9 datasets found
  1. U.S household income shares of quintiles 1970-2023

    • statista.com
    • ai-chatbox.pro
    Updated Sep 17, 2024
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    Statista (2024). U.S household income shares of quintiles 1970-2023 [Dataset]. https://www.statista.com/statistics/203247/shares-of-household-income-of-quintiles-in-the-us/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, the Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.

  2. U.S. median household income 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. median household income 1990-2023 [Dataset]. https://www.statista.com/statistics/200838/median-household-income-in-the-united-states/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

  3. N

    Pelham Town, New York annual income distribution by work experience and...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Pelham Town, New York annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/babe2908-f4ce-11ef-8577-3860777c1fe6/
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    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
    New York, Pelham
    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, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. 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 detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Pelham town. The dataset can be utilized to gain insights into gender-based income distribution within the Pelham town population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Pelham town, among individuals aged 15 years and older with income, there were 4,368 men and 4,386 women in the workforce. Among them, 2,774 men were engaged in full-time, year-round employment, while 2,110 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 0.68% fell within the income range of under $24,999, while 1% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 73.72% of men in full-time roles earned incomes exceeding $100,000, while 62.94% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    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:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 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 $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    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.

    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 Pelham town median household income by race. You can refer the same here

  4. d

    Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects...

    • catalog.data.gov
    • data.ny.gov
    • +1more
    Updated Jan 26, 2024
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    data.ny.gov (2024). Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects for Households with Income up to 60% State Median Income: Beginning January 2018 [Dataset]. https://catalog.data.gov/dataset/residential-existing-homes-one-to-four-units-energy-efficiency-projects-for-households-wit
    Explore at:
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    data.ny.gov
    Description

    IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. To reduce the energy burden on income-qualified households within New York State, NYSERDA offers the EmPower New York (EmPower) program, a retrofit program that provides cost-effective electric reduction measures (i.e., primarily lighting and refrigerator replacements), and cost-effective home performance measures (i.e., insulation air sealing, heating system repair and replacments, and health and safety measures) to income qualified homeowners and renters. Home assessments and implementation services are provided by Building Performance Institute (BPI) Goldstar contractors to reduce energy use for low income households. This data set includes energy efficiency projects completed since January 2018 for households with income up to 60% area (county) median income. D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 54 percent of the Estimated Annual kWh Savings and 70 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: https://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-EmPower-New-York-Impact-Report.pdf. This dataset includes the following data points for projects completed after January 1, 2018: Reporting Period, Project ID, Project County, Project City, Project ZIP, Gas Utility, Electric Utility, Project Completion Date, Total Project Cost (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Number of Units, Job Type, Type of Dwelling, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Modeled Energy Savings $ Estimate (USD). How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

  5. U.S. household income Gini Index 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income Gini Index 1990-2023 [Dataset]. https://www.statista.com/statistics/219643/gini-coefficient-for-us-individuals-families-and-households/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, according to the Gini coefficient, household income distribution in the United States was 0.47. This figure was at 0.43 in 1990, which indicates an increase in income inequality in the U.S. over the past 30 years. What is the Gini coefficient? The Gini coefficient, or Gini index, is a statistical measure of economic inequality and wealth distribution among a population. A value of zero represents perfect economic equality, and a value of one represents perfect economic inequality. The Gini coefficient helps to visualize income inequality in a more digestible way. For example, according to the Gini coefficient, the District of Columbia and the state of New York have the greatest amount of income inequality in the U.S. with a score of 0.51, and Utah has the greatest income equality with a score of 0.43. The Gini coefficient around the world The Gini coefficient is also an effective measure to help picture income inequality around the world. For example, in 2018 income inequality was highest in South Africa, while income inequality was lowest in Slovenia.

  6. d

    Residential Existing Homes (One to Four Units) Energy Efficiency Projects...

    • catalog.data.gov
    • data.ny.gov
    • +2more
    Updated Jan 26, 2024
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    data.ny.gov (2024). Residential Existing Homes (One to Four Units) Energy Efficiency Projects with Income-based Incentives by Customer Type: Beginning 2010 [Dataset]. https://catalog.data.gov/dataset/residential-existing-homes-one-to-four-units-energy-efficiency-projects-with-income-based-
    Explore at:
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    data.ny.gov
    Description

    IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. The Residential Existing Homes Program is a market transformation program that uses Building Performance Institute (BPI) Goldstar contractors to install comprehensive energy-efficient improvements. The program is designed to use building science and a whole-house approach to reduce energy use in the State’s existing one-to-four family and low-rise multifamily residential buildings and capture heating fuel and electricity-related savings. The Program provides income-based incentives, including an assisted subsidy for households with income up to 80% of the State or Median County Income, whichever is higher to install eligible energy efficiency improvements including building shell measures, high efficiency heating and cooling measures, ENERGY STAR appliances and lighting. D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 35 percent of the Estimated Annual kWh Savings and 65 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Many factors influence the degree to which estimated savings are realized, including proper calibration of the savings model and the savings algorithms used in the modeling software. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. Beginning November 2017, the Program requires the use of HPXML-compliant modeling software tools and data quality protocols have been implemented to more accurately project savings. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: http://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-HPwES-Impact-Report-with-Appendices.pdf. The New York Residential Existing Homes (One to Four Units) dataset includes the following data points for projects completed during Green Jobs Green-NY, beginning November 15, 2010: Home Performance Project ID, Home Performance Site ID, Project County, Project City, Project Zip, Gas Utility, Electric Utility, Project Completion Date, Customer Type, Low-Rise or Home Performance Indicator, Total Project Cost (USD), Total Incentives (USD), Type of Program Financing, Amount Financed Through Program (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Volume of Home, Number of Units, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Energy Savings $ Estimate (USD), Homeowner Received Green Jobs-Green NY Free/Reduced Cost Audit (Y/N). How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

  7. A

    ‘Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects...

    • analyst-2.ai
    Updated Sep 15, 2019
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2019). ‘Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects for Households with Income up to 60% State Median Income: Beginning January 2018’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-residential-existing-homes-one-to-four-units-energy-efficiency-projects-for-households-with-income-up-to-60-state-median-income-beginning-january-2018-d355/dcfb2bbf/?iid=013-434&v=presentation
    Explore at:
    Dataset updated
    Sep 15, 2019
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Residential Existing Homes (One-to-Four Units) Energy Efficiency Projects for Households with Income up to 60% State Median Income: Beginning January 2018’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/361fed56-140f-4b31-8092-22e8d4c807a5 on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. To reduce the energy burden on income-qualified households within New York State, NYSERDA offers the EmPower New York (EmPower) program, a retrofit program that provides cost-effective electric reduction measures (i.e., primarily lighting and refrigerator replacements), and cost-effective home performance measures (i.e., insulation air sealing, heating system repair and replacments, and health and safety measures) to income qualified homeowners and renters. Home assessments and implementation services are provided by Building Performance Institute (BPI) Goldstar contractors to reduce energy use for low income households. This data set includes energy efficiency projects completed since January 2018 for households with income up to 60% area (county) median income.

    D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 54 percent of the Estimated Annual kWh Savings and 70 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: https://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-EmPower-New-York-Impact-Report.pdf.

    This dataset includes the following data points for projects completed after January 1, 2018: Reporting Period, Project ID, Project County, Project City, Project ZIP, Gas Utility, Electric Utility, Project Completion Date, Total Project Cost (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Number of Units, Job Type, Type of Dwelling, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Modeled Energy Savings $ Estimate (USD).

    How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

    --- Original source retains full ownership of the source dataset ---

  8. Richest owners of MLB teams in the U.S. in 2024

    • statista.com
    Updated Mar 12, 2024
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    Statista (2024). Richest owners of MLB teams in the U.S. in 2024 [Dataset]. https://www.statista.com/statistics/1125149/wealthiest-mlb-teams-owners/
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    Dataset updated
    Mar 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    North America, United States
    Description

    Major League Baseball (MLB) teams are owned by a variety of individuals and groups. The Toronto Blue Jays are owned by Rogers Communications, led by CEO Edward S. Rogers III, with a net worth of 11.5 billion U.S. dollars. Individual owners of MLB franchises include wealthy individuals such as Mark Attanasio (Milwaukee Brewers), John Henry (Boston Red Sox), and Arte Moreno (Los Angeles Angels), who also have other business interests outside of sports ownership. There are also multiple ownership groups that own MLB franchises, made up of a mix of businesspeople, investors, and wealthy individuals who come together specifically to purchase and operate the teams. In rare occurrences, franchises have also been owned by the league, such as the Montreal Expos and the Texas Rangers in the past. The ownership process often includes the approval of the other MLB owners and requires significant financial resources.

    Steven A. Cohen Steven A. Cohen's purchase of the New York Mets for 2.4 billion U.S. dollars in 2020 constituted a significant event in the sport. The purchase made him the wealthiest franchise owner in the league, with a personal wealth of around 16 billion U.S. dollars. Cohen stated that he planned to invest in the team to help bring it success on the field, as well as in its business operations. One of his main goals with the purchase was to renovate Citi Field, the team's stadium, and to invest in the team's player development facilities. He also announced plans to enhance the fan experience through technology and fan engagement, aiming to bring the team closer to its fan base. Billionaire sports club ownership The growing trend of wealthy individuals buying sports teams can have both positive and negative impacts. On one hand, wealthy owners bring significant financial resources to teams, which can improve the team's performance and overall competitiveness. However, there are also concerns such as concentration of wealth and power among a small number of teams and owners, a less competitive league, and owners prioritizing financial returns over competitive balance. Additionally, the high price of ownership can make it difficult for new ownership groups to enter the market and lead to lack of diversity among ownership group of sports teams. This can also lead to high-priced tickets and merchandise, making it harder for low-income fans to support their team.

  9. Hispanic population U.S. 2023, by state

    • statista.com
    Updated Oct 18, 2024
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    Statista (2024). Hispanic population U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/259850/hispanic-population-of-the-us-by-state/
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    Dataset updated
    Oct 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2024). U.S household income shares of quintiles 1970-2023 [Dataset]. https://www.statista.com/statistics/203247/shares-of-household-income-of-quintiles-in-the-us/
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U.S household income shares of quintiles 1970-2023

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10 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 17, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, the Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.

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