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Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005Q) from Q4 1987 to Q1 2025 about net worth, Net, households, and USA.
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Graph and download economic data for Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) (WFRBLT01026) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.
In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.
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Context
The dataset presents the mean household income for each of the five quintiles in Log Lane Village, CO, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Log Lane Village median household income. You can refer the same here
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Context
The dataset presents the mean household income for each of the five quintiles in Rich Hill, MO, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rich Hill median household income. You can refer the same here
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Context
The dataset presents the mean household income for each of the five quintiles in Lake Worth, TX, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lake Worth median household income. You can refer the same here
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Context
The dataset presents the mean household income for each of the five quintiles in Rich Square, NC, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rich Square median household income. You can refer the same here
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Rich County, UT, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rich County median household income. You can refer the same here
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Wealth inequality has been sharply rising in the United States and across many other high-income countries. Due to a lack of data, we know little about how this trend has unfolded across locations within countries. Investigating this subnational geography of wealth is crucial, as from one generation to the next, wealth powerfully shapes opportunity and disadvantage across individuals and communities. Using machine-learning-based imputation to link newly assembled national historical surveys conducted by the U.S. Federal Reserve to population survey microdata, the data presented in this paper addresses this gap. The Geographic Wealth Inequality Database ("GEOWEALTH-US") provides the first estimates of the level and distribution of wealth at various geographical scales within the United States from 1960 to 2020. The GEOWEALTH-US database enables new lines investigation into the contribution of inter-regional wealth patterns to major societal challenges including wealth concentration, spatial income inequality, equality of opportunity, housing unaffordability, and political polarization.
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Graph and download economic data for Households; Net Worth, Transactions (BOGZ1FA192090005Q) from Q1 1988 to Q1 2025 about net worth, transactions, Net, households, and USA.
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Graph and download economic data for Net Worth Held by the Bottom 50% (1st to 50th Wealth Percentiles) (WFRBLB50107) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.
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U.S. Top 1% Wealth Share: 36 years of historical data from 1989 to 2025.
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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 Rich County. 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 Rich County, the median income for all workers aged 15 years and older, regardless of work hours, was $45,000 for males and $22,645 for females.
These income figures highlight a substantial gender-based income gap in Rich County. Women, regardless of work hours, earn 50 cents for each dollar earned by men. This significant gender pay gap, approximately 50%, underscores concerning gender-based income inequality in the county of Rich County.
- Full-time workers, aged 15 years and older: In Rich County, among full-time, year-round workers aged 15 years and older, males earned a median income of $72,653, while females earned $35,278, leading to a 51% gender pay gap among full-time workers. This illustrates that women earn 49 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Rich County, showcasing a consistent income pattern irrespective of employment status.
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:
Employment type classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rich County median household income by race. You can refer the same here
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United States US: Central Government: Net Worth data was reported at -13,504.022 USD bn in 2017. This records a decrease from the previous number of -12,876.033 USD bn for 2016. United States US: Central Government: Net Worth data is updated yearly, averaging -6,768.117 USD bn from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of -2,905.666 USD bn in 2001 and a record low of -13,504.022 USD bn in 2017. United States US: Central Government: Net Worth data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s USA – Table US.IMF.IFS: Government Finance: Balance Sheet: Annual.
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Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005A) from 1987 to 2024 about net worth, Net, households, and USA.
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Replication data and code for Ellora Derenoncourt, Chi Hyun Kim, Moritz Kuhn, Moritz Schularick, Wealth of Two Nations: The U.S. Racial Wealth Gap, 1860–2020, The Quarterly Journal of Economics, 2023;, qjad044, https://doi.org/10.1093/qje/qjad044
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This dataset is about books. It has 2 rows and is filtered where the book is Healthy, wealthy, or wise? : issues in American health care policy. It features 7 columns including author, publication date, language, and book publisher.
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Graph and download economic data for All Sectors; U.S. Wealth, Level (BOGZ1FL892090005A) from 1945 to 2024 about wealth, sector, and USA.
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Graph and download economic data for Minimum Wealth Cutoff for the 90th to 99th Wealth Percentiles (WFRBLN09304) from Q3 1989 to Q3 2022 about wealth, percentile, and USA.
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Graph and download economic data for Households and Nonprofit Organizations; Net Worth as a Percentage of Disposable Personal Income, Level (HNONWPDPI) from Q4 1946 to Q1 2025 about net worth, disposable, nonprofit organizations, personal income, Net, percent, personal, households, income, and USA.
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Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005Q) from Q4 1987 to Q1 2025 about net worth, Net, households, and USA.