6 datasets found
  1. Forecast of the global middle class population 2015-2030

    • statista.com
    Updated Jan 23, 2025
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    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/
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    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.

  2. Pre and post COVID-19 size of income tiers in India 2020

    • statista.com
    Updated Jul 10, 2023
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    Statista (2023). Pre and post COVID-19 size of income tiers in India 2020 [Dataset]. https://www.statista.com/statistics/1266075/india-pre-and-post-covid-income-tier-size/
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    Dataset updated
    Jul 10, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    India
    Description

    According to data published by the Pew Research Center, India is estimated to have had a shrinking middle class as a result of the global recession brought on by the COVID-19 pandemic. It is estimated that the number of people in the middle income tier in India decreased from 99 million to 66 million following the COVID-19 global recession.

  3. Changes in income tiers as a result of COVID-19 global recession in India...

    • statista.com
    Updated Jul 10, 2023
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    Statista (2023). Changes in income tiers as a result of COVID-19 global recession in India 2020 [Dataset]. https://www.statista.com/statistics/1266065/india-changes-in-income-tiers/
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    Dataset updated
    Jul 10, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    India
    Description

    According to data published by the Pew Research Center, India is estimated to have had a shrinking middle class as a result of the global recession brought on by the COVID-19 pandemic. It is estimated that the number of people in India living on less than $2 per day grew by 75 million people in 2020.

  4. International Social Survey Programme: Social Inequality V - ISSP 2019

    • datacatalogue.cessda.eu
    • dbk.gesis.org
    • +2more
    Updated Jan 25, 2024
    + more versions
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    Steinmetz, Stephanie; Sapin, Marlène; Joye, Dominique; Gonzalez, Ricardo; Hamplová, Dana; Krejčí, Jindřich; Wolf, Christof; Scholz, Evi; Jutz, Regina; Hochman, Oshrat; Clement, Sanne L.; Melin, Harri; Borg, Sami; Marinović Jerolimov, Dinka; Pedrazzani, Andrea; Vegetti, Federico; Kobayashi, Toshiyuki; Murata, Hiroko; Milne, Barry; Randow, Martin von; Guerrero, Linda Luz; Labucay, Iremae; Karaeva, Olga; Hafner Fink, Mitja; Malnar, Brina; Bureekul, Thawilwadee; Sangmahamad, Ratchawadee; Udompong, Lertporn; Struwig, Jare; Roberts, Benjamin; Ngungu, Mercy; Gordon, Steven; Dimova, Lilia; Chengelova, Emilia; Phillips, Miranda; Jónsdóttir, Guðbjörg A.; Ólafsdóttir, Sigrún; Bernburg, Jón G.; Tryggvadóttir, Guðný B.; Lewin-Epstein, Noah; Krupavičius, Algis; Sno, Tamira; Ganzeboom, Harry; Fu, Yang-chih; Höllinger, Franz; Hadler, Markus; Aschauer, Wolfgang; Eder, Anja; Bacher, Johann; Prandner, Dimitri; Gonthier, Frédéric; Zmerli, Sonja; Bréchon, Pierre; Astor, Sandrine; Zolotoukhine, Erik; Skjåk, Knut Kalgraff; Edlund, Jonas; Briceño-León, Roberto; McEachern, Steven; Gray, Matthew; Evans, Ann; Zammit, Adam; Davern, Michael; Bautista, Rene; Smith, Tom W.; Freese, Jeremy; Morgan, Stephen L. (2024). International Social Survey Programme: Social Inequality V - ISSP 2019 [Dataset]. http://doi.org/10.4232/1.14009
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    Dataset updated
    Jan 25, 2024
    Dataset provided by
    Finnish Social Science Data Archive
    VU Amsterdam, Netherlands
    Institute of Sociology, Academia Sinica, Taipei City, Taiwan
    Levada Center, Moscow, Russia
    Institute for Social Research, Zagreb, Croatia
    Department of Social and Political Sciences, University of Milan, Italy
    National Centre for Social Research (NatCen), London, Great Britain
    Institut für Soziologie, Universität Graz, Austria
    Institute of Sociology of the Czech Academy of Sciences, Prague, Czech Republic
    Anton de Kom University of Suriname, Paramaribo, Suriname
    Department of Sociology, Umeå University, Sweden
    Institute of Philosophy and Sociology at BAS (IPS-BAS), Sofia, Bulgaria & Agency for Social Analyses (ASA), Bulgaria
    Social Weather Stations, Quezon City, Philippines
    Social Science Research Institute, University of Iceland, Reykjavik, Iceland
    Human Sciences Research Council (HSRC), Pretoria, South Africa
    GESIS Leibniz Institute for the Social Sciences, Mannheim, Germany
    Australian Consortium for Political and Social Research, Inc. (ACSPRI), Black Rock, Melbourne Victoria, Australia;
    NHK (Japan Broadcasting Corporation), Tokyo, Japan
    Sciences Po Grenoble - Université Grenoble Alpes - Pacte - CNRS, France
    Department of Political Science, Aalborg University, Aalborg, Denmark
    The University of Auckland, New Zealand
    ANU Centre for Social Research and Methods (ANUCSRM), Australian National University, Canberra, Australia
    Centro de Estudios Públicos (CEP), Santiago, Chile
    B.I. and Lucille Cohen Institute for public opinion, Tel-Aviv, Israel
    Institut für Soziologie, Johannes Kepler Universität Linz, Austria
    FORS, c/o University of Lausanne, Switzerland
    King Prajadhipok’s Institute, Bangkok, Thailand
    Laboratorio de Ciencias Sociales (LACSO), Caracas, Venezuela
    Fachbereich Soziologie und Kulturwissenschaften, Universität Salzburg, Austria
    Norwegian Social Science Data Services, Bergen, Norway
    University of Ljubljana, Faculty of Social Science, Ljubljana, Slovenia
    National Opinion Research Center (NORC) at the University of Chicago, Chicago, USA
    Vytautas Magnus University, Kaunas, Lithuania
    Authors
    Steinmetz, Stephanie; Sapin, Marlène; Joye, Dominique; Gonzalez, Ricardo; Hamplová, Dana; Krejčí, Jindřich; Wolf, Christof; Scholz, Evi; Jutz, Regina; Hochman, Oshrat; Clement, Sanne L.; Melin, Harri; Borg, Sami; Marinović Jerolimov, Dinka; Pedrazzani, Andrea; Vegetti, Federico; Kobayashi, Toshiyuki; Murata, Hiroko; Milne, Barry; Randow, Martin von; Guerrero, Linda Luz; Labucay, Iremae; Karaeva, Olga; Hafner Fink, Mitja; Malnar, Brina; Bureekul, Thawilwadee; Sangmahamad, Ratchawadee; Udompong, Lertporn; Struwig, Jare; Roberts, Benjamin; Ngungu, Mercy; Gordon, Steven; Dimova, Lilia; Chengelova, Emilia; Phillips, Miranda; Jónsdóttir, Guðbjörg A.; Ólafsdóttir, Sigrún; Bernburg, Jón G.; Tryggvadóttir, Guðný B.; Lewin-Epstein, Noah; Krupavičius, Algis; Sno, Tamira; Ganzeboom, Harry; Fu, Yang-chih; Höllinger, Franz; Hadler, Markus; Aschauer, Wolfgang; Eder, Anja; Bacher, Johann; Prandner, Dimitri; Gonthier, Frédéric; Zmerli, Sonja; Bréchon, Pierre; Astor, Sandrine; Zolotoukhine, Erik; Skjåk, Knut Kalgraff; Edlund, Jonas; Briceño-León, Roberto; McEachern, Steven; Gray, Matthew; Evans, Ann; Zammit, Adam; Davern, Michael; Bautista, Rene; Smith, Tom W.; Freese, Jeremy; Morgan, Stephen L.
    Time period covered
    Nov 20, 2018 - May 5, 2022
    Area covered
    Denmark, Philippines, Sweden, Iceland, Bolivarian Republic of, South Africa, Chile, Israel, Switzerland, Suriname
    Measurement technique
    Self-administered questionnaire: Paper, Self-administered questionnaire: Web-based (CAWI), Face-to-face interview: Computer-assisted (CAPI/CAMI), Web-based interview, Telephone interview, Face-to-face interview: Paper-and-pencil (PAPI)
    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 different opportunities for getting ahead (wealthy family, well-educated parents, good education, hard work, knowing the right people, political connections, giving bribes, person´s race and religion, gender); estimation of actual and reasonable earnings for occupational groups: doctor in general practice, chairman of a large national corporation, shop assistant, unskilled worker in a factory, cabinet minister in the national government; concerns about inequality: income differences are too large in respondent´s country; feeling angry about differences in wealth between the rich and the poor (10 point scale); rating the fairness of income distribution in the country.

    Social policy and redistribution: responsibility of the government to reduce income differences, the government should provide a decent standard of living for the unemployed; Reducing inequality by market actors: responsibility of private companies to reduce the differences in pay between their employees; market actor with the greatest responsibility for reducing differences in income (private companies, government, trade-unions, high-income individuals themselves, low-income individuals themselves, income differences do not need to be reduced); government inefficacy: most politicians in the country do not care about reducing the differences in income between people with high incomes and people with low incomes; rating of the government´s success in reducing the differences in income; opinion on taxation (people with high incomes should pay a larger share of their income in taxes than those with low incomes, the same share, or a smaller share); general rating of taxes in the country as much too high, too high, about right, too low, or much too low; market inequality in social services (just or unjust that people with higher incomes can buy better health care/ better education for their children than people with lower incomes); perceptions of global inequality (present economic differences between rich and poor countries are too large, people in wealthy countries should make an additional tax contribution to help people in poor countries, people from poor countries should be allowed to work in wealthy countries).

    Social conflict: rating of social conflicts between different social groups (poor people and rich people, the working class and die middle class, management and workers, young people and older people, people born in the country and people from other countries who have come to live in the country).

    Subjective social class / class mobility: Top-Bottom self-placement; Top-Bottom placement of the family the respondent grew up in; Top-Bottom self-placement in 10 years; subjective social class.

    Pay criteria: importance of different pay criteria (how much responsibility goes with the job, the number of years spent in education and training, whether the person has children to support, how well he or she does the job).

    Characterisation of the actual and the preferred type of society of the country, measured by classification on pyramid diagrams (image of society).

    Lived experience of inequality: frequency of contact with people who are a lot poorer than the respondent; frequency of contact with people who are a lot richer than the respondent.

    Economic insecurity: difficulties to make ends meet from total household´s income currently and during the next 12 months; frequency of how often a meal is skipped because there is not enough money for food.

    Social trust (people can be trusted vs. can´t be too careful in dealing with people).

    Background questions: Objective social mobility: father’s and mother´s employment relationship in respondent´s youth; main occupation of father and mother in respondent´s youth.

    Optional variables: Lay explanations of inequality (workers would not bother to get skills and qualifications unless they were paid extra for having them, large differences in income are necessary for country´s prosperity, inequality continues because it benefits the rich and powerful, inequality continues to exist because ordinary people don´t join together to get rid of it).

    Perceptions of global inequality: rating of differences in wealth between rich and poor countries as fair or unfair....

  5. Proportion of population protected from catastrophic health expenditure upon...

    • plos.figshare.com
    xls
    Updated Jan 26, 2024
    + more versions
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    Emily R. Smith; Pamela Espinoza; Madeline Metcalf; Osondu Ogbuoji; Cesia Cotache-Condor; Henry E. Rice; Mark G. Shrime (2024). Proportion of population protected from catastrophic health expenditure upon out-of-pocket costs reduction for pediatric surgery by income quintile and WHO region. [Dataset]. http://doi.org/10.1371/journal.pgph.0002872.t002
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    xlsAvailable download formats
    Dataset updated
    Jan 26, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Emily R. Smith; Pamela Espinoza; Madeline Metcalf; Osondu Ogbuoji; Cesia Cotache-Condor; Henry E. Rice; Mark G. Shrime
    License

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

    Description

    Proportion of population protected from catastrophic health expenditure upon out-of-pocket costs reduction for pediatric surgery by income quintile and WHO region.

  6. f

    Descriptive Statistics by World Bank Income Groups, in FTARs.

    • plos.figshare.com
    xls
    Updated Jun 13, 2023
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    Athanasios Gkekas; Benoit Varenne; Nicole Stauf; Habib Benzian; Stefan Listl (2023). Descriptive Statistics by World Bank Income Groups, in FTARs. [Dataset]. http://doi.org/10.1371/journal.pone.0275111.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Athanasios Gkekas; Benoit Varenne; Nicole Stauf; Habib Benzian; Stefan Listl
    License

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

    Description

    Descriptive Statistics by World Bank Income Groups, in FTARs.

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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/
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Forecast of the global middle class population 2015-2030

Explore at:
10 scholarly articles cite this dataset (View in Google Scholar)
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.

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