Overall, both the number of people living in poverty and the number of people living in extreme poverty in Latin America increased between 2015 and 2022, reaching 202 million and 81 million people, respectively. Since then, the number of people living in poverty has declined. In 2024, an estimated 170 million people were projected to be living in poverty in the region. . Moreover, indigenous peoples in Latin America continue to experience extremely high poverty rates.
In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.
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.
{"definition": "Percent of county population living in families with income below half of one poverty threshold", "availableYears": "2008-2012", "name": "Deep poverty, 2010-14", "units": "Percent", "shortName": "Deep_Pov_All", "geographicLevel": "County", "dataSources": "U.S. Census Bureau, American Community Survey"}
© Deep_Pov_All This layer is sourced from gis.ers.usda.gov.
Data for Indicator 1.1.1 comes from the Census Bureau's American Community Survey (ACS) poverty estimates. The U.S. poverty threshold varies based on year and family size. For example, in 2020, a household with two adults and two children would be considered under the poverty line if the household had an annual income less than $26,246. We define people living in extreme poverty line as people from households which earn less than 50% of the U.S. national poverty level for the specific year.
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Extreme poverty and poverty rate according to national measurements and definitions.
Calculation Methodology
Each country reports the rate of extreme poverty and official national poverty. For detail of methodologies and definitions, see the source used for each country.
Poverty Area MeasuresThis data product provides poverty area measures for counties across 50 States and Washington DC. The measures include indicators of high poverty areas, extreme poverty areas, persistent poverty areas, and enduring poverty areas for Decennial Census years 1960–2000 and for American Community Survey (ACS) 5-year periods spanning both 2007–11 and 2015–19.HighlightsThis data product uniquely provides poverty area measures at the census-tract level for decennial years 1970 through 2000 and 5-year periods spanning 2007–11 and 2015–19.The poverty area measure—enduring poverty—is introduced, which captures the entrenchment of high poverty in counties for Decennial Census years 1960–2000 and for ACS 5-year periods spanning 2007–11 and 2015–19. The same is available for census tracts beginning in 1970.High and extreme poverty area measures are provided for various data years, offering end-users the flexibility to adjust persistent poverty area measures to meet their unique needs.All measures are geographically standardized to allow for direct comparison over time and for census tracts within county analysis.Diverse geocoding is provided, which can be used for mapping/GIS applications, to link to supplemental data (e.g., USDA, Economic Research Service’s Atlas of Rural and Small-Town America), and to explore various spatial categories (e.g., regions and metro/nonmetro status). DefinitionsHigh poverty: areas with a poverty rate of 20.0 percent or more in a single time period.Extreme poverty: areas with a poverty rate of 40.0 percent or more in a single time period.Persistent poverty: areas with a poverty rate of 20.0 percent or more for 4 consecutive time periods, about 10 years apart, spanning approximately 30 years (baseline time period plus 3 evaluation time periods).Enduring poverty: areas with a poverty rate of 20.0 percent or more for at least 5 consecutive time periods, about 10 years apart, spanning approximately 40 years or more (baseline time period plus four or more evaluation time periods).Additional information about the measures can be found in the downloadable Excel file, which includes the documentation, data, and codebook for the poverty area measures (county and tract).The next update to this data product—planned for early 2023—is expected to include the addition of poverty area measures for the 5-year period 2017–21.Data SetLast UpdatedNext UpdatePoverty area measures (in CSV format)11/10/2022Poverty area measures11/10/2022Poverty Area MeasuresOverviewBackground and UsesERS's Legacy of Poverty Area MeasurementDocumentationDescriptions and MapsLast updated: Thursday, November 10, 2022For more information, contact: Tracey Farrigan and Austin SandersRecommended CitationU.S. Department of Agriculture, Economic Research Service. Poverty Area Measures, November 2022.
Since 2005, the share of indigenous population with an average per capita income below the extreme poverty has remained above the minimum of 16 percent in Latin America. In 2022, the percentage reached its lowest score of 16.6, a considerable decrease in comparison to the previous year. Furthermore, that year Colombia had the highest share of indigenous population living in extreme poverty.
{"definition": "Percent of county population under age 18 living in families with cash income below half of one poverty threshold", "availableYears": "2008-2012", "name": "Deep poverty for children, 2010-14", "units": "Percent", "shortName": "Deep_Pov_Children", "geographicLevel": "County", "dataSources": "U.S. Census Bureau, American Community Survey"}
© Deep_Pov_Children This layer is sourced from gis.ers.usda.gov.
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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).
In 2023, indigenous women in Latin America had a slightly higher share of people living under extreme poverty than indigenous men. Throughout the time of reference, the disparities amongst those genders haven't been extremely noticeable, with the largest difference being 1.3 percentage points. Overall, 17 percent of indigenous people in Latin America had an average per capita income below the extreme poverty line in 2023.
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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).
To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line.
Using a poverty metric of 2.15 U.S. dollars per day, 37 percent of the women in Sub-Saharan Africa were living in extreme poverty in 2023. This is expected to fall to one third by 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.
A new basis for an international poverty measurement is proposed based on linear programming for specifying the least cost diet and explicit budgeting for nonfood spending. This approach is superior to the World Bank's $1-a-day line because it is (i) clearly related to survival and well being; (ii) comparable across time and space since the same nutritional requirements are used everywhere while nonfood spending is tailored to climate; (iii) adjusts consumption patterns to local prices; (iv) presents no index number problems since solutions are always in local prices; and (v) requires only readily available information. The new approach implies much more poverty than the World Bank's, especially in Asia.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de451063https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de451063
Abstract (en): Nearly 9 million Americans live in extreme-poverty neighborhoods, places that also tend to be racially segregated and dangerous. Yet, the effects on the well-being of residents of moving out of such communities into less distressed areas remain uncertain. Moving to Opportunity (MTO) is a randomized housing experiment administered by the United States Department of Housing and Urban Development that gave low-income families living in high-poverty areas in five cities the chance to move to lower-poverty areas. Families were randomly assigned to one of three groups: (1) the low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location; (2) the traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling; (3) the control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and whatever other social programs and services to which they would otherwise be entitled. Families were tracked from baseline (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families. This data collection includes data from the 3,273 adult interviews completed as part of the MTO long-term evaluation. Using data from the long-term evaluation, the associated article reports that moving from a high-poverty to lower-poverty neighborhood was associated in the long-term (10 to 15 years) with modest, but potentially important, reductions in the prevalence of extreme obesity and diabetes. The data contain all outcomes and mediators analyzed for the associated article (with the exception of a few mediator variables from the interim MTO evaluation) as well as a variety of demographic and other baseline measures that were controlled for in the analysis. All analysis of the data should be weighted using the total survey weight. The cell-level file includes a separate weight for each outcome and mediator measure that is the sum of weights for all observations in the cell with valid data for the measure (for example, wt_f_db_hba1c_diab_final is the weight for the glycated hemoglobin measure, mn_f_db_hba1c_diab_final). In the pseudo-individual file, mn_f_wt_totsvy is the average of the total survey weight variable for all observations in the cell. In the original individual-level file, the total survey weight (f_wt_totsvy) is calculated as the product of three component weights: (1) Randomization ratio weight -- At the start of the MTO program, random assignment (RA) ratios were set to produce equal numbers of leased-up families in the low-poverty and traditional voucher groups based on expected leased-up rates. The initial ratios were "8 to 3 to 5": eight low-poverty voucher group families to three traditional voucher families to five control families. During the demonstration program, these RA ratios were adjusted to accommodate higher than anticipated leased-up rates among low-poverty voucher group families. This weight ensures that the proportion of families in a given site is the same across all three treatment groups. This component weight value ranges from 0.59 to 2.09. (2) Survey sample selection weight -- For budgetary reasons, adults from only a random two-thirds of traditional voucher group households were selected for the long-term survey interview sample (while adults from all low-poverty voucher and control group families were selected), so this component weights up the selected traditional voucher group adults so that they are representative of all traditional voucher group adults. This weight component is equal to the inverse probability of selection into the subsample (~1.52). (3) Phase 2 subsample weight -- The long-term survey data collection was completed as a two-phase process. In the first phase, we sought to interview all selected respondents. Phase 2 of fielding was triggered when the response rate reached approximately 74 percent. In the second phase, we su...
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Despite a decline in both monetary and multidimensional poverty rates since 2000, Haiti remains among the poorest and most unequal countries in Latin America. Two years after the 2010 earthquake, poverty was still high, particularly in rural areas. This report establishes that in 2012 more than one in two Haitians was poor, living on less than $ 2.41 a day, and one person in four was living below the national extreme poverty line of $1.23 a day. Extreme poverty declined from 31 to 24 percent between 2000 and 2012, and there have been some gains in access to education and sanitation, although access to basic services is generally low and is characterized by important inequalities. Urban areas have fared relatively better than rural areas, reflecting more nonagricultural employment opportunities, larger private transfers, more access to critical goods, and services and narrowing inequality compared to rural areas. Continued advances in reducing both extreme and moderate poverty will require greater, more broad-based growth, but also a concerted focus on increasing the capacity of the poor and vulnerable to accumulate assets, generate income, and better protect their livelihoods from shocks. Special attention should be given to vulnerable groups such as women and children and to rural areas, which are home to over half of the population and where extreme poverty persists, and income inequality is increasing.
Among Latin American countries in 2023, Colombia had the highest share of both Afro-descendants and indigenous people living impoverished, with 45.6 percent and 63.5 percent, respectively. Additionally, Colombia also had the highest share of indigenous people living under extreme poverty that year. Ecuador had the second-highest share of indigenous population whose average per capita income was below the poverty line, with 50.4 percent. Uruguay was the only nation where Afro-descendants were the ethnic group with the largest share of the poor population, as in the other selected countries such group was indigenous people.
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In the majority of the analyzed countries in Latin America and the Caribbean, the share of the population living in extreme poverty was expected to grow in 2022 compared to 2021. Colombia presented the most adverse situation, as extreme poverty in the country was expected to increase by 2.5 percentage points. On the flip side, it was forecasted that exreme poverty would decline in four countries: Dominican Republic, Ecuador, Panama and Bolivia.
Overall, both the number of people living in poverty and the number of people living in extreme poverty in Latin America increased between 2015 and 2022, reaching 202 million and 81 million people, respectively. Since then, the number of people living in poverty has declined. In 2024, an estimated 170 million people were projected to be living in poverty in the region. . Moreover, indigenous peoples in Latin America continue to experience extremely high poverty rates.