100+ datasets found
  1. 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.

  2. 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.

  3. g

    Indicator 1.1.1: Proportion of population below international poverty line...

    • globalfistulahub.org
    • sdgs.amerigeoss.org
    • +5more
    Updated Feb 3, 2021
    + more versions
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    Direct Relief (2021). Indicator 1.1.1: Proportion of population below international poverty line (percent) [Dataset]. https://www.globalfistulahub.org/datasets/indicator-1-1-1-proportion-of-population-below-international-poverty-line-percent-2/geoservice
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    Dataset updated
    Feb 3, 2021
    Dataset authored and provided by
    Direct Relief
    Area covered
    Description

    Series Name: Proportion of population below international poverty line (percent)Series Code: SI_POV_DAY1Release Version: 2020.Q2.G.03This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.1.1: Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural)Target 1.1: By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a dayGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  4. Indicator 1.1.1: Employed population below international poverty line by sex...

    • sdgs.amerigeoss.org
    • sdg.org
    • +1more
    Updated Sep 23, 2021
    + more versions
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    UN DESA Statistics Division (2021). Indicator 1.1.1: Employed population below international poverty line by sex and age (percent) [Dataset]. https://sdgs.amerigeoss.org/items/e03c84e43f2d461fb6b097132eb31a67
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    Dataset updated
    Sep 23, 2021
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Employed population below international poverty line by sex and age (percent)Series Code: SI_POV_EMP1Release Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.1.1: Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural)Target 1.1: By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a dayGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  5. P

    Portugal PT: Proportion of People Living Below 50 Percent Of Median Income:...

    • ceicdata.com
    Updated Dec 15, 2024
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    CEICdata.com (2024). Portugal PT: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/portugal/social-poverty-and-inequality/pt-proportion-of-people-living-below-50-percent-of-median-income-
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    Dataset updated
    Dec 15, 2024
    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
    Portugal
    Description

    Portugal PT: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 10.500 % in 2021. This records a decrease from the previous number of 12.300 % for 2020. Portugal PT: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 12.200 % from Dec 2003 (Median) to 2021, with 19 observations. The data reached an all-time high of 14.400 % in 2013 and a record low of 10.500 % in 2021. Portugal PT: 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 Portugal – Table PT.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).

  6. V

    Vietnam VN: Proportion of People Living Below 50 Percent Of Median Income: %...

    • ceicdata.com
    Updated Sep 15, 2022
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    CEICdata.com (2022). Vietnam VN: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/vietnam/social-poverty-and-inequality/vn-proportion-of-people-living-below-50-percent-of-median-income-
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    Dataset updated
    Sep 15, 2022
    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, 1997 - Dec 1, 2022
    Area covered
    Vietnam
    Description

    Vietnam VN: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 13.400 % in 2022. This records a decrease from the previous number of 13.900 % for 2020. Vietnam VN: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 12.800 % from Dec 1992 (Median) to 2022, with 13 observations. The data reached an all-time high of 14.000 % in 2018 and a record low of 7.100 % in 1997. Vietnam VN: 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 Vietnam – Table VN.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).

  7. I

    Italy IT: Proportion of People Living Below 50 Percent Of Median Income: %

    • ceicdata.com
    Updated Nov 29, 2022
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    CEICdata.com (2022). Italy IT: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/italy/social-poverty-and-inequality
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    Dataset updated
    Nov 29, 2022
    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
    Italy
    Description

    IT: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 15.300 % in 2021. This records a decrease from the previous number of 15.600 % for 2020. IT: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 14.050 % from Dec 1977 (Median) to 2021, with 36 observations. The data reached an all-time high of 16.200 % in 1993 and a record low of 9.700 % in 1982. IT: 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 Italy – Table IT.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).

  8. Extreme poverty

    • kaggle.com
    Updated Dec 3, 2021
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    Mathurin Aché (2021). Extreme poverty [Dataset]. https://www.kaggle.com/datasets/mathurinache/extreme-poverty/versions/1
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 3, 2021
    Dataset provided by
    Kaggle
    Authors
    Mathurin Aché
    License

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

    Description

    Context

    Two centuries ago the majority of the world population was extremely poor. Back then it was widely believed that widespread poverty was inevitable. But this turned out to be wrong. Economic growth is possible and poverty can decline. The world has made immense progress against extreme poverty.

    But even after two centuries of progress, extreme poverty is still the reality for every tenth person in the world. This is what the ‘international poverty line’ highlights – this metric plays an important (and successful) role in focusing the world’s attention on these very poorest people in the world.

    The poorest people today live in countries which have achieved no growth. This stagnation of the world’s poorest economies is one of the largest problems of our time. Unless this changes millions of people will continue to live in extreme poverty.

    Content

    Data comes from https://ourworldindata.org/extreme-poverty-in-brief Thanks to them to aggregate this kind of informations!

    Acknowledgements

    https://media.globalcitizen.org/thumbnails/90/19/90190c20-1182-47d6-a86e-3a2dcc912e73/extreme-poverty-un-explainer-social-share.jpg_1500x670_q85_ALIAS-hero_image_crop_subsampling-2.jpg" alt="Extreme Poverty">

    Inspiration

    Compare country, by year the % of persons in extreme poverty

  9. A

    Indicator 1.1.1: Employed population below international poverty line, by...

    • data.amerigeoss.org
    • hub.arcgis.com
    csv, esri rest +4
    Updated Jun 13, 2019
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    AmeriGEO ArcGIS (2019). Indicator 1.1.1: Employed population below international poverty line, by sex and age (percent) [Dataset]. https://data.amerigeoss.org/bg/dataset/indicator-1-1-1-employed-population-below-international-poverty-line-by-sex-and-age-percent1
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    html, zip, geojson, csv, esri rest, kmlAvailable download formats
    Dataset updated
    Jun 13, 2019
    Dataset provided by
    AmeriGEO ArcGIS
    Description

    Series SI_POV_EMP1: Employed population below international poverty line, by sex and age (%)

    Indicator 1.1.1: Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)

    Target 1.1: By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day

    Goal 1: End poverty in all its forms everywhere

    Release Version: 2018.Q2.G.01

  10. Lebanon LB: Proportion of People Living Below 50 Percent Of Median Income: %...

    • ceicdata.com
    Updated Dec 15, 2022
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    CEICdata.com (2022). Lebanon LB: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/lebanon/poverty/lb-proportion-of-people-living-below-50-percent-of-median-income-
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    Dataset updated
    Dec 15, 2022
    Dataset provided by
    CEIC Data
    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, 2011
    Area covered
    Lebanon
    Description

    Lebanon LB: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 10.700 % in 2011. Lebanon LB: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 10.700 % from Dec 2011 (Median) to 2011, with 1 observations. The data reached an all-time high of 10.700 % in 2011 and a record low of 10.700 % in 2011. Lebanon LB: 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 Lebanon – Table LB.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).

  11. d

    Proportion of population living below national poverty line, by sex and age

    • data.gov.au
    • cloud.csiss.gmu.edu
    • +1more
    csv
    Updated Jun 26, 2019
    + more versions
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    Sustainable Development Goals (2019). Proportion of population living below national poverty line, by sex and age [Dataset]. https://data.gov.au/data/dataset/proportion-of-population-living-below-national-poverty-line-by-sex-and-age
    Explore at:
    csv(130)Available download formats
    Dataset updated
    Jun 26, 2019
    Dataset authored and provided by
    Sustainable Development Goals
    License

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

    Description

    The most common poverty measures, including that used by the OECD, focus on income based approaches. One of the most common measures of income poverty is the proportion of households with income less than half median equivalised disposable household income (which is set as the poverty line); this is a relative income poverty measure as poverty is measured by reference to the income of others rather than in some absolute sense. Australia has one of the highest household disposable incomes in the world, which means that an Australian relative income poverty line is set at a high level of income compared to most other countries.

    OECD statistics on Australian poverty 2015-16 (based on ABS Survey of Income and Housing data and applying a poverty line of 50% of median income) determined the Australian poverty rate was over 25% before taxes and transfers, but falls around 12% after taxes and transfers. Though measuring poverty through application of solely an income measure is not considered comprehensive for an Australian context, however, it does demonstrate that the Australian welfare system more than halves the number of Australians that would otherwise be considered as at risk of living in poverty under that measure.
    It is important to consider a range of indicators of persistent disadvantage to understand poverty and hardship and its multidimensional nature. Different indicators point to different dimensions of poverty. While transient poverty is a problem, the experience of persistent poverty is of deeper concern, particularly where families experience intergenerational disadvantage and long-term welfare reliance. HILDA data from the Melbourne Institute of Applied Economic and Social Research shows the Distribution of number of years in poverty 2001–2015. The figure focuses on the longer term experience of working age adults and shows that while people do fall into poverty, only a small proportion of people are persistently poor.

  12. e

    Young Lives: an International Study of Childhood Poverty: Round 3, 2009 -...

    • b2find.eudat.eu
    Updated Oct 23, 2023
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    (2023). Young Lives: an International Study of Childhood Poverty: Round 3, 2009 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/a09c4f55-aa3c-5d02-b80c-897bc0908a79
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    Dataset updated
    Oct 23, 2023
    Description

    Abstract copyright UK Data Service and data collection copyright owner.The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The study is being conducted in Ethiopia, India, Peru and Vietnam and has tracked the lives of 12,000 children over a 20-year period, through 5 (in-person) survey rounds (Round 1-5) and, with the latest survey round (Round 6) conducted over the phone in 2020 and 2021 as part of the Listening to Young Lives at Work: COVID-19 Phone Survey.Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, Round 4 surveyed them at 12 and 19 years old, and Round 5 surveyed them at 15 and 22 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves.The 2020 phone survey consists of three phone calls (Call 1 administered in June-July 2020; Call 2 in August-October 2020 and Call 3 in November-December 2020) and the 2021 phone survey consists of two additional phone calls (Call 4 in August 2021 and Call 5 in October-December 2021) The calls took place with each Young Lives respondent, across both the younger and older cohort, and in all four study countries (reaching an estimated total of around 11,000 young people).The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country.Further information about the survey, including publications, can be downloaded from the Young Lives website. This study includes data and documentation for Round 3 only. Round 1 is available under SN 5307, Round 2 under SN 6852, Round 4 under SN 7931 and Round 5 under SN 8357.Latest edition:For the fourth edition (August 2022), the Peruvian household level data files (pe_oc_householdlevel and pe_yc_householdlevel) have been updated to include the mother's health variables. Main Topics: This dataset comprises the data from the 8-year-olds' and 15-year-olds' household surveys and child questionnaires carried out in 2009. For each of the four countries the dataset contains files at the community, household and child level for both ages. In addition there are several files at lower levels (i.e. where there are several records per household). These include the household roster and activity schedules for livelihoods, etc. The Peru community level data includes an additional file with community data covering new communities for children who have migrated. Topics covered in the dataset include: community characteristics (environmental, social and economic); parental background; household and child education; livelihoods and asset framework; household food and non-food consumption and expenditure; social capital, economic changes and recent life history; socio-economic status; child care, education and activities; child health; anthropometry; caregivers perceptions and attitudes; school and activities, child time use; social networks, social skills and social support; feelings and attitudes; parents and household issues; child development; perception of the future, environment and household wealth. Also included are calculated indices such as a wealth index, various social capital scores, and mental health scores, which are all detailed in the documentation. The SPSS syntax code and/or Stata 'do' files that show methods of calculation for the composite indices are also included in the dataset. Purposive selection/case studies

  13. C

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

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/china/social-poverty-and-inequality/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
    China
    Description

    China Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.600 % in 2021. This records a decrease from the previous number of 11.900 % for 2020. China Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 15.100 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 19.500 % in 2010 and a record low of 8.900 % in 1990. China 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 China – Table CN.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).

  14. H

    Data from: We Just Ran Twenty-Three Million Queries of the World Bank's Web...

    • dataverse.harvard.edu
    Updated Apr 27, 2014
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    Sarah Dykstra; Benjamin Dykstra; Justin Sandefur (2014). We Just Ran Twenty-Three Million Queries of the World Bank's Web Site [Dataset]. http://doi.org/10.7910/DVN/25492
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 27, 2014
    Dataset provided by
    Harvard Dataverse
    Authors
    Sarah Dykstra; Benjamin Dykstra; Justin Sandefur
    License

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

    Time period covered
    1977 - 2012
    Area covered
    World
    Description

    This study provides data from the World Bank's PovcalNet on the distribution of household income and consumption across populations for 942 country-years, organized in dta and csv files by region. Each distribution contains 10,000 data points, one for each 0.01 incremental increase in percent of people living in households at or below a given income or consumption level. In addition, a data set containing the estimated parameters of the Beta and General Quadratic Lorenz curves is provided. For reference, we also provide the Python scripts used to query the PovcalNet online tool and export data from the Mongo database used to store results of these queries, along with all do files used to clean and construct the final data sets and summary statistics.

  15. Forest proximate people – 1km cutoff distance (Global - 100m)

    • data.amerigeoss.org
    http, wmts
    Updated Oct 24, 2022
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    Food and Agriculture Organization (2022). Forest proximate people – 1km cutoff distance (Global - 100m) [Dataset]. https://data.amerigeoss.org/dataset/8ed893bd-842a-4866-a655-a0a0c02b79b4
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    http, wmtsAvailable download formats
    Dataset updated
    Oct 24, 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

    The "Forest Proximate People" (FPP) dataset is one of the data layers contributing to the development of indicator #13, “number of forest-dependent people in extreme poverty,” of the Collaborative Partnership on Forests (CPF) Global Core Set of forest-related indicators (GCS). The FPP dataset provides an estimate of the number of people living in or within 1 kilometer of forests (forest-proximate people) for the year 2019 with a spatial resolution of 100 meters at a global level.

    For more detail, such as the theory behind this indicator and the definition of parameters, and to cite this data, see: Newton, P., Castle, S.E., Kinzer, A.T., Miller, D.C., Oldekop, J.A., Linhares-Juvenal, T., Pina, L., Madrid, M., & de Lamo, J. 2022. The number of forest- and tree-proximate people: a new methodology and global estimates. Background Paper to The State of the World’s Forests 2022 report. Rome, FAO.

    Contact points:

    Maintainer: Leticia Pina

    Distributor: Sarah E., Castle

    Data lineage:

    The FPP data are generated using Google Earth Engine. Forests are defined by the Copernicus Global Land Cover (CGLC) (Buchhorn et al. 2020) classification system’s definition of forests: tree cover ranging from 15-100%, with or without understory of shrubs and grassland, and including both open and closed forests. Any area classified as forest sized ≥ 1 ha in 2019 was included in this definition. Population density was defined by the WorldPop global population data for 2019 (WorldPop 2018). High density urban populations were excluded from the analysis. High density urban areas were defined as any contiguous area with a total population (using 2019 WorldPop data for population) of at least 50,000 people and comprised of pixels all of which met at least one of two criteria: either the pixel a) had at least 1,500 people per square km, or b) was classified as “built-up” land use by the CGLC dataset (where “built-up” was defined as land covered by buildings and other manmade structures) (Dijkstra et al. 2020). Using these datasets, any rural people living in or within 1 kilometer of forests in 2019 were classified as forest proximate people. Euclidean distance was used as the measure to create a 1-kilometer buffer zone around each forest cover pixel. The scripts for generating the forest-proximate people and the rural-urban datasets using different parameters or for different years are published and available to users. For more detail, such as the theory behind this indicator and the definition of parameters, and to cite this data, see: Newton, P., Castle, S.E., Kinzer, A.T., Miller, D.C., Oldekop, J.A., Linhares-Juvenal, T., Pina, L., Madrid, M., & de Lamo, J. 2022. The number of forest- and tree-proximate people: a new methodology and global estimates. Background Paper to The State of the World’s Forests 2022. Rome, FAO.

    References:

    Buchhorn, M., Smets, B., Bertels, L., De Roo, B., Lesiv, M., Tsendbazar, N.E., Herold, M., Fritz, S., 2020. Copernicus Global Land Service: Land Cover 100m: collection 3 epoch 2019. Globe.

    Dijkstra, L., Florczyk, A.J., Freire, S., Kemper, T., Melchiorri, M., Pesaresi, M. and Schiavina, M., 2020. Applying the degree of urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation. Journal of Urban Economics, p.103312.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University, 2018. Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

    Online resources:

    GEE asset for "Forest proximate people – 1km cutoff distance (100-m resolution)"

  16. Djibouti DJ: Proportion of People Living Below 50 Percent Of Median Income:...

    • ceicdata.com
    Updated Dec 16, 2022
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    CEICdata.com (2022). Djibouti DJ: Proportion of People Living Below 50 Percent Of Median Income: % [Dataset]. https://www.ceicdata.com/en/djibouti/social-poverty-and-inequality/dj-proportion-of-people-living-below-50-percent-of-median-income-
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    Dataset updated
    Dec 16, 2022
    Dataset provided by
    CEIC Data
    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, 2002 - Dec 1, 2017
    Area covered
    Djibouti
    Description

    Djibouti DJ: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 17.200 % in 2017. This records a decrease from the previous number of 18.900 % for 2013. Djibouti DJ: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 18.050 % from Dec 2002 (Median) to 2017, with 4 observations. The data reached an all-time high of 18.900 % in 2013 and a record low of 15.400 % in 2002. Djibouti DJ: 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 Djibouti – Table DJ.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).

  17. o

    Land tenure security and poverty reduction

    • data.opendevelopmentmekong.net
    Updated Jun 14, 2015
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    (2015). Land tenure security and poverty reduction [Dataset]. https://data.opendevelopmentmekong.net/dataset/land-tenure-security-and-poverty-reduction
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    Dataset updated
    Jun 14, 2015
    Description

    "Land is fundamental to the lives of poor rural people. It is a source of food, shelter, income and social identity. Secure access to land reduces vulnerability to hunger and poverty. But for many of the world’s poor rural people in developing countries, access is becoming more tenuous than ever."

  18. 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).

  19. e

    Globalization and Indian Poverty - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Nov 12, 2024
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    (2024). Globalization and Indian Poverty - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/0ea3d9d6-77d2-57ed-a903-b4f48f511f5e
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    Dataset updated
    Nov 12, 2024
    Area covered
    India
    Description

    Globalization started in india in 1991 is done. Today we are in the age of globalization living. Globalization means market access, trade growth, agricultural development, job creation means the country fulfilling the objective of accelerating overall development is a new experiment made by the world. Of india from the very beginning, the experiment of globalization in context opposition, as well as support from many intellectuals, is great is done in proportion. Globalization in india today accepted for more than 25 years. Favorable for india as well as in some areas the opposite effect can be seen in globalizationdue to this industry and trade sector in the country, you see the prosperity. Here is the information the field of technology has developed a lot and at present, this sector is also ahead in terms of employing the agricultural sector in the country was ahead. She is currently considering employment in the country has been declining since 2014 and as a result, adverse effects on poverty in the country are living. Poverty is an issue related to purchasing power and the purchasing power of people in the country decreases every day. This is happening because the high level of employment in the country is declining.

  20. g

    Persons at risk of poverty or social exclusion

    • gimi9.com
    • opendata.marche.camcom.it
    • +2more
    Updated Jul 17, 2021
    + more versions
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    (2021). Persons at risk of poverty or social exclusion [Dataset]. https://gimi9.com/dataset/eu_m5wby8e91guwdym9uoa
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    Dataset updated
    Jul 17, 2021
    Description

    This indicator corresponds to the sum of persons who are: at risk of poverty after social transfers, severely materially deprived or living in households with very low work intensity. Persons are counted only once even if they are affected by more than one of these phenomena. • Persons are considered to be at risk of poverty after social transfers, if they have an equivalised disposable income below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income. • Severely materially or socially deprived persons have living conditions severely constrained by a lack of resources, they experience at least 7 out of 13 following deprivations items: cannot afford i) to pay rent or utility bills, ii) keep home adequately warm, iii) face unexpected expenses, iv) eat meat, fish or a protein equivalent every second day, v) a week holiday away from home, vi) have access to a car/van for personal use; vii) replace worn out furniture; viii) replace worn-out clothes with some new ones; ix) have two pairs of properly fitting shoes; x) spend a small amount of money each week on him/herself (“pocket money”); xi) have regular leisure activities; xii) get together with friends/family for a drink/meal at least once a month; and xiii) have an internet connection. • People living in households with very low work intensity are those aged 0-64 living in households where the adults (aged 18-64) work 20 % or less of their total work potential during the past year. In order to measure child poverty, the indicator is available for the age group 0-17.

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

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22 scholarly articles cite this dataset (View in Google Scholar)
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.

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