54 datasets found
  1. h

    100-richest-people-in-world

    • huggingface.co
    Updated Aug 2, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nate Raw (2023). 100-richest-people-in-world [Dataset]. https://huggingface.co/datasets/nateraw/100-richest-people-in-world
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 2, 2023
    Authors
    Nate Raw
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Area covered
    World
    Description

    Dataset Card for 100 Richest People In World

      Dataset Summary
    

    This dataset contains the list of Top 100 Richest People in the World Column Information:-

    Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

      Join our Community
    
    
    
    
    
    
    
    
    
      Supported Tasks and Leaderboards
    

    [More Information Needed]

      Languages
    

    [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

  2. 1000 Richest People in the World

    • kaggle.com
    zip
    Updated Jul 28, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Waqar Ali (2024). 1000 Richest People in the World [Dataset]. https://www.kaggle.com/datasets/waqi786/1000-richest-people-in-the-world
    Explore at:
    zip(8652 bytes)Available download formats
    Dataset updated
    Jul 28, 2024
    Authors
    Waqar Ali
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    This dataset provides a synthetic overview of the 1,000 wealthiest individuals in the world, offering insights into the distribution of wealth across industries and regions. It is designed to help analysts, researchers, and data enthusiasts explore global wealth trends, industry dominance, and regional wealth concentration.

    Whether you're conducting market research, financial analysis, or data modeling, this dataset serves as a valuable resource for understanding the characteristics of the world's top billionaires.

    📊 Key Features: Name 👤: The name of the billionaire. Country 🌍: Country of residence or primary business operation. Industry 🏭: Industry in which the individual has built their wealth. Net Worth (in billions) 💵: Estimated net worth in billions of USD. Company 🏢: The primary company or business associated with the billionaire. ⚠️ Important Note: This dataset is 100% synthetic and does not contain real financial or personal data. It is artificially generated for educational, analytical, and research purposes.

  3. Forbes Top 200 Richest American

    • kaggle.com
    zip
    Updated Feb 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ayessa (2023). Forbes Top 200 Richest American [Dataset]. https://www.kaggle.com/datasets/ayessa/forbes-top-200-richest-american/code
    Explore at:
    zip(9658 bytes)Available download formats
    Dataset updated
    Feb 6, 2023
    Authors
    Ayessa
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    The Forbes published "The Definitive Ranking of the Wealthiest Americans In 2022". And here is the top 200 list including additional information on each of the billionaires.

    About Dataset

    This dataset contains the top 200 richest American based on their net worth.

    Columns Attributes

    | Column | Meaning | | -- | -- | | rank | their rank | | name | their name | | net worth | their net worth | | age | their age | | title | their title (e.g. CEO, Chairman etc.) | | source of wealth | the source of how they've managed to get this much money | | self made score | shows how far each of these billionaires has climbed to make it to the top. According to Forbes, The score ranges from 1 to 10, with 1 through 5 indicating someone who inherited some or all of his or her fortune; while 6 through 10 are for those who built their company or established a fortune on his or her own. | | philanthropy score | this score shows how much these billionaires donates on nonprofits foundations | | residence | their residence | | marital status | their marital status | | children | their children | | education | their education |

    Methodology

    This dataset was acquired using a web scraping tool called Beautiful soup and scraped Forbes website

    Image by pch.vector on Freepik

  4. U.S. wealth distribution Q1 2025

    • statista.com
    Updated Jun 18, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). U.S. wealth distribution Q1 2025 [Dataset]. https://www.statista.com/statistics/203961/wealth-distribution-for-the-us/
    Explore at:
    Dataset updated
    Jun 18, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the first quarter of 2025, almost ********** of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest ** percent of earners only owned *** 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 2024, *** 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 was the country with the most billionaires in the world in 2025. Elon Musk, with a net worth of *** billion U.S. dollars, was among the richest people in the United States in 2025. 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.

  5. Forbes 400 Richest 2022

    • kaggle.com
    zip
    Updated Dec 26, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    kabhishm (2022). Forbes 400 Richest 2022 [Dataset]. https://www.kaggle.com/datasets/kabhishm/forbes-400-richest-2022
    Explore at:
    zip(131277 bytes)Available download formats
    Dataset updated
    Dec 26, 2022
    Authors
    kabhishm
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The rich don’t always get richer. As a group, the 400 wealthiest Americans are worth $4 trillion—$500 billion less than last year. The minimum net worth to make The Forbes 400 dropped for the first time since the Great Recession, down $200 million to $2.7 billion amid the market selloff. No one has been hit harder than tech billionaires, who have lost a combined $315 billion. Still, it was a great year to be an oil-and-gas tycoon, a sports mogul or Elon Musk. And 42 people, spanning ages 29 to 90, joined or rejoined the ranks. Fortunes were calculated using stock prices from September 2, 2022.

    FILE DESCRIPTION

    File name: forbes_400 _richest.csv

    COLUMN DESCRIPTION

    • 'bio': bio of the person
    • 'rank': rank of the person
    • 'finalWorth': final net worth of the person
    • 'personName': name of the person
    • 'city': city where the person lives
    • 'source': source of income
    • 'countryOfCitizenship': country where the person lives
    • 'gender': gender of the person
    • 'lastName': last name of the person
    • 'estWorthPrev': estimated previous net worth
    • 'privateAssetsWorth': worth of their private assets
    • 'archivedWorth': archived worth
    • 'abouts': a little bit about them
    • 'state': state where they live
    • 'industries': industry they are in
  6. Leading billionaires worldwide 2025

    • statista.com
    Updated Mar 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Leading billionaires worldwide 2025 [Dataset]. https://www.statista.com/statistics/272047/top-25-global-billionaires/
    Explore at:
    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2025
    Area covered
    World
    Description

    As of March 2025, Elon Musk had a net worth valued at 328.5 billion U.S. dollars, making him the richest man in the world. Amazon founder Jeff Bezos followed in second, with Marc Zuckerberg, the founder of Facebook, in third. The list is dominated by Americans, and Alice Walton and Francoise Bettencourt Meyers are the only women among the 20 richest people worldwide.

  7. Survey of Consumer Finances

    • federalreserve.gov
    Updated Oct 18, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Board of Governors of the Federal Reserve Board (2023). Survey of Consumer Finances [Dataset]. http://doi.org/10.17016/8799
    Explore at:
    Dataset updated
    Oct 18, 2023
    Dataset provided by
    Federal Reserve Board of Governors
    Federal Reserve Systemhttp://www.federalreserve.gov/
    Authors
    Board of Governors of the Federal Reserve Board
    Time period covered
    1962 - 2023
    Description

    The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

  8. World's Billionaires

    • kaggle.com
    zip
    Updated May 19, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sadialiou Diallo (2021). World's Billionaires [Dataset]. https://www.kaggle.com/seriadiallo1/world-billionaires
    Explore at:
    zip(2962 bytes)Available download formats
    Dataset updated
    May 19, 2021
    Authors
    Sadialiou Diallo
    Description

    The richest people in the world, yearly rank from 2002 to 2021

    This dataset contains 200 rows and 7 columns.

    The World's Billionaires is an annual ranking by documented net worth of the world's wealthiest billionaires compiled and published in March annually by the American business magazine Forbes. The list was first published in March 1987. The total net worth of each individual on the list is estimated and is cited in United States dollars, based on their documented assets and accounting for debt. Royalty and dictators whose wealth comes from their positions are excluded from these lists. This ranking is an index of the wealthiest documented individuals, excluding and ranking against those with wealth that is not able to be completely ascertained. (wikipedia)

  9. N

    Rich Square, NC annual median income by work experience and sex dataset:...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). Rich Square, NC annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/rich-square-nc-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Rich Square, North Carolina
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    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 Rich Square. 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 Square, the median income for all workers aged 15 years and older, regardless of work hours, was $24,265 for males and $17,431 for females.

    These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Rich Square. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Rich Square.

    - Full-time workers, aged 15 years and older: In Rich Square, among full-time, year-round workers aged 15 years and older, males earned a median income of $45,893, while females earned $36,089, leading to a 21% gender pay gap among full-time workers. This illustrates that women earn 79 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.

    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 Square, showcasing a consistent income pattern irrespective of employment status.

    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 Rich Square median household income by race. You can refer the same here

  10. N

    Rich Creek, VA Median Income by Age Groups Dataset: A Comprehensive...

    • neilsberg.com
    csv, json
    Updated Feb 25, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2025). Rich Creek, VA Median Income by Age Groups Dataset: A Comprehensive Breakdown of Rich Creek Annual Median Income Across 4 Key Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/e9540156-f353-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 25, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Virginia, Rich Creek
    Variables measured
    Income for householder under 25 years, Income for householder 65 years and over, Income for householder between 25 and 44 years, Income for householder between 45 and 64 years
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across four age groups (Under 25 years, 25 to 44 years, 45 to 64 years, and 65 years and over) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the distribution of median household income among distinct age brackets of householders in Rich Creek. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Rich Creek. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

    Key observations: Insights from 2023

    In terms of income distribution across age cohorts, in Rich Creek, householders within the 25 to 44 years age group have the highest median household income at $93,472, followed by those in the under 25 years age group with an income of $53,750. Meanwhile householders within the 45 to 64 years age group report the second lowest median household income of $52,813. Notably, householders within the 65 years and over age group, had the lowest median household income at $38,750.

    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.

    Age groups classifications include:

    • Under 25 years
    • 25 to 44 years
    • 45 to 64 years
    • 65 years and over

    Variables / Data Columns

    • Age Of The Head Of Household: This column presents the age of the head of household
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

    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 Rich Creek median household income by age. You can refer the same here

  11. F

    Households; Net Worth, Level

    • fred.stlouisfed.org
    json
    Updated Sep 11, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Households; Net Worth, Level [Dataset]. https://fred.stlouisfed.org/series/BOGZ1FL192090005Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 11, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005Q) from Q4 1987 to Q2 2025 about net worth, Net, households, and USA.

  12. N

    Median Household Income Variation by Family Size in Rich Valley Township,...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2024). Median Household Income Variation by Family Size in Rich Valley Township, Minnesota: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/1b5facb3-73fd-11ee-949f-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Minnesota, Rich Valley Township
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Rich Valley Township, Minnesota, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Rich Valley township did not include 7-person households. Across the different household sizes in Rich Valley township the mean income is $130,586, and the standard deviation is $54,983. The coefficient of variation (CV) is 42.10%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $51,343. It then further increased to $146,599 for 6-person households, the largest household size for which the bureau reported a median household income.

    https://i.neilsberg.com/ch/rich-valley-township-mn-median-household-income-by-household-size.jpeg" alt="Rich Valley Township, Minnesota median household income, by household size (in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

    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 Rich Valley township median household income. You can refer the same here

  13. H

    Replication Data for: "The Rich are Different from You and Me": College...

    • dataverse.harvard.edu
    • datasetcatalog.nlm.nih.gov
    Updated Oct 11, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Tali Mendelberg; Katherine McCabe; Adam Thal (2017). Replication Data for: "The Rich are Different from You and Me": College Socialization and the Economic Views of Affluent Americans [Dataset]. http://doi.org/10.7910/DVN/FS90RJ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 11, 2017
    Dataset provided by
    Harvard Dataverse
    Authors
    Tali Mendelberg; Katherine McCabe; Adam Thal
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7910/DVN/FS90RJhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7910/DVN/FS90RJ

    Description

    Affluent Americans support more conservative economic policies than the non-affluent, and government responds disproportionately to these views. Yet little is known about the emergence of these consequential views. We develop, test and find support for a theory of class cultural norms: these preferences are partly traceable to socialization that occurs on predominately affluent college campuses, especially those with norms of financial gain, and especially among socially embedded students. The economic views of the student’s cohort also matter, in part independently of affluence. We use a large panel dataset with a high response rate and more rigorous causal inference strategies than previous socialization studies. The affluent campus effect holds with matching, among students with limited school choice, and in a natural experiment, and passes placebo tests. College socialization partly explains why affluent Americans support economically conservative policies.

  14. Survey of Consumer Finances 2019

    • kaggle.com
    zip
    Updated Nov 5, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Zaid Ullah (2024). Survey of Consumer Finances 2019 [Dataset]. https://www.kaggle.com/datasets/syntheticprogrammer/survey-of-consumer-finances-2022
    Explore at:
    zip(3062552 bytes)Available download formats
    Dataset updated
    Nov 5, 2024
    Authors
    Zaid Ullah
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The Survey of Consumer Finances (SCF) dataset, provided by the Federal Reserve, offers comprehensive insights into the financial condition of U.S. households. This dataset is invaluable for researchers, policymakers, and analysts interested in understanding consumer behavior, wealth distribution, and economic trends in the United States.

    The SCF dataset includes detailed information on household income, assets, liabilities, and various demographic characteristics. It is collected every three years and serves as a crucial resource for analyzing the financial well-being of American families.

    Key Features: Income Data: Information on various sources of income, including wages, investments, and government assistance. Asset Ownership: Detailed accounts of household assets, such as real estate, retirement accounts, stocks, and other investments. Liabilities:Comprehensive details on household debts, including mortgages, credit card debts, and student loans. Demographics: Data covering age, education, race, and family structure, allowing for nuanced analysis of financial trends across different segments of the population.

    Use Cases: Economic research and analysis, Policy formulation and assessment, Understanding wealth inequality, Consumer behavior studies

    Citing the Dataset:

    When using this dataset in your research, please ensure to cite the Federal Reserve Board and the SCF as the original source.

    Note: The dataset is intended for educational and research purposes. Users are encouraged to adhere to ethical guidelines when analyzing and interpreting the data.

  15. n

    Luxembourg Income Study

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Aug 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Luxembourg Income Study [Dataset]. http://identifiers.org/RRID:SCR_008732
    Explore at:
    Dataset updated
    Aug 9, 2024
    Description

    A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150

  16. m

    Morgan Stanley - Operating-Income

    • macro-rankings.com
    csv, excel
    Updated Sep 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    macro-rankings (2025). Morgan Stanley - Operating-Income [Dataset]. https://www.macro-rankings.com/markets/stocks/ms-nyse/income-statement/operating-income
    Explore at:
    excel, csvAvailable download formats
    Dataset updated
    Sep 18, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    united states
    Description

    Operating-Income Time Series for Morgan Stanley. Morgan Stanley, a financial holding company, provides various financial products and services to governments, financial institutions, and individuals in the Americas, Asia, Europe, Middle East, and Africa. The company operates through Institutional Securities, Wealth Management, and Investment Management segments. It offers capital raising and financial advisory services, including services related to the underwriting of debt, equity, and other securities, as well as advice on mergers and acquisitions, restructurings, and project finance. It also provides equity and fixed income products comprising sales, financing, prime brokerage, and market-making services; Asia wealth management; business-related investments services; originating corporate and commercial real estate loans, secured lending facilities, and extending securities; and research. In addition, the company offers financial advisor-led brokerage, custody, and administrative and investment advisory services; self-directed brokerage services; financial and wealth planning services; stock plan administration; securities-based lending, residential and commercial real estate loans, and other lending products; banking; and retirement plan services. Further, it provides equity, fixed income, alternatives and solutions, and liquidity and overlay services to benefit/defined contribution plans, foundations, endowments, government entities, sovereign wealth funds, insurance companies, third-party fund sponsors, corporations, and individuals. The company was founded in 1924 and is headquartered in New York, New York.

  17. Top Countries with the highest average wealth

    • kaggle.com
    zip
    Updated Feb 10, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Pulkit Mehta (2020). Top Countries with the highest average wealth [Dataset]. https://www.kaggle.com/pulkitmehtawork1985/top-countries-with-the-highest-average-wealth
    Explore at:
    zip(10520 bytes)Available download formats
    Dataset updated
    Feb 10, 2020
    Authors
    Pulkit Mehta
    Description

    Context

    Ever wondered , which country has highest average wealth per adult . This data set attempts to answer that question.

    Content

    There are just 2 columns for top 100 countries . Country Name Average Wealth per Adult in USD

    Acknowledgements

    I have received this data from https://www.statista.com/statistics/203941/countries-with-the-highest-wealth-per-adult/

  18. N

    Median Household Income Variation by Family Size in Rich Creek, VA:...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2024). Median Household Income Variation by Family Size in Rich Creek, VA: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/1b5fa4f1-73fd-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Virginia, Rich Creek
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Rich Creek, VA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, only 2, and 4-person households were found in Rich Creek. Across the different household sizes in Rich Creek the mean income is $97,102, and the standard deviation is $56,305. The coefficient of variation (CV) is 57.99%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 2-person households, with an income of $57,288. It then further increased to $136,916 for 4-person households, the largest household size for which the bureau reported a median household income.

    https://i.neilsberg.com/ch/rich-creek-va-median-household-income-by-household-size.jpeg" alt="Rich Creek, VA median household income, by household size (in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

    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 Rich Creek median household income. You can refer the same here

  19. Forbes 2022 Billionaires data [Pre-processed]

    • kaggle.com
    zip
    Updated May 23, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    SJ (2022). Forbes 2022 Billionaires data [Pre-processed] [Dataset]. https://www.kaggle.com/surajjha101/forbes-billionaires-data-preprocessed
    Explore at:
    zip(50115 bytes)Available download formats
    Dataset updated
    May 23, 2022
    Authors
    SJ
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    About the Ranking

    The World's Billionaires is an annual ranking by documented net worth of the wealthiest billionaires in the world, compiled and published in March annually by the American business magazine Forbes. The list was first published in March 1987. The total net worth of each individual on the list is estimated and is cited in United States dollars, based on their documented assets and accounting for debt and other factors. Royalty and dictators whose wealth comes from their positions are excluded from these lists. This ranking is an index of the wealthiest documented individuals, excluding any ranking of those with wealth that is not able to be completely ascertained.

    Forbes Methodology

    Each year, Forbes employs a team of over 50 reporters from a variety of countries to track the activity of the world's wealthiest individuals and sometimes groups or families – who share wealth. Preliminary surveys are sent to those who may qualify for the list. According to Forbes, they received three types of responses – some people try to inflate their wealth, others cooperate but leave out details, and some refuse to answer any questions. Business deals are then scrutinized and estimates of valuable assets – land, homes, vehicles, artwork, etc. – are made. Interviews are conducted to vet the figures and improve the estimate of an individual's holdings. Finally, positions in a publicly traded stock are priced to market on a date roughly a month before publication. Privately held companies are priced by the prevailing price-to-sales or price-to-earnings ratios. Known debt is subtracted from assets to get a final estimate of an individual's estimated worth in United States dollars. Since stock prices fluctuate rapidly, an individual's true wealth and ranking at the time of publication may vary from their situation when the list was compiled.

  20. Donald Trump Forbes 400 Rankings

    • kaggle.com
    zip
    Updated Oct 19, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DaveRosenman (2017). Donald Trump Forbes 400 Rankings [Dataset]. https://www.kaggle.com/datasets/daverosenman/donald-trump-forbes-400-rankings-1985-to-2017
    Explore at:
    zip(1081 bytes)Available download formats
    Dataset updated
    Oct 19, 2017
    Authors
    DaveRosenman
    Description

    Context

    Donald Trump's 'Forbes Richest 400 Americans' rankings and estimated net worth from 1985 to 2017.

    Content

    Forbes Magazine's yearly Richest 400 Americans list was first published in 1982. Trump was on the list in 1982, 1983, and 1984, which are the only three years that I haven't been able to find his ranking. I left those years off the list. In 1982, according to "TrumpNation: The Art of Being the Donald" by Timothy O'Brien, "Forbes gave Donald an undefined share of a family fortune the magazine estimate at $200 million - at at time when all Donald owned personally was a half interest in the Grand Hyatt and a share of the yet-to-be completed Trump Tower. 1983- Wealth: Share of Fred's estimated $400 million fortune...1984- Wealth: Fred has $200 million, Donald has $400 million... 1985-Rank:51 Wealth: $600 million. Donald becomes a solo Forbes 400 act; Fred disappears from list."

    The "Worth" column contains Trump's estimated net worth in billions. Years when his ranking and net worth are "NA" are years when he did not make the Forbes 400 list (1990-1995).

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Nate Raw (2023). 100-richest-people-in-world [Dataset]. https://huggingface.co/datasets/nateraw/100-richest-people-in-world

100-richest-people-in-world

nateraw/100-richest-people-in-world

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Aug 2, 2023
Authors
Nate Raw
License

https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

Area covered
World
Description

Dataset Card for 100 Richest People In World

  Dataset Summary

This dataset contains the list of Top 100 Richest People in the World Column Information:-

Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

  Join our Community









  Supported Tasks and Leaderboards

[More Information Needed]

  Languages

[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

Search
Clear search
Close search
Google apps
Main menu