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.

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.

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.

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.

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

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.

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

Over the past three decades, the number of people living on less than 2.15 U.S. dollars a day in terms of 2017 Purchasing Power Parities has fallen remarkably. Whereas around two billion people lived on less than this amount a day in 1990, the number had fallen to around 711 million by 2022. Although much progress has been made and this figure is falling, this number increased slightly in light of the COVID-19 pandemic, going from around 689 million in 2019 to 762 million in 2020 and 749 million by 2021.

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).

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

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

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).

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.

Definition: The indicator “proportion of the population below the international poverty line” is defined as the percentage of the population living on less than $2.15 a day at 2017 international prices. Concepts: In assessing poverty in a given country, and how best to reduce poverty, one naturally focuses on a poverty line that is considered appropriate for that country. But how do we talk meaningfully about Last updated: 2023-03-31 “global poverty?” Poverty lines across countries vary in terms of their purchasing power, and they have a strong economic gradient, such that richer countries tend to adopt higher standards of living in defining poverty. But to consistently measure global absolute poverty in terms of consumption we need to treat two people with the same purchasing power over commodities the same way—both are either poor or not poor—even if they live in different countries. Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parity (PPP) exchange rates, was chosen for World Development Report 1990 because it was typical of the poverty lines in lowincome countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when the World Bank adopted $2.15 as the international poverty line using the 2017 PPP. Prior to that, the 2015 update set the international poverty line at $1.90 using the 2011 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries and over time. Unit of measure: Percent (%). The unit of measure is the proportion of people.Validation: The raw data are obtained by poverty economists through their contacts in the NSOs, and checked for quality before being submitted for further analysis. The raw data can be unit-record survey data, or grouped data, depending on the agreements with the country governments. In most cases, the welfare aggregate, the essential element for poverty estimation, is generated by the country governments. Sometimes, the World Bank constructs the welfare aggregate or adjusts the aggregate provided by the countryData availability: Data are available in 160+ economies, (measured in terms of number of economies that have at least 1 data point). References: For more information and methodology, please see : https://worldbank.github.io/PIP-Methodology/. Also, consult: https://openknowledge.worldbank.org/handle/10986/37061

Egypt EG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 15.300 % in 2010. This records an increase from the previous number of 11.000 % for 2008. Egypt EG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 10.550 % from Dec 2000 (Median) to 2010, with 4 observations. The data reached an all-time high of 15.300 % in 2010 and a record low of 9.300 % in 2000. Egypt EG: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Egypt – Table EG.World Bank.WDI: Poverty. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; 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.

Series Name: Proportion of population below international poverty line (percent)Series Code: SI_POV_DAY1Release Version: 2021.Q2.G.03 This 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/

VE: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 33.100 % in 2015. This records an increase from the previous number of 29.500 % for 2014. VE: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 33.100 % from Dec 1997 (Median) to 2015, with 19 observations. The data reached an all-time high of 55.600 % in 1997 and a record low of 26.400 % in 2009. VE: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Venezuela – Table VE.World Bank.WDI: Poverty. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.; ; 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.

The eradication of poverty and the provision of equitable and inclusive quality education for all are two intricately linked Sustainable Development Goals (SDGs). As this year’s High Level Political Forum focuses on prosperity and poverty reduction, this paper, jointly released by the UNESCO Institute for Statistics (UIS) and the Global Education Monitoring (GEM) Report, shows why education is so central to the achievement of the SDGs and presents the latest estimates on out-of school children, adolescents and youth to demonstrate how much is at stake. The out-of school rate has not budged since 2008 at the primary level, since 2012 at the lower secondary level and since 2013 at the upper secondary level. The consequences are grave: if all adults completed secondary school, the global poverty rate would be more than halved.

Series Name: Employed population below international poverty line by sex and age (percent)Series Code: SI_POV_EMP1Release Version: 2020.Q2.G.03 This 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/

The Global Gridded Relative Deprivation Index (GRDI), Version 1 (GRDIv1) data set characterizes the relative levels of multidimensional deprivation and poverty in each 30 arc-second (~1 km) pixel, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDIv1 is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final index raster. Inputs were selected from the best-available data that either continuously vary across space or have at least administrative level 1 (provincial/state) resolution, and which have global spatial coverage.