12.100 % for 2021. Brazil BR: Income Share Held by Third 20% data is updated yearly, averaging 11.000 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 12.900 % in 2020 and a record low of 8.900 % in 1989. Brazil BR: Income Share Held by Third 20% 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. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.;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).

Abstract The paper presents the functional income distribution for the Brazilian economy between 1947 and 2019. It is the first study that computes the functional income distribution for the whole period with official Brazilian national accounts. The wage share increased, the share of mixed earnings declined, while the labour share and the profit share were trendless between 1947 and 2019. The cyclical movements of the functional income distribution were driven by economic and political factors in Brazil.

Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 3.800 % in 2015. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 3.800 % from Dec 2015 (Median) to 2015, with 1 observations. The data reached an all-time high of 3.800 % in 2015 and a record low of 3.800 % in 2015. Multidimensional Poverty Headcount Ratio: UNDP: % of total population 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. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

Brazil BR: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data was reported at 0.990 % in 2022. Brazil BR: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data is updated yearly, averaging 0.990 % from Dec 2022 (Median) to 2022, with 1 observations. The data reached an all-time high of 0.990 % in 2022 and a record low of 0.990 % in 2022. Brazil BR: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate 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. The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The coverage and quality of the 2017 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2017 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Income share held by third 20% of Brazil grew by 1.63% from 12.30 % in 2022 to 12.50 % in 2023. Since the 6.20% drop in 2021, income share held by third 20% climb by 3.31% in 2023. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Brazil. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Brazil, the median income for all workers aged 15 years and older, regardless of work hours, was $40,771 for males and $23,384 for females.

These income figures highlight a substantial gender-based income gap in Brazil. Women, regardless of work hours, earn 57 cents for each dollar earned by men. This significant gender pay gap, approximately 43%, underscores concerning gender-based income inequality in the city of Brazil.

- Full-time workers, aged 15 years and older: In Brazil, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,489, while females earned $38,980, leading to a 30% gender pay gap among full-time workers. This illustrates that women earn 70 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Brazil.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil median household income by race. You can refer the same here

We document a large decrease in earnings inequality in Brazil between 1996 and 2012. Using administrative linked employer-employee data, we fit high-dimensional worker and firm fixed-effects models to understand the sources of this decrease. Firm effects account for 40 percent of the total decrease and worker effects for 29 percent. Changes in observable worker and firm characteristics contributed little to these trends. Instead, the decrease is primarily due to a compression of returns to these characteristics, particularly a declining firm productivity-pay premium. Our results shed light on potential drivers of earnings inequality dynamics.

Brazil BR: Income Share Held by Lowest 10% data was reported at 1.200 % in 2022. This records an increase from the previous number of 1.000 % for 2021. Brazil BR: Income Share Held by Lowest 10% data is updated yearly, averaging 0.900 % from Dec 1981 (Median) to 2022, with 38 observations. The data reached an all-time high of 1.600 % in 2020 and a record low of 0.600 % in 1989. Brazil BR: Income Share Held by Lowest 10% 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. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.;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).