100+ datasets found
  1. U.S. median household income1970-2020, by income tier

    • statista.com
    Updated Aug 7, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). U.S. median household income1970-2020, by income tier [Dataset]. https://www.statista.com/statistics/500385/median-household-income-in-the-us-by-income-tier/
    Explore at:
    Dataset updated
    Aug 7, 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 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.

  2. Forecast of the global middle class population 2015-2030

    • statista.com
    Updated Jan 23, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Forecast of the global middle class population 2015-2030 [Dataset]. https://www.statista.com/statistics/255591/forecast-on-the-worldwide-middle-class-population-by-region/
    Explore at:
    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    World
    Description

    By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

    Worldwide wealth

    While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

    The middle-class

    The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

  3. ISSP 2019: Social Inequality V: Finnish Data

    • services.fsd.tuni.fi
    • datacatalogue.cessda.eu
    zip
    Updated Jan 9, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Melin, Harri (2025). ISSP 2019: Social Inequality V: Finnish Data [Dataset]. http://doi.org/10.60686/t-fsd3431
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jan 9, 2025
    Dataset provided by
    Finnish Social Science Data Archive
    Authors
    Melin, Harri
    Area covered
    Finland
    Description

    The 2019 International Social Survey Programme (ISSP) studied economic inequality in Finland. The respondents' attitudes were surveyed on income disparity between social groups, occupations and societies as well as which actors in society should solve these disparities. In addition, the survey charted the respondents' socio-economic situation, Finnish taxation, and conflicts between social groups. The previous ISSP survey regarding inequality was collected in 2009. First, the respondents' opinions were charted concerning the importance of different factors for succeeding in life, such as parents' wealth, ambition, social networks, corruption, or gender. Additionally, views were canvassed on fairness of differences in wealth between rich and poor countries. The respondents were also asked to estimate what persons in different occupations earned (euros/month, gross) and what the respondents thought they ought to be paid. Next, the respondents were presented with a set of statements that they were asked to agree or disagree with on a 5-point Likert scale. The questions concerned, for example, whether income disparity was too great in Finland, who should intervene with income disparity, whether the policies of the government were justified and whether the current level of taxation was justified. The respondents also placed themselves on a 10-point scale according to whether they considered themselves to be at the top or the bottom in society - currently, in childhood home and ten years into the future. Their views were also enquired on which factors they deemed important in deciding one's level of pay. Views on the hierarchical structure of society were examined by showing the respondents five figures representing differently built societies and asking which of the figures corresponded most closely to the situation in the respondent's own country, and which figure corresponded most closely to an optimal situation. The respondents were also asked questions regarding their economic situation at the time of the survey. Background variables included, for instance, gender, year of birth, region of residence (NUTS2), occupation, educational background, religious affiliation, which party the respondent voted for in previous elections, number of children, income, marital status, and statistical grouping of municipalities (urban, semi-urban, rural). The survey also included questions concerning the respondent's spouse/partner and parents' occupations.

  4. CBS News/New York Times Monthly Poll, September 2009

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated May 9, 2011
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Inter-university Consortium for Political and Social Research [distributor] (2011). CBS News/New York Times Monthly Poll, September 2009 [Dataset]. http://doi.org/10.3886/ICPSR27805.v1
    Explore at:
    stata, ascii, sas, spss, delimitedAvailable download formats
    Dataset updated
    May 9, 2011
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/27805/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/27805/terms

    Time period covered
    Sep 2009
    Area covered
    United States
    Description

    This poll, fielded September 19-23, 2009, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked whether they approved of the way Barack Obama was handling the presidency, the situations in Iraq and in Afghanistan, health care and the economy, whether they thought the country was on the right track, how they would rate the condition of the national economy and whether they thought the economy would get better. Respondents were also asked questions about the economic recession, whether they believed the stimulus package had made the economy better, whether the stimulus package would make the economy better in the future, and whether it was acceptable to raise the deficit to create jobs and stimulate growth. Several questions about health care were included that asked respondents how much change was needed in the health care system, how changes to the health care system would affect the Medicare program, whether they favored government administered health insurance plans, how satisfied they were with the quality of health care they were receiving, whether they were satisfied with their health care costs, whether they believed health care coverage could be increased without increasing the budget deficit, whether fixing the cost or providing coverage for the uninsured had the higher priority, and whether the respondent would consider public health care that anyone could join at any age. Other topics that were covered included, the war in Afghanistan and the war in Iraq, respondents' opinion of Michelle Obama, how the federal government should use taxpayer's money, how the deficit should be handled, personal finances, and job security. Demographic variables include sex, age, race, marital status, education level, household income, political party affiliation, political philosophy, perceived social class, religious preference, whether the respondent considered themselves to be a born-again Christian, and voter registration status and participation history.

  5. H

    Replication Data for The Myth of the Middle Class Squeeze: Employment and...

    • dataverse.harvard.edu
    Updated May 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jad Moawad; Daniel Oesch (2024). Replication Data for The Myth of the Middle Class Squeeze: Employment and Income by Class in Six Western Countries, 1980-2020 [Dataset]. http://doi.org/10.7910/DVN/MFAIFO
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 22, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Jad Moawad; Daniel Oesch
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This folder contains files to help you replicate the analyses from the study "The Myth of the Middle Class Squeeze: Employment and Income by Class in Six Western Countries, 1980-2020". The study uses data from the Luxembourg Income Study (LIS, 2024). To access this data, you must request access to the LIS data by visiting this website: https://www.lisdatacenter.org/data-access/lissy/eligibility/. Once you have access, you can use the codes in this folder to analyze the data. The analysis was conducted in R, and all the packages used are included in the R scripts. Note: The LIS data are not directly accessible. Instead, researchers can access an online platform to submit their analysis codes. The platform then returns the results. You can't download or physically access the data, but you can still use the codes provided here to get the same results as the original study. The LIS regularly updates new modules and revises old ones. This project started in 2022 and, therefore, uses the selection of countries released in LIS in that year. The final execution of this set of modules was done in 2024. To ensure you get the same results, please select the modules in the code and run them on the 2024 release.

  6. Perceptions of social classes in Italy 2019

    • statista.com
    Updated Aug 30, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Perceptions of social classes in Italy 2019 [Dataset]. https://www.statista.com/statistics/596152/perception-of-social-class-italy/
    Explore at:
    Dataset updated
    Aug 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Italy
    Description

    In 2019, most of Italians assumed to belong to the middle class. More specifically, 52 percent of individuals defined their social status as middle class. Moreover, 37 percent of Italians stated to be part of the lower social class. Data for social class perception suggested that the occupation with the highest share of upper-class people was being a student. At the same time, freelance professional was most popular job position among middle class citizens, while the majority of unemployed people felt to belong to the lower class.

    How much do Italians earn on average?

    From 2006 to 2015, gross household disposable income per capita in Italy was fluctuating with no precise pattern. In the next three years, however, gross income per capita steadily increased until peaking above 31 thousand U.S. dollars in 2018. This figure put Italy at the 17th place in the ranking of OECD countries with the gross disposable income per household.

    Income inequalities in Italy

    National average figures can be quite misleading. In Italy, substantial economic differences across regions and also due to gender can be observed. Inhabitants of the South and the Islands earn on average around ten thousand euros less annually than Italians from the North East. Moreover, female households’ average net income in 2017 was eight thousand euros smaller than male households’ income.

  7. N

    Income Bracket Analysis by Age Group Dataset: Age-Wise Distribution of...

    • 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). Income Bracket Analysis by Age Group Dataset: Age-Wise Distribution of Social Circle, GA Household Incomes Across 16 Income Brackets // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/social-circle-ga-median-household-income-by-age/
    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
    Georgia, Social Circle
    Variables measured
    Number of households with income $200,000 or more, Number of households with income less than $10,000, Number of households with income between $15,000 - $19,999, Number of households with income between $20,000 - $24,999, Number of households with income between $25,000 - $29,999, Number of households with income between $30,000 - $34,999, Number of households with income between $35,000 - $39,999, Number of households with income between $40,000 - $44,999, Number of households with income between $45,000 - $49,999, Number of households with income between $50,000 - $59,999, and 6 more
    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 16 income brackets (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out the total number of households within a specific income bracket along with how many households with that income bracket for each of the 4 age cohorts (Under 25 years, 25-44 years, 45-64 years and 65 years and over). 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 the household distribution across 16 income brackets among four distinct age groups in Social Circle: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

    Key observations

    • Upon closer examination of the distribution of households among age brackets, it reveals that there are 90(5.14%) households where the householder is under 25 years old, 537(30.67%) households with a householder aged between 25 and 44 years, 705(40.26%) households with a householder aged between 45 and 64 years, and 419(23.93%) households where the householder is over 65 years old.
    • The age group of under 25 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the city of Social Circle, showcasing varying income levels among different age demographics.
    Content

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

    Income brackets:

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

    Variables / Data Columns

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

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Social Circle median household income by age. You can refer the same here

  8. f

    Self-organization and time-stability of social hierarchies

    • plos.figshare.com
    pdf
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joseph Hickey; Jörn Davidsen (2023). Self-organization and time-stability of social hierarchies [Dataset]. http://doi.org/10.1371/journal.pone.0211403
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Joseph Hickey; Jörn Davidsen
    License

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

    Description

    The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple generalized theoretical model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of “winning” depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one high-status individual and all other individuals having status approaching zero. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. As we show, our model allows us to make predictions consistent with animal interaction data and their evolution over a number of years. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a distinct high-status class. Using household income as a proxy for societal status in human societies, we find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status “tail”. We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.

  9. Income Inequality

    • data.ca.gov
    pdf, xlsx, zip
    Updated Aug 28, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Income Inequality [Dataset]. https://data.ca.gov/dataset/income-inequality
    Explore at:
    pdf, xlsx, zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

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

    Description

    This table contains data on income inequality. The primary measure is the Gini index – a measure of the extent to which the distribution of income among families/households within a community deviates from a perfectly equal distribution. The index ranges from 0.0, when all families (households) have equal shares of income (implies perfect equality), to 1.0 when one family (household) has all the income and the rest have none (implies perfect inequality). Index data is provided for California and its counties, regions, and large cities/towns. The data is from the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Income is linked to acquiring resources for healthy living. Both household income and the distribution of income across a society independently contribute to the overall health status of a community. On average Western industrialized nations with large disparities in income distribution tend to have poorer health status than similarly advanced nations with a more equitable distribution of income. Approximately 119,200 (5%) of the 2.4 million U.S. deaths in 2000 are attributable to income inequality. The pathways by which income inequality act to increase adverse health outcomes are not known with certainty, but policies that provide for a strong safety net of health and social services have been identified as potential buffers. More information about the data table and a data dictionary can be found in the About/Attachments section.

  10. Forecast share of consumers Indonesia 2024, by social class

    • statista.com
    Updated Aug 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Forecast share of consumers Indonesia 2024, by social class [Dataset]. https://www.statista.com/statistics/1488457/indonesia-consumer-share-by-social-class/
    Explore at:
    Dataset updated
    Aug 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Indonesia
    Description

    According to forecast data from Tellusant, approximately 66.8 percent of the Indonesian population in 2024 would earn at least the equivalent of the top 40 percent of global earners in 2022 constant purchasing power parity. Meanwhile, around 1.5 percent of the population were considered high-class consumers, earning the equivalent of the top ten percent of global earners in 2022 constant purchasing power parity.

  11. N

    Comprehensive Income by Age Group Dataset: Longitudinal Analysis of Social...

    • neilsberg.com
    Updated Aug 7, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2024). Comprehensive Income by Age Group Dataset: Longitudinal Analysis of Social Circle, GA Household Incomes Across 4 Age Groups and 16 Income Brackets. Annual Editions Collection // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/2ef1be70-aeee-11ee-aaca-3860777c1fe6/
    Explore at:
    Dataset updated
    Aug 7, 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
    Georgia, Social Circle
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

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

    Content

    The dataset will have the following datasets when applicable

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

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

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Interested in deeper insights and visual analysis?

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

  12. S

    Spain ES: Proportion of People Living Below 50 Percent Of Median Income: %

    • ceicdata.com
    Updated Feb 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). Spain ES: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/spain/social-poverty-and-inequality/es-proportion-of-people-living-below-50-percent-of-median-income-
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2010 - Dec 1, 2021
    Area covered
    Spain
    Description

    Spain ES: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 15.400 % in 2021. This records a decrease from the previous number of 16.500 % for 2020. Spain ES: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 14.750 % from Dec 1980 (Median) to 2021, with 30 observations. The data reached an all-time high of 17.800 % in 2013 and a record low of 11.200 % in 1990. Spain ES: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Spain – Table ES.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

  13. r

    Data from: Panel Study of Income Dynamics

    • rrid.site
    • dknet.org
    • +1more
    Updated Aug 3, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Panel Study of Income Dynamics [Dataset]. http://identifiers.org/RRID:SCR_008976
    Explore at:
    Dataset updated
    Aug 3, 2024
    Description

    Long-term longitudinal dataset with information on generational links and socioeconomic and health conditions of individuals over time. The central foci of the data are economic and demographic, with substantial detail on income sources and amounts, wealth, savings, employment, pensions, family composition changes, childbirth and marriage histories, and residential location. Over the life of the PSID, the NIA has funded supplements on wealth, health, parental health and long term care, housing, and the financial impact of illness, thus also making it possible to model retirement and residential mobility. Starting in 1999, much greater detail on specific health conditions and health care expenses is included for respondent and spouse. Other enhancements have included a question series about emotional distress (2001); the two stem questions from the Composite International Diagnostic Interview to assess symptoms of major depression (2003); a supplement on philanthropic giving and volunteering (2001-03); a question series on Internet and computer use (2003); linkage to the National Death Index with cause of death information for more than 4,000 individuals through the 1997 wave, updated for each subsequent wave; social and family history variables and GIS-linked environmental data; basic data on pension plans; event history calendar methodology to facilitate recall of employment spells (2001). The reporting unit is the family: single person living alone or sharing a household with other non-relatives; group of people related by blood, marriage, or adoption; unmarried couple living together in what appears to be a fairly permanent arrangement. Interviews were conducted annually from 1968 through 1997; biennial interviewing began in 1999. There is an oversample of Blacks (30%). Waves 1990 through 1995 included a 20% Hispanic oversample; within the Hispanic oversample, Cubans and Puerto Ricans were oversampled relative to Mexicans. All data from 1994 through 2001 are available as public release files; prior waves can be obtained in archive versions. The special files with weights for families are also available. Restricted files include the Geocode Match File with information for 1968 through 2001, the 1968-2001 Death File, and the 1991 Medicare Claims File. * Dates of Study: 1968-2003 * Study Features: Longitudinal, Minority Oversampling * Sample Size: 65,000+ Links * ICPSR Series: http://www.icpsr.umich.edu/icpsrweb/ICPSR/series/00131 * ICPSR 1968-1999: Annual Core Data: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/07439 * ICPSR 1968-1999: Supplemental Files: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03202 * ICPSR 1989-1990: Latino Sample: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03203

  14. B

    Bangladesh BD: Proportion of People Living Below 50 Percent Of Median...

    • ceicdata.com
    Updated Jan 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com, Bangladesh BD: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/bangladesh/social-poverty-and-inequality/bd-proportion-of-people-living-below-50-percent-of-median-income-
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1983 - Dec 1, 2022
    Area covered
    Bangladesh
    Description

    Bangladesh BD: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 14.000 % in 2022. This records an increase from the previous number of 6.100 % for 2016. Bangladesh BD: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 5.250 % from Dec 1983 (Median) to 2022, with 10 observations. The data reached an all-time high of 14.000 % in 2022 and a record low of 3.600 % in 1985. Bangladesh BD: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

  15. Share of urban households in China in 2022, by income class

    • statista.com
    Updated Feb 19, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). Share of urban households in China in 2022, by income class [Dataset]. https://www.statista.com/statistics/701623/china-share-of-urban-household-by-class/
    Explore at:
    Dataset updated
    Feb 19, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    China
    Description

    This statistic shows a forecast of the distribution of urban households across income classes in China in 2022. In 2022, around 54 percent of the Chinese urban households would become upper middle class, while nine percent would be considered as wealthy.

  16. Rent increase dwellings; income class

    • cbs.nl
    • dexes.eu
    • +2more
    xml
    Updated Sep 4, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Centraal Bureau voor de Statistiek (2024). Rent increase dwellings; income class [Dataset]. https://www.cbs.nl/en-gb/figures/detail/84825ENG
    Explore at:
    xmlAvailable download formats
    Dataset updated
    Sep 4, 2024
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

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

    Time period covered
    2015 - 2024
    Area covered
    The Netherlands
    Description

    This table includes figures on the average increase of rent broken down by income class. A distinction is made here between rental of regulated dwellings by social and other landlords and liberalised rental.

    Data available from: 2015.

    Status of the figures: The figures in this table are definitive.

    Changes as of 4 September 2024: The figures of 2024 have been published.

    Changes as of 8 September 2023: The category 'middle income' has been added to the table.

    When will new figures be published? New figures of 2025 will become available in September 2025.

  17. o

    Data from: The Social Class Test Gap: A Worldwide Investigation of the Role...

    • osf.io
    Updated Apr 17, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nele Claes; Smeding; Nicolas Sommet (2024). The Social Class Test Gap: A Worldwide Investigation of the Role of Academic Anxiety and Income Inequality in Standardized Test Score Disparities [Dataset]. https://osf.io/92bnw
    Explore at:
    Dataset updated
    Apr 17, 2024
    Dataset provided by
    Center For Open Science
    Authors
    Nele Claes; Smeding; Nicolas Sommet
    Description

    No description was included in this Dataset collected from the OSF

  18. c

    System of Social Indicators for the Federal Republic of Germany: Socio...

    • datacatalogue.cessda.eu
    Updated Mar 22, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Noll, Heinz-Herbert; Weick, Stefan (2024). System of Social Indicators for the Federal Republic of Germany: Socio Economic Classification and Social Stratification [Dataset]. http://doi.org/10.4232/1.14254
    Explore at:
    Dataset updated
    Mar 22, 2024
    Dataset provided by
    GESIS - Leibniz Institut für Sozialwissenschaften, Mannheim
    Authors
    Noll, Heinz-Herbert; Weick, Stefan
    Time period covered
    Jan 1, 1950 - Dec 31, 2013
    Area covered
    Germany
    Variables measured
    Political-administrative area
    Measurement technique
    Aggregation
    Description

    The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to observe them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the dashboard, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
    The data on the area of life “Socio Economic Classification and Social Stratification” is composed as follows:

    Intergenerational mobility: employed people in the upper service class without intergenerational mobility, employed people in the lower service class without intergenerational mobility, employed skilled workers and technicians without intergenerational mobility, employed unskilled workers without intergenerational mobility, employed self-employed people without intergenerational mobility, employed people in agricultural professions without intergenerational mobility. Social mobility: proportion of class-homogeneous marriages among men and women in the upper service class, proportion of class-homogeneous marriages among men and women in the lower service class, proportion of class-homogeneous marriages among men and women - skilled workers and technicians, proportion of class-homogeneous marriages among men and women - unskilled workers, share of class-homogeneous marriages among men and women - self-employed, share of class-homogeneous marriages among men and women with agricultural professions. Socio-economic breakdown of the population: Number of private households according to participation in the working life of the reference person, share of private households according to participation in the working life of the reference person, number of private households according to the occupational status of the reference person, share of private households according to the occupational status of the reference person, share of the population earning a living through employment , share of the population earning a living through unemployment benefits and assistance, share of the population earning a living through pensions, share of the population earning a living from family members, share of self-employed people in all employed people, share of helping family members in all employed people, share of civil servants in all employed people, share of employees in all employed people , proportion of workers in all employed persons, employed people in the upper service class, employed people in the lower service class, employed people - skilled workers and technicians, employed people - unskilled workers, employed people - self-employed, employed people with agricultural professions. Subjective class classification: Population according to subjective class classification (working class, middle class, upper middle and upper class, none of these classes).

  19. Average Monthly Household Income Among Resident Households by Age Group of...

    • data.gov.sg
    Updated Nov 8, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Singapore Department of Statistics (2024). Average Monthly Household Income Among Resident Households by Age Group of Main Income Earner and Type of Dwelling (Household Expenditure Survey 2017/18) [Dataset]. https://data.gov.sg/datasets/d_c1002c75e01ede0b6cf79979ee1b4cbe/view
    Explore at:
    Dataset updated
    Nov 8, 2024
    Dataset authored and provided by
    Singapore Department of Statistics
    License

    https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence

    Description

    Source: SINGAPORE DEPARTMENT OF STATISTICS

    Data Last Updated: 31/07/2019

    Update Frequency: 5 years

    Survey period: Household Expenditure Survey 2017/18

    Footnotes: Income data include employer CPF contributions.

    Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/16483

  20. International Social Survey Programme: Social Inequality IV - ISSP 2009

    • datacatalogue.cessda.eu
    • search.gesis.org
    • +2more
    Updated Jan 25, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jorrat, Jorge Raúl; Evans, Ann; Haller, Max; Hadler, Markus; Segovia, Carolina; Bian, Yanjie; Li, Lulu; Institute for Social Research, Zagreb; Papageorgiou, Bambos; Simonová, Natalie; Matějů, Petr; Clement, Sanne L.; Andersen, Jørgen G.; Harrits, Gitte S.; Gundelach, Peter; Kjær, Ulrik; Lüchau, Peter; Fridberg, Torben; Jæger, Mads; Helemäe, Jelena; Täht, Kadri; Pashkov, Marii; Carton, Ann; Blom, Raimo; Melin, Harri; Forsé, Michel; Lemel, Yannick; Wolf, Christof; Park, Alison; Robert, Peter; Ólafsdóttir, Sigrún; Bernburg, Jón Gunnar; Lewin-Epstein, Noah; Meraviglia, Cinzia; Hara, Miwako; Nishi, Kumiko; Aramaki, Hiroshi; Tabuns, Aivars; Koroleva, Ilze; Krupavičius, Algis; Gendall, Philip; Skjåk, Knut K.; Kolsrud, Kirstine; Mortensen, Anne K.; Social Weather Stations, Quezon City; Cichomski, Bogdan; Vala, Jorge; Khakhulina, Ludmilla; Ramos, Alice; Institute for Sociology of Slovak Academy of Sciences, Bratislava; Hafner-Fink, Mitja; Malnar, Brina; Toš, Niko; Struwig, Jare; Kim, Sang-Wook; Diez-Nicholas, Juan; Edlund, Jonas; Svallfors, Stefan; Joye, Dominique; Chang, Ying-hwa; Kalaycıoğlu, Ersin; Çarkoğlu, Ali; Paniotto, Volodimir; Makejev, S.; Smith, Tom W.; Marsden, Peter V.; Hout, Michael; Briceño-León, Roberto; Ávila, Olga; Camardiel, Alberto (2024). International Social Survey Programme: Social Inequality IV - ISSP 2009 [Dataset]. http://doi.org/10.4232/1.12777
    Explore at:
    Dataset updated
    Jan 25, 2024
    Dataset provided by
    TARKI Social Research Institute
    Vlaamse Overheid, Studiedienst van de Vlaamse Regering (Research Centre of the Flemish Government) (SVR), Flanders (Belgium)
    Slovakian Republic
    Centro de Estudios Públicos (CEP), Santiago, Chile
    Institute for Social Studies, Warsaw University (ISS UW), Warsaw, Poland
    Tallinn University, Tallinn, Estonia
    Instituto de Ciências Sociais da Universidade de Lisboa, Portugal
    The Australian National University, Canberra, Australia
    Human Sciences Research Council (HSRC), Pretoria, South Africa
    Institute of Philosophy and Sociology, University of Latvia, Latvia
    Boston University, Boston, USA
    Department of Political Science, University of Aarhus, Aarhus, Denmark
    Philippines
    The Danish National Institute of Social Research, Copenhagen, Denmark
    GESIS Leibniz Institut für Sozialwissenschaften, Mannheim, Germany
    B.I. and Lucille Cohen, Institute for public opinion research, Tel Aviv, Israel
    Center of Applied Research, Cyprus College, Nicosia, Cyprus
    National Centre for Social Research (NatCen), London, Great Britain
    Policy and Public Administration Institute, Kaunas University of Technology, Kaunas, Lithuania
    Institute of Sociology, Academy of Sciences of the Czech Republic, Praha, Czech Republic
    Department of Political Science, University of Southern Denmark, Odense, Denmark
    LACSO, Laboratorio de Ciencias Sociales, Caracas, Venezuela
    University of Minnesota, Minnesota, USA
    Department of Sociology, Sungkyunkwan University, Seoul, Korea
    CEDOP-UBA, Argentina
    Institute of Philosophy, Education and Study of Religions, University of Southern Denmark, Odense, Denmark
    FRANCE-ISSP (Centre de Recherche en Economie et Statistique, Laboratoire de Sociologie Quantitative), Malakoff, France
    Norwegian Social Science Data Services, Bergen, Norway
    University of Tampere, Finland
    Public Opinion and Mass Communication Research Centre (CJMMK), University of Ljubljana, Slovenia
    Kiev International Institute of Sociology (KIIS), Kiev, Ukraine
    Department of Economics, Politics and Public Administration, Aalborg University, Aalborg, Denmark
    Department of Sociology, Umea University, Umea, Sweden
    Renmin University of China, Beijing, China
    University of Lausanne, Switzerland
    National Opinion Research Center (NORC), Chicago, USA
    Department of Communication, Journalism and Marketing, Massey University, Palmerston North, New Zealand
    Department of Social Structures, Institute of Sociology, National Academy of Sciences of Ukraine (NASU), Kiev, Ukraine
    Institute of Sociology, Academia Sinica, Nankang, Taipei, Taiwan
    Institute of Social Research, University of Eastern Piedmont, Italy
    University of Iceland, Reykjavík, Iceland
    Institut für Soziologie, Universität Graz, Austria
    Croatia
    LACSO/UCV, Laboratorio de Ciencias Sociales, Caracas, Venezuela
    Levada Center, Moscow, Russia
    Istanbul Policy Center-Sabancı University, Istanbul, Turkey
    ASEP, Madrid, Spain
    Department of Sociology, University of Copenhagen, Copenhagen, Denmark
    Agency for Social Analyses (ASA), Bulgaria
    NHK Broadcasting Culture Research Institute, Tokyo, Japan
    Authors
    Jorrat, Jorge Raúl; Evans, Ann; Haller, Max; Hadler, Markus; Segovia, Carolina; Bian, Yanjie; Li, Lulu; Institute for Social Research, Zagreb; Papageorgiou, Bambos; Simonová, Natalie; Matějů, Petr; Clement, Sanne L.; Andersen, Jørgen G.; Harrits, Gitte S.; Gundelach, Peter; Kjær, Ulrik; Lüchau, Peter; Fridberg, Torben; Jæger, Mads; Helemäe, Jelena; Täht, Kadri; Pashkov, Marii; Carton, Ann; Blom, Raimo; Melin, Harri; Forsé, Michel; Lemel, Yannick; Wolf, Christof; Park, Alison; Robert, Peter; Ólafsdóttir, Sigrún; Bernburg, Jón Gunnar; Lewin-Epstein, Noah; Meraviglia, Cinzia; Hara, Miwako; Nishi, Kumiko; Aramaki, Hiroshi; Tabuns, Aivars; Koroleva, Ilze; Krupavičius, Algis; Gendall, Philip; Skjåk, Knut K.; Kolsrud, Kirstine; Mortensen, Anne K.; Social Weather Stations, Quezon City; Cichomski, Bogdan; Vala, Jorge; Khakhulina, Ludmilla; Ramos, Alice; Institute for Sociology of Slovak Academy of Sciences, Bratislava; Hafner-Fink, Mitja; Malnar, Brina; Toš, Niko; Struwig, Jare; Kim, Sang-Wook; Diez-Nicholas, Juan; Edlund, Jonas; Svallfors, Stefan; Joye, Dominique; Chang, Ying-hwa; Kalaycıoğlu, Ersin; Çarkoğlu, Ali; Paniotto, Volodimir; Makejev, S.; Smith, Tom W.; Marsden, Peter V.; Hout, Michael; Briceño-León, Roberto; Ávila, Olga; Camardiel, Alberto
    Time period covered
    Feb 8, 2008 - Jan 16, 2012
    Area covered
    United States, Norway, Denmark
    Measurement technique
    Self-administered questionnaire, Mode of interview differs for the individual countries: partlyface-to-face interviews (partly CAPI) with standardized questionnaire,partly paper and pencil and postal survey
    Description

    The International Social Survey Programme (ISSP) is a continuous programme of cross-national collaboration running annual surveys on topics important for the social sciences. The programme started in 1984 with four founding members - Australia, Germany, Great Britain, and the United States – and has now grown to almost 50 member countries from all over the world. As the surveys are designed for replication, they can be used for both, cross-national and cross-time comparisons. Each ISSP module focuses on a specific topic, which is repeated in regular time intervals. Please, consult the documentation for details on how the national ISSP surveys are fielded. The present study focuses on questions about social inequality.
    Importance of social background, merit, discrimination, corruption and good relations as prerequisites for success in society (wealthy family, well-educated parents, good education, ambitions, hard working, knowing the right people, political connections, giving bribes, person´s race and religion, gender); attitude towards equality of educational opportunity in one´s country (corruption as criteria for social mobility, only students from the best secondary schools have a good chance to obtain a university education, only rich people can afford the costs of attending university, same chances for everyone to enter university, regardless of gender, ethnicity or social background); opinion about own salary: actual occupational earning is adequate; estimation of actual and reasonable earnings for occupational groups: doctor, chairman of a large national corporation, shop assistant, unskilled worker in a factory, cabinet minister in the national government; income differences are too large in the respondent´s country; responsibility of government to reduce income differences; government should provide a decent standard of living for the unemployed and spend less on benefits for poor people; demand for higher taxes for people with high incomes; opinion on taxes for people with high income; justification of better medical supply and better education for people with higher income; perception of class conflicts between social groups in the country (poor and rich people, working class and middle class, management and workers, people at the top of society and people at the bottom); self-assessment and assessment of the family the respondent grew up in on a top-bottom-scale; social position compared to father (social mobility); salary criteria (scale: responsibility, education, needed support for family and children, quality of job performance or hard work at the job); feeling of a just payment; characterisation of the actual and the desired social system of the country, measured by classification on pyramid diagrams (image of society).

    Demography: sex; age; marital status; steady life partner; years of schooling; highest education level; country specific education and degree; current employment status (respondent and partner); hours worked weekly; occupation (ISCO 1988) (respondent and partner); supervising function at work; working for private or public sector or self-employed (respondent and partner); if self-employed: number of employees; trade union membership; earnings of respondent (country specific); family income (country specific); size of household; household composition; party affiliation (left-right); country specific party affiliation; participation in last election; religious denomination; religious main groups; attendance of religious services; self-placement on a top-bottom scale; region (country specific); size of community (country specific); type of community: urban-rural area; country of origin or ethnic group affiliation; occupation status and profession of respondent´s father and mother during the youth of the respondent (ISCO 88); number of books in the parental home during the youth of the respondent (cultural resources); occupational status and profession in the first job and the current job (ISCO 88 and working type); self-assessment of the social class; estimated amount of family wealth (monetary value of assets); work orientation: self-characterisation at this time and in the youth of the respondent concerning his performance at work respectively at school.

    Additionally coded: administrative mode of data-collection; weighting factor; case substitution.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2024). U.S. median household income1970-2020, by income tier [Dataset]. https://www.statista.com/statistics/500385/median-household-income-in-the-us-by-income-tier/
Organization logo

U.S. median household income1970-2020, by income tier

Explore at:
Dataset updated
Aug 7, 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 1970 to 2020, by income tier. In 2020, the median household income for the middle class stood at 90,131 U.S. dollars, which was approximately a 50 percent increase from 1970. However, the median income of upper income households in the U.S. increased by almost 70 percent compared to 1970.

Search
Clear search
Close search
Google apps
Main menu