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.

In 2022, the percentage of income held by the richest 20 percent of the population in Brazil remained nearly unchanged at around 56.9 percent. With a decline of 0.6 percentage points (-1.04 percent), there is no significant change to 2021. These figures refer to the share of total income held by the highest 20 percent of earners in a given population.Find more statistics on other topics about Brazil with key insights such as poverty headcount ratio at national poverty lines.

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).

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

Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 2.040 % in 2017. This records an increase from the previous number of 2.030 % for 2008. Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 2.030 % from Dec 1996 (Median) to 2017, with 3 observations. The data reached an all-time high of 2.040 % in 2017 and a record low of 1.920 % in 1996. Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % 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. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

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/);;

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Brazil: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 140(4.03%) households where the householder is under 25 years old, 1,151(33.13%) households with a householder aged between 25 and 44 years, 1,096(31.55%) households with a householder aged between 45 and 64 years, and 1,087(31.29%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Brazil, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 age. You can refer the same here

In 2024, the national gross income per capita in Brazil amounted to around 9,950 U.S. dollars, an increase from 9,310 dollars per person in the previous year. Gross national income (GNI) is the aggregated sum of the value added by residents in an economy, plus net taxes (minus subsidies) and net receipts of primary income from abroad. Excluding countries and territories in the Caribbean, Uruguay and Chile were the Latin American countries with the highest national income per capita. Demographic elements and income There are many factors that may influence the income level, such as gender, academic attainment, location, ethnicity, etc. The gender pay gap, for example, is significant in Brazil. As of 2024, the monthly income per capita of men was 3,549 Brazilian reals, while the figure was 2,793 reals in the case of women. Additionally, monthly per capita household income varies greatly from state to state; the figures registered in Distrito Federal and São Paulo more than double the income of federative units like Acre, Alagoas or Maranhão. A high degree of inequality The Gini coefficient measures the degree of income inequality on a scale from 0 (total equality of incomes) to 100 (total inequality). Between 2010 and 2023, Brazil's degree of inequality in wealth distribution based on the Gini coefficient reached 52. That year, Brazil was deemed one of the most unequal countries in Latin America. Although the latest result represented one of the worst values in recent years, the Gini index is projected to improve slightly in the near future.

In Brazil, the bottom 50 percent had a negative average personal wealth in 2021, which means that the value of their debts exceeded that of their assets. In comparison, in Argentina, average personal wealth of the bottom 50 percent reached 3,500 euros that same year. In stark contrast, the richest one percent in Brazil held an average wealth of 1.79 million euros, revealing the high level of inequality i the country.

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

ABSTRACT The article presents a panorama of socioeconomic hierarchies in late Nineteenth-century Brazil. Income analysis of social classes underpins these echelons. Within a theoretical and historical approach focused on social class, the article reckons that the Brazilian Empire was relatively egalitarian in terms of wages. A broad expressiveness of the lower classes, rather than a hypothetical robustness of the middle or the upper classes, explains this equality. The analysis of purchasing power and patterns of consumption made it possible to identify the degree of precariousness of the popular classes, as well as the existence of mainly urban middle classes. Lastly, salary data on the upper classes should not hide concentration of wealth, a main characteristic of the Empire’s decay, which was largely due to a polarized structure of slave property.

Brazil is one of the most unequal countries in terms of income in Latin America. In 2022, it was estimated that almost 57 percent of the income generated in Brazil was held by the richest 20 percent of its population. Among the Latin American countries with available data included in this graph, Colombia came in first, as the wealthiest 20 percent of the Colombian population held over 59 percent of the country's total income.

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 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 This article aims at providing an overview of the Brazilian income distribution controversyduring the 1960´s.To that end, we present the key arguments of theso-called “official” interpretation, based mostly on Langoni's (1973) study, as well as the main criticisms it received.The “official” interpretation states that the increase in the inequality of income distribution between 1960 and 1970 is a natural and transitory consequence of the disequilibrium between thesupply and demand of qualified labor,within the context of a high economic growth. However, from our part and in line with the main criticisms it received, we suggest that the "official" interpretation offers arguments which actually hinder the importance of crucial elements, both theoretical and empirical, linked tothe organizational hierarchy of businesses, to the economic policy adopted by the military government and to the pattern of capitalist development in Brazil.

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).

This paper aims to systematize the explanations for income inequality decreases observed in Brazil between 2001 and 2015, analyzing each region and subperiod separately and focusing on social programs. The results indicate that social program incomes, as well as pension incomes, have gained prominence as income sources relative to labor income. Social program incomes contributed 19% to income inequality decreases, especially in the North and Northeast, between 2001-2004 and 2008-2012. However, this contribution declined in the Northeast and increased in the Southeast at the beginning of the great recession. Labor income contributed 57% to income inequality decreases and explains why a sharper decrease was noted in the South and Center-West regions. Official pensions contributed 17% to inequality reductiomn in all Brazilian regions, more strongly between 2004 and 2012, when significant minimum wage increases occurred.

About this dataset

Context

The dataset tabulates the Brazil household income by age. The dataset can be utilized to understand the age-based income distribution of Brazil income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Brazil, IN annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Brazil, IN household incomes: Comparative analysis across 16 income brackets

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Brazil income distribution by age. You can refer the same here

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.