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.

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.

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: 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

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.

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.

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

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.

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.

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).

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.

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.

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.

Traditional agrarian elites have often been portrayed as obstacles to the expansion of the state. Because landed actors are particularly exposed to taxation, inequality is expected to exacerbate their resistance to the development of fiscal capacity. This article argues that when propertied actors are politically dominant and obtain benefits from public spending that are proportional to their capital endowments, wealth inequality is associated with greater elite support for capacity investments. Using early 20th-century Brazilian data, I show that where landed elites faced fewer political threats, higher levels of landholding concentration were associated with increased fiscal and administrative capacity. Tests of mechanisms corroborate the idea that this relationship results from elite demands for specific types of public spending. These findings contribute to the broader literature on state-building by providing new insights into the interaction between economic interests and political dominance in shaping subnational variation in the reach of the state.

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/].

ABSTRACT Brazil is the only country among the 20 richest and the 20 most unequal. It has one of the largest income redistribution programs in the world, Bolsa Família, but also one of the most unjust tax burdens. Taxation and economic inequality are two of the most important issues in developing countries. In a situation of economic stagnation, the government prioritized cutting expenses as a measure of fiscal balance. This paper aims to analyze the implementation of a Wealth Tax, its feasibility and tax collection by simulation with data from tax declarations. It is shown that the Wealth Tax is feasible, has a solid revenue and could be used as an instrument of fiscal justice. It could also help with fiscal equilibrium instead of other austerity measures such as cuts in expenses of essential sectors to the economic growth and well-being of Brazil.

In 2024, Colombia ranked first by percentage of income held by the richest 20 percent of the population among the 22 countries presented in the ranking. Colombia's percentage of income held amounted to 58.70 percent, while Brazil and Panama, the second and third countries, had records amounting to 56.60 percent and 53.50 percent, respectively.

About this dataset

Context

The dataset presents the median household income across different racial categories in Brazil. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Brazil population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 93.58% of the total residents in Brazil. Notably, the median household income for White households is $48,592. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $48,592.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Brazil.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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