100+ datasets found
  1. Share of world population living in poverty 1990-2022

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Share of world population living in poverty 1990-2022 [Dataset]. https://www.statista.com/statistics/1341003/poverty-rate-world/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    Over the past 30 years, there has been an almost constant reduction in the poverty rate worldwide. Whereas nearly ** percent of the world's population lived on less than 2.15 U.S. dollars in terms of 2017 Purchasing Power Parity (PPP) in 1990, this had fallen to *** percent in 2022. This is even though the world's population was growing over the same period. However, there was a small increase in the poverty rate during the COVID-19 pandemic in 2020 and 2021, when thousands of people became unemployed overnight. Moreover, the rising cost of living in the aftermath of the pandemic and spurred by the Russian invasion of Ukraine in 2022 meant that many people were struggling to make ends meet. Poverty is a regional problem Poverty can be measured in relative and absolute terms. Absolute poverty concerns basic human needs such as food, clothing, shelter, and clean drinking water, whereas relative poverty looks at whether people in different countries can afford a certain living standard. Most countries that have a high percentage of their population living in absolute poverty, meaning that they are poor compared to international standards, are regionally concentrated. African countries are most represented among the countries in which poverty prevails the most. In terms of numbers, Sub-Saharan Africa and South Asia have the most people living in poverty worldwide. Inequality on the rise How wealth, or the lack thereof, is distributed within the global population and even within countries is very unequal. In 2022, the richest one percent of the world owned almost half of the global wealth, while the poorest 50 percent owned less than two percent in the same year. Within regions, Latin America had the most unequal distribution of wealth, but this phenomenon is present in all world regions.

  2. World Development Indicators on Poverty

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). World Development Indicators on Poverty [Dataset]. https://www.johnsnowlabs.com/marketplace/world-development-indicators-on-poverty/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2019
    Area covered
    World
    Description

    This dataset contains data from the World Development Indicators on Poverty and Shared Prosperity presenting indicators that measure progress toward the World Bank Group’s twin goals of ending extreme poverty by 2030 and promoting shared prosperity in every country in a sustainable manner.

  3. C

    China Poverty Headcount Ratio at Societal Poverty Lines: % of Population

    • ceicdata.com
    Updated Feb 1, 2023
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    CEICdata.com (2023). China Poverty Headcount Ratio at Societal Poverty Lines: % of Population [Dataset]. https://www.ceicdata.com/en/china/social-poverty-and-inequality
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    Dataset updated
    Feb 1, 2023
    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
    China
    Description

    Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 19.000 % in 2021. This records a decrease from the previous number of 20.900 % for 2020. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 31.700 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 72.000 % in 1990 and a record low of 19.000 % in 2021. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;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).

  4. J

    Jordan JO: Poverty Gap at National Poverty Lines: %

    • ceicdata.com
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    CEICdata.com, Jordan JO: Poverty Gap at National Poverty Lines: % [Dataset]. https://www.ceicdata.com/en/jordan/poverty/jo-poverty-gap-at-national-poverty-lines-
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    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, 2008 - Dec 1, 2010
    Area covered
    Jordan
    Description

    Jordan JO: Poverty Gap at National Poverty Lines: % data was reported at 3.600 % in 2010. This records an increase from the previous number of 2.600 % for 2008. Jordan JO: Poverty Gap at National Poverty Lines: % data is updated yearly, averaging 3.100 % from Dec 2008 (Median) to 2010, with 2 observations. The data reached an all-time high of 3.600 % in 2010 and a record low of 2.600 % in 2008. Jordan JO: Poverty Gap at National Poverty Lines: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank: Poverty. Poverty gap at national poverty lines is the mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

  5. d

    Global Subnational Inequality

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Hai-Anh H. Dang; Minh Cong Nguyen; Trong-Anh Trinh (2023). Global Subnational Inequality [Dataset]. http://doi.org/10.7910/DVN/IOGOYE
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Hai-Anh H. Dang; Minh Cong Nguyen; Trong-Anh Trinh
    Description

    The database (version August 2022) is built upon the released Global Subnational Atlas of Poverty (GSAP) (World Bank, 2021). In this database, we assemble a new panel dataset that provides different measures of inequality. This database is generated using household income and consumption surveys from the World Bank’s Global Monitoring Database (GMD), which underlie country official poverty statistics, and offers the most detailed subnational poverty data on a global scale to date. The Global Subnational Atlas of Poverty (GSAP) is produced by the World Bank’s Poverty and Equity Global Practice, coordinated by the Data for Goals (D4G) team, and supported by the six regional statistics teams in the Poverty and Equity Global Practice, and Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) at the World Bank. The Global Monitoring Database (GMD) is the World Bank’s repository of multitopic income and expenditure household surveys used to monitor global poverty and shared prosperity. The household survey data are typically collected by national statistical offices in each country, and then compiled, processed, and harmonized. The process is coordinated by the Data for Goals (D4G) team and supported by the six regional statistics teams in the Poverty and Equity Global Practice. Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) also contributed historical data from before 1990, and recent survey data from Luxemburg Income Studies (LIS). Selected variables have been harmonized to the extent possible such that levels and trends in poverty and other key sociodemographic attributes can be reasonably compared across and within countries over time. The GMD’s harmonized microdata are currently used in Poverty and Inequality Platform (PIP), World Bank’s Multidimensional Poverty Measures (WB MPM), the Global Database of Shared Prosperity (GDSP), and Poverty and Shared Prosperity Reports. Reference: World Bank. (2021). World Bank estimates based on data from the Global Subnational Atlas of Poverty, Global Monitoring Database. World Bank: Washington. https://datacatalog.worldbank.org/search/dataset/0042041

  6. World Bank Subnational Poverty Data

    • kaggle.com
    Updated Feb 28, 2018
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    Brooke Watson (2018). World Bank Subnational Poverty Data [Dataset]. https://www.kaggle.com/brookewatson/worldbank-subnational-poverty/activity
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 28, 2018
    Dataset provided by
    Kaggle
    Authors
    Brooke Watson
    Description

    Context

    This dataset was uploaded to support the Data Science For Good Kiva crowdfunding challenge. In particular, in uploading this dataset, I intend to assist with mapping subnational locations in the Kiva dataset to more accurate geocodes.

    Content

    This dataset contains poverty data at the administrative unit level 1, based on national poverty line(s). Administrative unit level 1 refers to the highest subnational unit level (examples include ‘state’, ‘governorate’, ‘province’). This dataset also provides data and methodology for distinguishing between poverty rates in urban and rural regions.

    This dataset includes one main .csv file: Subnational-PovertyData.csv, which includes a set of poverty indicators at the national and subnational level between the years 1996-2013. Many countries are missing data for multiple years, and no country has data for the years 1997-1999.

    It also includes three metadata .csv files: 1. Subnational-PovertyCountry.csv, which describes the country codes and subregions. 2.Subnational-PovertySeries.csv, which describes the three series indicators for national, urban, and rural poverty headcount ratios. This metadata file also including limitations, statistical methodologies, and development relevance for these metrics. 3. Subnational-Povertyfootnote.csv, which describes the years and sources for all of the country-series combinations.

    Acknowledgements

    This dataset is provided openly by the World Bank. Individual sources for the different data series are available in Subnational-Povertyfootnote.csv.

    This dataset is classified as Public under the Access to Information Classification Policy. Users inside and outside the World Bank can access this dataset. It is licensed under CC-BY 4.0.

    Metadata

    Type: Time Series Topics: Economic Growth Poverty Economy Coverage: IBRD Languages Supported: English Number of Economies: 60 Geographical Coverage: World Access Options: Download, Query Tool Temporal Coverage: 1996 - 2013 Last Updated: April 27, 2015

  7. M

    Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population [Dataset]. https://www.ceicdata.com/en/mexico/social-poverty-and-inequality/multidimensional-poverty-headcount-ratio-world-bank--of-total-population
    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, 2010 - Dec 1, 2022
    Area covered
    Mexico
    Description

    Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 1.700 % in 2022. This records a decrease from the previous number of 2.600 % for 2020. Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 2.900 % from Dec 2010 (Median) to 2022, with 7 observations. The data reached an all-time high of 5.700 % in 2010 and a record low of 1.700 % in 2022. Mexico Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;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).

  8. d

    Global Subnational Atlas of Poverty

    • dataone.org
    Updated Nov 8, 2023
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    Hai-Anh H. Dang; Minh Cong Nguyen; Trong-Anh Trinh (2023). Global Subnational Atlas of Poverty [Dataset]. http://doi.org/10.7910/DVN/MLHFAF
    Explore at:
    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Hai-Anh H. Dang; Minh Cong Nguyen; Trong-Anh Trinh
    Description

    The database (version August 2022) is built upon the released Global Subnational Atlas of Poverty (GSAP) (World Bank, 2021). In this database, we assemble a new panel dataset that provides (headcount) poverty rates using the daily poverty lines of US $1.90, $3.20, and $5.50 (based on the revised 2011 Purchasing Power Parity (PPP) dollars). This database is generated using household income and consumption surveys from the World Bank’s Global Monitoring Database (GMD), which underlie country official poverty statistics, and offers the most detailed subnational poverty data on a global scale to date. The Global Subnational Atlas of Poverty (GSAP) is produced by the World Bank’s Poverty and Equity Global Practice, coordinated by the Data for Goals (D4G) team, and supported by the six regional statistics teams in the Poverty and Equity Global Practice, and Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) at the World Bank. The Global Monitoring Database (GMD) is the World Bank’s repository of multitopic income and expenditure household surveys used to monitor global poverty and shared prosperity. The household survey data are typically collected by national statistical offices in each country, and then compiled, processed, and harmonized. The process is coordinated by the Data for Goals (D4G) team and supported by the six regional statistics teams in the Poverty and Equity Global Practice. Global Poverty & Inequality Data Team (GPID) in Development Economics Data Group (DECDG) also contributed historical data from before 1990, and recent survey data from Luxemburg Income Studies (LIS). Selected variables have been harmonized to the extent possible such that levels and trends in poverty and other key sociodemographic attributes can be reasonably compared across and within countries over time. The GMD’s harmonized microdata are currently used in Poverty and Inequality Platform (PIP), World Bank’s Multidimensional Poverty Measures (WB MPM), the Global Database of Shared Prosperity (GDSP), and Poverty and Shared Prosperity Reports. Reference: World Bank. (2021). World Bank estimates based on data from the Global Subnational Atlas of Poverty, Global Monitoring Database. World Bank: Washington. https://datacatalog.worldbank.org/search/dataset/0042041

  9. World Development Indicators Data Package

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). World Development Indicators Data Package [Dataset]. https://www.johnsnowlabs.com/marketplace/world-development-indicators-data-package/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Description

    This data package contains data on World Development Indicators on Population and Economy, Poverty and Shared Prosperity, People, Environment, Economy, States and Markets and Global links.

  10. G

    Ghana Multidimensional Poverty Headcount Ratio: World Bank: % of total...

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Ghana Multidimensional Poverty Headcount Ratio: World Bank: % of total population [Dataset]. https://www.ceicdata.com/en/ghana/social-poverty-and-inequality/multidimensional-poverty-headcount-ratio-world-bank--of-total-population
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    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, 2012 - Dec 1, 2016
    Area covered
    Ghana
    Description

    Ghana Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 32.800 % in 2016. This records a decrease from the previous number of 33.200 % for 2012. Ghana Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 33.000 % from Dec 2012 (Median) to 2016, with 2 observations. The data reached an all-time high of 33.200 % in 2012 and a record low of 32.800 % in 2016. Ghana Multidimensional Poverty Headcount Ratio: World Bank: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;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).

  11. Female extreme poverty rate worldwide 2515-2030, by region

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Female extreme poverty rate worldwide 2515-2030, by region [Dataset]. https://www.statista.com/statistics/1423615/women-extreme-poverty-rate-world-region/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    World
    Description

    Using a poverty metric of 2.15 U.S. dollars per day, 37 percent of the women in Sub-Saharan Africa were living in extreme poverty in 2023. This is expected to fall to one third by 2023. On the other hand, less than one percent of the population in Europe and North America as well as Australia and New Zealand were living in extreme poverty. Nevertheless, there are also many people in these regions struggling to make ends meet.

  12. Share of population living in extreme poverty, by country, varying years...

    • data.amerigeoss.org
    • data.apps.fao.org
    png, wms, zip
    Updated Mar 14, 2023
    + more versions
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    Food and Agriculture Organization (2023). Share of population living in extreme poverty, by country, varying years (FGGD) [Dataset]. https://data.amerigeoss.org/dataset/847f3f50-8519-11db-b9b2-000d939bc5d8
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    png, wms, zipAvailable download formats
    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Description

    The FGGD extreme poverty map is a global vector datalayer at scale 1:5 000 000. The map depicts the differences among countries with respect to the national population estimated to be living in extreme poverty as of the latest year for which data was available in 2005. Data have been compiled by FAO from data reported in World Bank, WDI Online, as of April 2005.

    Data publication: 2007-06-25

    Supplemental Information:

    This dataset is contained in Module 3 "Socio-economics and nutrition indicators" of Food Insecurity, Poverty and Environment Global GIS Database (FGGD) (FAO, 2007).

    Contact points:

    Metadata Contact: FAO-Data

    Resource Contact: Mirella Salvatore

    Resource constraints:

    copyright

    Online resources:

    Share of population living in extreme poverty, by country, varying years

  13. People living in extreme poverty (World Data Lab)

    • sdgstoday-sdsn.hub.arcgis.com
    Updated Feb 5, 2022
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    Sustainable Development Solutions Network (2022). People living in extreme poverty (World Data Lab) [Dataset]. https://sdgstoday-sdsn.hub.arcgis.com/datasets/people-living-in-extreme-poverty-world-data-lab-1
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    Dataset updated
    Feb 5, 2022
    Dataset authored and provided by
    Sustainable Development Solutions Networkhttps://www.unsdsn.org/
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    This dashboard is part of SDGs Today. Please see sdgstoday.orgExtreme poverty poses a major challenge to the livelihood of current and future generations everywhere and threatens Agenda 2030’s promise of leaving no one behind. The World Poverty Clock developed by the World Data Lab provides real-time poverty estimates through 2030 for nearly all countries. The World Poverty Clock uses publicly available data on income distributions, production factors, and household consumption provided by various international organizations, including the World Bank and the International Monetary Fund (IMF). These organizations compile data provided to them by the local governments, and when this information is not available, the World Poverty Clock uses specific models to estimate poverty in these countries. The models include how individual incomes might change over time using IMF growth forecasts for the medium-term complemented by long-term “shared socio-economic pathways” developed by the International Institute for Applied Systems Analysis (IIASA) and similar analysis developed by the OECD. The World Poverty Clock dataset was updated in February 2021, taking into consideration the COVID-19 pandemic effects on the economy.

  14. Extreme poverty as share of global population in Africa 2025, by country

    • statista.com
    Updated Feb 3, 2025
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    Statista (2025). Extreme poverty as share of global population in Africa 2025, by country [Dataset]. https://www.statista.com/statistics/1228553/extreme-poverty-as-share-of-global-population-in-africa-by-country/
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    Dataset updated
    Feb 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Africa
    Description

    In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

  15. W

    United States of America Poverty rate at $3.2 a day

    • knoema.com
    csv, json, sdmx, xls
    Updated Jul 14, 2025
    + more versions
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    Knoema (2025). United States of America Poverty rate at $3.2 a day [Dataset]. https://knoema.com/atlas/United-States-of-America/Poverty-rate-at-dollar32-a-day
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    sdmx, csv, json, xlsAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Knoema
    Time period covered
    2012 - 2023
    Area covered
    United States
    Variables measured
    Poverty headcount ratio at $3.2 a day based on purchasing-power-parity in constant prices of 2011
    Description

    Poverty rate at $3.2 a day of United States of America remained constant at 1.50 % over the last 1 years. Population below $3.1 a day is the percentage of the population living on less than $3.1 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

  16. W

    United States of America Poverty rate at $1.9 a day

    • knoema.com
    csv, json, sdmx, xls
    Updated Jul 14, 2025
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    Knoema (2025). United States of America Poverty rate at $1.9 a day [Dataset]. https://knoema.com/atlas/United-States-of-America/Poverty-rate-at-dollar19-a-day
    Explore at:
    xls, json, csv, sdmxAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Knoema
    Time period covered
    2012 - 2023
    Area covered
    United States
    Variables measured
    Poverty headcount ratio at $1.9 a day based on purchasing-power-parity in constant prices of 2011
    Description

    Poverty rate at $1.9 a day of United States of America remained stable at 1.20 % over the last 1 years. Population below $1.9 a day is the percentage of the population living on less than $1.9 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

  17. w

    Poverty and Inequality Platform (PIP)

    • data360.worldbank.org
    Updated Apr 18, 2025
    + more versions
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    (2025). Poverty and Inequality Platform (PIP) [Dataset]. https://data360.worldbank.org/en/dataset/WB_PIP
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    Dataset updated
    Apr 18, 2025
    License

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

    Time period covered
    1963 - 2023
    Description

    The Poverty and Inequality Platform (PIP), developed by the World Bank, provides global, regional, and country-level estimates of poverty, inequality, and shared prosperity for 170 economies. PIP is the primary source for the World Bank's poverty and inequality estimates, and it informs many Sustainable Development Goal (SDG) indicators on poverty and inequality. The data, governed by the Global Poverty Working Group (GPWG), are expressed in 2017 Purchasing Power Parity (PPP) prices, with global poverty lines set at $2.15, $3.65, and $6.85 per day.

  18. T

    Nigeria - Poverty Headcount Ratio At National Poverty Line (% Of Population)...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 6, 2013
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    TRADING ECONOMICS (2013). Nigeria - Poverty Headcount Ratio At National Poverty Line (% Of Population) [Dataset]. https://tradingeconomics.com/nigeria/poverty-headcount-ratio-at-national-poverty-line-percent-of-population-wb-data.html
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Aug 6, 2013
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Nigeria
    Description

    Poverty headcount ratio at national poverty lines (% of population) in Nigeria was reported at 40.1 % in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Poverty headcount ratio at national poverty line (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  19. Data from: Multidimensional Poverty Index (MPI)

    • data.amerigeoss.org
    http, pdf, wms
    Updated Apr 23, 2022
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    Food and Agriculture Organization (2022). Multidimensional Poverty Index (MPI) [Dataset]. https://data.amerigeoss.org/dataset/513c4c5b-e29d-4cbb-9911-3d1ce5a4b026
    Explore at:
    pdf, wms, httpAvailable download formats
    Dataset updated
    Apr 23, 2022
    Dataset provided by
    Food and Agriculture Organizationhttp://fao.org/
    License

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

    Description

    Multidimensional Poverty Index (MPI): countries where the MPI is below 0.6. Pixels with a value lower than the specified threshold (0.6) were given a value of 1 (YES response)

    The 2020 Global MPI data and publication "Charting pathways out of multidimensional poverty: Achieving the SDGs" released on 16 July 2020 by the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford and the Human Development Report Office of the United Nations Development Programme (UNDP). The global MPI measures the complexities of poor people’s lives, individually and collectively, each year. This report focuses on how multidimensional poverty has declined. It provides a comprehensive picture of global trends in multidimensional poverty, covering 5 billion people. It probes patterns between and within countries and by indicator, showcasing different ways of making progress. Together with data on the $1.90 a day poverty rate, the trends monitor global poverty in different forms.

    Data revision: 2020-07-16

    Contact points:

    Contact: Admir Jahic UNDP

    Metadata contact: OCB Environment FAO-UN

    Resource constraints:

    license

    Online resources:

    Global Multidimensional Poverty Index

    Charting pathways out of multidimensional poverty: Achieving the SDGs

  20. Ghana Poverty rate at national poverty line

    • knoema.com
    csv, json, sdmx, xls
    Updated Jul 14, 2025
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    Knoema (2025). Ghana Poverty rate at national poverty line [Dataset]. https://knoema.com/atlas/Ghana/Poverty-rate-at-national-poverty-line
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    json, csv, sdmx, xlsAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    2005 - 2016
    Area covered
    Ghana
    Variables measured
    Poverty headcount ratio at national poverty line
    Description

    Poverty rate at national poverty line of Ghana slipped by 3.31% from 24.2 % in 2012 to 23.4 % in 2016. Since the 24.14% drop in 2012, poverty rate at national poverty line declined by 3.31% in 2016. National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys.

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Statista (2025). Share of world population living in poverty 1990-2022 [Dataset]. https://www.statista.com/statistics/1341003/poverty-rate-world/
Organization logo

Share of world population living in poverty 1990-2022

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
World
Description

Over the past 30 years, there has been an almost constant reduction in the poverty rate worldwide. Whereas nearly ** percent of the world's population lived on less than 2.15 U.S. dollars in terms of 2017 Purchasing Power Parity (PPP) in 1990, this had fallen to *** percent in 2022. This is even though the world's population was growing over the same period. However, there was a small increase in the poverty rate during the COVID-19 pandemic in 2020 and 2021, when thousands of people became unemployed overnight. Moreover, the rising cost of living in the aftermath of the pandemic and spurred by the Russian invasion of Ukraine in 2022 meant that many people were struggling to make ends meet. Poverty is a regional problem Poverty can be measured in relative and absolute terms. Absolute poverty concerns basic human needs such as food, clothing, shelter, and clean drinking water, whereas relative poverty looks at whether people in different countries can afford a certain living standard. Most countries that have a high percentage of their population living in absolute poverty, meaning that they are poor compared to international standards, are regionally concentrated. African countries are most represented among the countries in which poverty prevails the most. In terms of numbers, Sub-Saharan Africa and South Asia have the most people living in poverty worldwide. Inequality on the rise How wealth, or the lack thereof, is distributed within the global population and even within countries is very unequal. In 2022, the richest one percent of the world owned almost half of the global wealth, while the poorest 50 percent owned less than two percent in the same year. Within regions, Latin America had the most unequal distribution of wealth, but this phenomenon is present in all world regions.

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