Whereas less than *** percent of the population in high income countries in the world lived on less than **** U.S. dollars a day in 2018 in terms of 2017 purchasing power parities, ** percent of the population in low income countries did the same. On a more positive note, the poverty rate in low income countries fell by ** percentage points from 1994 to 2018. In 2025, the share is estimated to be around *** for high income countries.

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 3.00 U.S. dollars in terms of 2021 Purchasing Power Parity (PPP) in 1990, this had fallen to **** percent in 2024. 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 2024, the richest one percent of the world owned almost ** percent of the global wealth, while the poorest 50 percent owned less than ***** percent in the same year. Within regions, the MENA region, Central Asia, and Latin America had the most unequal distribution of wealth, but this phenomenon is present in all world regions.

The Global Poverty Dataset extracted from Wikipedia provides a comprehensive overview of poverty levels across countries and regions worldwide. The dataset is primarily based on internationally recognized poverty benchmarks such as the World Bank’s international poverty lines (e.g., people living on less than $2.15 per day in purchasing power parity terms).

This dataset typically includes country-wise information on the percentage of population living below the poverty line, along with absolute counts of people in poverty, regional classifications, and reference years. The data reflects economic inequality, income distribution, and living standards across different parts of the world, making it a valuable resource for socioeconomic analysis.

The information compiled on Wikipedia is sourced from reputable institutions such as the World Bank, United Nations, IMF, and national statistical agencies, ensuring reasonable reliability and global coverage. However, the dataset may contain variations in reporting years, methodologies, and estimation techniques due to differences in national data collection practices.

Key Features of the Dataset

Country or region name

Poverty rate (percentage of population below the poverty line)

Number of people living in poverty

Poverty threshold used (e.g., $1.90 or $2.15 per day PPP)

Year of estimation

Regional or income-group classification

Use Cases

Comparative analysis of poverty across countries or regions

Studying global income inequality and development trends

Policy analysis and evaluation of poverty reduction initiatives

Data visualization and time-series analysis (where multiple years are available)

Limitations

Differences in survey years and poverty definitions across countries

Estimates may not fully capture informal economies or recent economic shocks

Wikipedia acts as a secondary source, so original datasets should be consulted for high-stakes research

Overall, this dataset offers a high-level yet insightful snapshot of global poverty patterns and serves as a strong starting point for economic research, academic projects, and data analysis exercises.

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

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.

Sub-Saharan Africa is the region with the highest prevalence of multidimensional poverty globally based on the Multidimensional Poverty Index (MPI). On a scale from zero to one, the region received a score of ****. South Asia had the second-highest prevalence of multidimensional poverty. On the other hand, Europe & Central Asia had a score of *****.

The average for 2020 based on 65 countries was 21.91 percent. The highest value was in Democratic Republic of the Congo: 56.2 percent and the lowest value was in China: 0 percent. The indicator is available from 1985 to 2024. Below is a chart for all countries where data are available.

The Poverty and Inequality Platform (PIP), developed by the World Bank, provides global, regional, and country-level estimates of poverty, inequality, and shared prosperity covering 172 countries. PIP is the primary source for the World Bank's poverty and inequality estimates, and it informs many Sustainable Development Goal (SDG) indicators on poverty and inequality. The data, governed by the Global Poverty Working Group (GPWG), are expressed in 2021 Purchasing Power Parity (PPP) prices, with global poverty lines set at $3.00, $4.20, and $8.30 per day.

Out of all OECD countries, Costa Rica had the highest poverty rate as of 2023, at over 21 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 5.5 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.

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.

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

In 2024, the number of people living on less than 2.15 U.S. dollars a day worldwide amounted to 10.3 percent. Between 1981 and 2024, the figure dropped by 36.8 percentage points, though the decline followed an uneven course rather than a steady trajectory.

United States Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 1.300 % in 2023. This records a decrease from the previous number of 1.400 % for 2022. United States Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 1.300 % from Dec 2010 (Median) to 2023, with 14 observations. The data reached an all-time high of 1.500 % in 2014 and a record low of 0.500 % in 2020. United States 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 United States – Table US.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., World Bank (WB), uri: http://pip.worldbank.org, note: 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.;Population-weighted average;

Survey years The Poverty and Inequality Platform: Percentiles database reports 100 points ranked according to the consumption or income distributions for country-year survey data available in the World Bank’s Poverty and Inequality Platform (PIP). There are, as of September 30, 2025, a total of 2,556 country-survey-year data points, which include 2,375 distributions based on microdata, binned data, or imputed/synthetic data, and 181 based on grouped data. For the grouped data, the percentiles are derived by fitting a parametric Lorenz distribution following Datt (1998). For ease of communication, all distributions are referred to as survey data henceforth, and the welfare variable is referred to as income. Details Each distribution reports 100 points per country per survey year ranked from the smallest (percentile 1) to the largest (percentile 100) income or consumption. For each income percentile, the database reports the following variables: the average daily per person income or consumption (avg_welfare); the income or consumption value for the upper threshold of the percentile (quantile); the share of the population in the percentile (which might deviate slightly from 1% due to coarseness in the raw data) (pop_share); and the share of income or consumption held by each percentile (welfare_share). In addition, the database reports the welfare measure (welfare_type) used in the survey data—income or consumption—and the region covered (reporting_level)—urban, rural, or national. The distributions are available in 2017 or 2021 PPP$. Stata code example Below is an example of how to use the database to generate an anonymous growth incidence curve for Bangladesh between 2005 and 2010 keep if country_code=="BGD" & reporting_level==1 & /// inlist(year,2005,2010) bys country_code percentile (year): /// gen growth05_10 = (avg_welfare/avg_welfare[_n-1] - 1) * 100 twoway connected growth05_10 percentile, ytitle("%") /// title("Cumulative growth in Bangladesh, 2005-2010") Metadata Some metadata of the data set, such as the version of the data, can be found by typing char dir in the Stata console. Alternatively, please refer to this portal, which contains all the information available. PIP version date: 20250930 (updated October 1, 2025) Lineup years Not currently available

This data entry includes lined-up subnational poverty estimates (based on international poverty line(s)) for more than 168 economies at administrative unit level 1 in 2010, 2019, 2021, and 2023. Administrative unit level 1 refers to the highest subnational unit level (examples include ‘state’, ‘governorate’, ‘province’) from household surveys. In 2013, the World Bank announced the goals of fighting poverty in all its forms by 2030 and promoting shared prosperity. Despite the remarkable progress in reducing poverty in recent years, reaching the targets remains challenging. The decline in poverty has been uneven. The poverty reduction in recent years was dominated by East Asia and Pacific (notably China and Indonesia) and South Asia (notably India) (World Bank, 2017). Despite progress, the number of extreme poor remains high, especially in Sub-Saharan Africa. In many countries, vast differences in poverty levels persist at the subnational level. In addition, global problems such as climate change, fragility, economic crises, and food security pose great risks for poverty reduction, and they are often trans-border issues that generate strong positive or negative externalities across neighboring countries. This version is based on the Oct. 2025 vintage of the GMD data with the latest poverty lines in 2021 PPP.

The average for 2021 based on 78 countries was 8.37 percent. The highest value was in the Central African Republic: 71.6 percent and the lowest value was in Belgium: 0 percent. The indicator is available from 1963 to 2024. Below is a chart for all countries where data are available.

Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at -4.600 % in 2020. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging -4.600 % from Dec 2020 (Median) to 2020, with 1 observations. The data reached an all-time high of -4.600 % in 2020 and a record low of -4.600 % in 2020. Colombia CO: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2021 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. 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. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered.;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., World Bank (WB), uri: http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity;NA;

NO: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 12.200 % in 2021. This records a decrease from the previous number of 12.600 % for 2020. NO: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 12.400 % from Dec 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 12.600 % in 2020 and a record low of 12.200 % in 2021. NO: 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 Norway – Table NO.World Bank.WDI: Social: Poverty and Inequality. National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.;World Bank, Poverty and Inequality Platform. 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

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.