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 average for 2020 based on 54 countries was 19.31 percent. The highest value was in the Gambia: 53.4 percent and the lowest value was in China: 0 percent. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.

Historical dataset showing World poverty rate by year from 1981 to 2023.

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.

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

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.

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

Using a poverty metric of 2.15 U.S. dollars per day, 38.7 percent of the women in Sub-Saharan Africa were living in extreme poverty in 2023. On the other hand, less than one percent of the population in Europe and North America as well as Australia and New Zealand were living in extreme poverty. Nevertheless, there are also many people in these regions struggling to make ends meet.

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

The Multidimensional Poverty Measure (MPM) seeks to understand poverty beyond just a monetary dimension by including access to education and basic infrastructure along with the monetary headcount ratio at the $1.90 poverty line. The World Bank’s measure takes inspiration and guidance from other prominent multidimensional measures, particularly the Multidimensional Poverty Index (MPI) developed by UNDP and Oxford University but differs from them in one important aspect: it includes Monetary poverty (measured as having a daily consumption less than $1.90 in 2011 PPP) as one of the dimensions. While monetary poverty is strongly correlated with deprivations in other domains, this correlation is far from perfect. The Poverty and Shared Prosperity 2020 (World Bank, 2020) report shows that over a third of those experiencing multidimensional poverty are not captured by the monetary headcount ratio, in line with the findings of the previous edition of the report (World Bank, 2018). A country’s MPM is at least as high as or higher than the monetary poverty, reflecting the additional role of nonmonetary dimensions in increasing multidimensional poverty and their importance to general well-being.

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

In 2023, the number of people living on less than 2.15 U.S. dollars a day worldwide stood at 10.2 percent. Between 1981 and 2023, the figure dropped by 37.2 percentage points, though the decline followed an uneven course rather than a steady trajectory.

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.

Global Poverty and Inequality Data

Source: Cross-National Data Center in Luxembourg - Income Study https://www.lisdatacenter.org/

Data Dictionary:

gini - Gini Coefficient atk5 - Atkinson Coefficient (epsilon=0.5) atk1 - Atkinson Coefficient (epsilon=1) d9010 - Percentile Ratio (90/10) d9050 - Percentile Ratio (90/50) d8020 - Percentile Ratio (80/20) poorAll4 - Relative Poverty Rates - Total Population (40%) poorAll5 - Relative Poverty Rates - Total Population (50%) poorAll6 - Relative Poverty Rates - Total Population (60%) poorK4 - Relative Poverty Rates - Children (40%) poorK5 - Relative Poverty Rates - Children (50%) poorK6 - Relative Poverty Rates - Children (60%) poorE4 - Relative Poverty Rates - Elderly (40%) poorE5 - Relative Poverty Rates - Elderly (50%) poorE6 - Relative Poverty Rates - Elderly (60%) d5075 - Distribution of Children by Income Group (50-75%) d75150 - Distribution of Children by Income Group (75-150%) d150 - Distribution of Children by Income Group (above 150%) poortp - Children Poverty Rates - Two-Parent Families (50%) poorsm - Children Poverty Rates - Single-Mother Families (50%) pkidsm - % Children Living in Single-Mother Families eymed - Median Equivalized Income average - Mean Equivalized Income

• The dataset consists of 108 columns and 4878 rows.
• It has the year when the data was surveyed for different countries and its other features.
• There will be multiple rows for a same country even so preprocess it accordingly.

Latest poverty and inequality indicators compiled from officially recognized international sources. Poverty indicators include the poverty headcount ratio, poverty gap, and number of poor at both international and national poverty lines. Inequality indicators include the Gini index and income or consumption distributions. The database includes national, regional and global estimates. This database is maintained by the Global Poverty Working Group (GPWG), a team of poverty measurement experts from the Poverty Global Practice, the Development Research Group, and the Development Data Group.

The database is part of the Poverty and Inequality Platform, https://pip.worldbank.org/home

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.

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

United States Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 19.200 % in 2022. This records an increase from the previous number of 16.700 % for 2021. United States Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 19.200 % from Dec 1963 (Median) to 2022, with 60 observations. The data reached an all-time high of 20.500 % in 1993 and a record low of 16.700 % in 2021. United States 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 United States – Table US.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).

Global poverty statistics and rates by country