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

    • statista.com
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    Statista, Share of world population living in poverty 1990-2022 [Dataset]. https://www.statista.com/statistics/1341003/poverty-rate-world/
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    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. Global access to electricity as a share of population 1990-2022

    • statista.com
    Updated May 30, 2025
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    Statista Research Department (2025). Global access to electricity as a share of population 1990-2022 [Dataset]. https://www.statista.com/topics/781/poverty/
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    Dataset updated
    May 30, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The share of the global population with access to electricity in 2022 was roughly 91 percent, up from 71.4 percent in 1990. South Sudan was the least electrified country worldwide, followed by Burundi.

  4. H

    Global Subnational Atlas of Poverty

    • dataverse.harvard.edu
    • dataone.org
    Updated Jan 14, 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
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 14, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Hai-Anh H. Dang; Minh Cong Nguyen; Trong-Anh Trinh
    License

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

    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

  5. Gender poverty gaps worldwide 2020-2021 (with a forecast to 2030), by gender...

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Gender poverty gaps worldwide 2020-2021 (with a forecast to 2030), by gender [Dataset]. https://www.statista.com/statistics/1219896/gender-poverty-gaps-worldwide-by-gender/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Worldwide
    Description

    According to a 2020 survey, the coronavirus (COVID-19) crisis will increase female poverty worldwide. Globally, *** million women aged 15 years and older will be living on less than 1.90 U.S. dollars per day in 2021, compared to *** million men. The gender poverty gap is expected to increase by 2030, as women will still be the majority of the world's extreme poor.

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

    • statista.com
    Updated Nov 28, 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
    Nov 28, 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.

  7. 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/
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    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.

  8. w

    Learning Poverty Global Database

    • data360.worldbank.org
    Updated Apr 18, 2025
    + more versions
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    (2025). Learning Poverty Global Database [Dataset]. https://data360.worldbank.org/en/dataset/WB_LPGD
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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
    2001 - 2023
    Area covered
    Bangladesh, Ireland, Thailand, Vietnam, Ukraine, Uganda, Lesotho, Uzbekistan, Georgia, Luxembourg
    Description

    Will all children be able to read by 2030? The ability to read with comprehension is a foundational skill that every education system around the world strives to impart by late in primary school—generally by age 10. Moreover, attaining the ambitious Sustainable Development Goals (SDGs) in education requires first achieving this basic building block, and so does improving countries’ Human Capital Index scores. Yet past evidence from many low- and middle-income countries has shown that many children are not learning to read with comprehension in primary school. To understand the global picture better, we have worked with the UNESCO Institute for Statistics (UIS) to assemble a new dataset with the most comprehensive measures of this foundational skill yet developed, by linking together data from credible cross-national and national assessments of reading. This dataset covers 115 countries, accounting for 81% of children worldwide and 79% of children in low- and middle-income countries. The new data allow us to estimate the reading proficiency of late-primary-age children, and we also provide what are among the first estimates (and the most comprehensive, for low- and middle-income countries) of the historical rate of progress in improving reading proficiency globally (for the 2000-17 period). The results show that 53% of all children in low- and middle-income countries cannot read age-appropriate material by age 10, and that at current rates of improvement, this “learning poverty” rate will have fallen only to 43% by 2030. Indeed, we find that the goal of all children reading by 2030 will be attainable only with historically unprecedented progress. The high rate of “learning poverty” and slow progress in low- and middle-income countries is an early warning that all the ambitious SDG targets in education (and likely of social progress) are at risk. Based on this evidence, we suggest a new medium-term target to guide the World Bank’s work in low- and middle- income countries: cut learning poverty by at least half by 2030. This target, together with improved measurement of learning, can be as an evidence-based tool to accelerate progress to get all children reading by age 10.

    For further details, please refer to https://thedocs.worldbank.org/en/doc/e52f55322528903b27f1b7e61238e416-0200022022/original/Learning-poverty-report-2022-06-21-final-V7-0-conferenceEdition.pdf

  9. 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

  10. A

    Argentina Poverty Line: Total Basic Basket

    • ceicdata.com
    Updated Nov 15, 2025
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    CEICdata.com (2025). Argentina Poverty Line: Total Basic Basket [Dataset]. https://www.ceicdata.com/en/argentina/indigence-and-poverty-lines-national-statistics--census-institute/poverty-line-total-basic-basket
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    Dataset updated
    Nov 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
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Argentina
    Description

    Argentina Poverty Line: Total Basic Basket data was reported at 356,073.460 USD in Mar 2025. This records an increase from the previous number of 342,370.040 USD for Feb 2025. Argentina Poverty Line: Total Basic Basket data is updated monthly, averaging 15,716.435 USD from Apr 2016 (Median) to Mar 2025, with 108 observations. The data reached an all-time high of 356,073.460 USD in Mar 2025 and a record low of 3,663.660 USD in Apr 2016. Argentina Poverty Line: Total Basic Basket data remains active status in CEIC and is reported by National Institute of Statistics and Censuses. The data is categorized under Global Database’s Argentina – Table AR.G013: Indigence and Poverty Lines: National Statistics & Census Institute.

  11. Female extreme poverty rate worldwide 2015-2030, by region

    • statista.com
    Updated Dec 15, 2023
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    Statista (2023). Female extreme poverty rate worldwide 2015-2030, by region [Dataset]. https://www.statista.com/statistics/1423615/women-extreme-poverty-rate-world-region/
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    Dataset updated
    Dec 15, 2023
    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, 38.7 percent of the women in Sub-Saharan Africa were living in extreme poverty in 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. Poverty rates in OECD countries 2022

    • statista.com
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    Statista, Poverty rates in OECD countries 2022 [Dataset]. https://www.statista.com/statistics/233910/poverty-rates-in-oecd-countries/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

    The significance of the OECD

    The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

    Poverty in the United States

    In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.

  13. Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition...

    • data.nasa.gov
    Updated Apr 23, 2025
    + more versions
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    nasa.gov (2025). Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition - Dataset - NASA Open Data Portal [Dataset]. https://data.nasa.gov/dataset/poverty-mapping-project-global-subnational-prevalence-of-child-malnutrition
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition data set consists of estimates of the percentage of children with weight-for-age z-scores that are more than two standard deviations below the median of the NCHS/CDC/WHO International Reference Population. Data are reported for the most recent year with subnational information available at the time of development. The data products include a shapefile (vector data) of percentage rates, grids (raster data) of rates (per thousand in order to preserve precision in integer format), the number of children under five (the rate denominator), and the number of underweight children under five (the rate numerator), and a tabular data set of the same and associated data. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

  14. C

    Chile Poverty Statistics: Female

    • ceicdata.com
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    CEICdata.com, Chile Poverty Statistics: Female [Dataset]. https://www.ceicdata.com/en/chile/national-socioeconomic-characterization-survey-poverty-situation/poverty-statistics-female
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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, 2006 - Dec 1, 2017
    Area covered
    Chile
    Description

    Chile Poverty Statistics: Female data was reported at 836,009.000 Person in 2017. This records a decrease from the previous number of 1,115,809.000 Person for 2015. Chile Poverty Statistics: Female data is updated yearly, averaging 1,715,728.500 Person from Dec 2006 (Median) to 2017, with 6 observations. The data reached an all-time high of 2,455,020.000 Person in 2006 and a record low of 836,009.000 Person in 2017. Chile Poverty Statistics: Female data remains active status in CEIC and is reported by Ministry of Social Development. The data is categorized under Global Database’s Chile – Table CL.H020: National Socio-Economic Characterization Survey: Poverty Situation.

  15. d

    Poverty Mapping Project: Small Area Estimates of Poverty and Inequality

    • search.dataone.org
    • dataverse.harvard.edu
    • +4more
    Updated Oct 29, 2025
    + more versions
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    Center for International Earth Science Information Network - CIESIN - Columbia University (2025). Poverty Mapping Project: Small Area Estimates of Poverty and Inequality [Dataset]. http://doi.org/10.7910/DVN/RKRW8Q
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    Dataset updated
    Oct 29, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Center for International Earth Science Information Network - CIESIN - Columbia University
    Time period covered
    Jan 1, 1990 - Dec 31, 2002
    Description

    The Poverty Mapping Project: Small Area Estimates of Poverty and Inequality data set consists of consumption-based poverty, inequality and related measures for subnational administrative units in approximately twenty countries throughout Africa, Asia, Europe, North America, and South America. These measures are derived on a country-level basis from a combination of census and survey data using small area estimates techniques. The collection of data have been compiled, integrated and standardized from the original data providers into a unified spatially referenced and globally consistent data set. The data products include shapefiles (vector data), tabular data sets (csv format), and centroids (csv file with latitude and longitude of a geographic unit and associated poverty estimates). Additionally, a data catalog (xls format) containing detailed information and documentation is provided. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with a number of external data providers. To provide high spatial resolution subnational estimates of poverty and inequality for use by a wide user community for interdisciplinary studies of poverty, inequality and the environment.

  16. d

    World's Women Reports

    • search.dataone.org
    • dataverse.harvard.edu
    • +1more
    Updated Nov 21, 2023
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    Harvard Dataverse (2023). World's Women Reports [Dataset]. http://doi.org/10.7910/DVN/EVWPN6
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Description

    Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

  17. The World Bank's Poverty and Equity Metrics

    • kaggle.com
    zip
    Updated Feb 28, 2018
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    Carrie (2018). The World Bank's Poverty and Equity Metrics [Dataset]. https://www.kaggle.com/carrie1/the-world-banks-poverty-and-equity-metrics
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    zip(64496 bytes)Available download formats
    Dataset updated
    Feb 28, 2018
    Authors
    Carrie
    License

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

    Description

    This dataset is from The World Bank's DataBank, which houses a variety of databases. It contains 44 series on 184 counties over the past five years. Topics range from income distribution, annualized growth per capita, poverty headcount, and much more. Please note that some countries do not have data for particular series and/or years due to data collection challenges. This data can be applied to the Kiva Crowdfunding Data Science for Good challenge by providing insight into what countries are in greatest need of funding.

    More about The World Bank: With 189 member countries, staff from more than 170 countries, and offices in over 130 locations, the World Bank Group is a unique global partnership: five institutions working for sustainable solutions that reduce poverty and build shared prosperity in developing countries.

    The image is from unsplash.com.

  18. i

    Grant Giving Statistics for Global Poverty Project Inc

    • instrumentl.com
    Updated Mar 24, 2021
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    (2021). Grant Giving Statistics for Global Poverty Project Inc [Dataset]. https://www.instrumentl.com/990-report/global-poverty-project-inc-1fbd5e41-4639-4037-9154-fae49348252d
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    Dataset updated
    Mar 24, 2021
    Variables measured
    Total Assets, Total Giving, Average Grant Amount
    Description

    Financial overview and grant giving statistics of Global Poverty Project Inc

  19. Global Poverty

    • gis-for-secondary-schools-schools-be.hub.arcgis.com
    Updated Jul 23, 2014
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    Urban Observatory by Esri (2014). Global Poverty [Dataset]. https://gis-for-secondary-schools-schools-be.hub.arcgis.com/datasets/UrbanObservatory::global-poverty
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    Dataset updated
    Jul 23, 2014
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Description

    Poverty affects billions of people around the globe. On a daily basis, they face low wages and substandard health, education, and living standards. Because of this, poverty must be understood and approached as a multidimensional issue. Through the use of storytelling, videos, and interactive maps, this Map Journal takes a look at one method of measuring global poverty. This measure, called the Multidimensional Poverty Index (MPI), addresses poverty through an integrative approach.For more information about the Multidimensional Poverty Index, click here.

  20. Projected female poverty worldwide 2030, by region

    • statista.com
    Updated Oct 19, 2023
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    Statista (2023). Projected female poverty worldwide 2030, by region [Dataset]. https://www.statista.com/statistics/1418058/projected-female-poverty-headcount/
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    Dataset updated
    Oct 19, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Latin America
    Description

    Poverty is expected to remain a global problem over the next decade, and many women will still experience extreme poverty in 2030. The data shows the millions of women predicted to live under each international poverty line, 1.90, 3.20, and 5.50 U.S. dollars per day. Sub-Saharan Africa is forecast to have the highest number of women under each poverty line, followed by Central Asia and South-Eastern Asia.

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

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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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