In 2023, about four percent of the people with a Bachelor's degree or higher were living below the poverty line in the United States. This is far below the poverty rate of those without a high school diploma, which was 25.1 percent in 2023.

In 2023, about 36.79 million Americans were living below the national poverty line in the United States. Of those Americans, around 4.04 million had a four-year degree or higher. This means they have an income below 100 percent of the national poverty level as defined by the U.S. Census Bureau.

The 2020-2021 School Neighborhood Poverty Estimates are based on school locations from the 2020-2021 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2017-2021 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The 2018-2019 School Neighborhood Poverty Estimates are based on school locations from the 2018-2019 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2015-2019 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

This statistic shows the percentage of the population aged 25 and over that live in households in poverty, as distinguished by their education level and household type. 47 percent of female householders with related children under the age of 18 who had never graduated from high school were living in poverty as of 2018.

This data collection contains information gathered in the Survey of Income and Education (SIE) conducted in April-July 1976 by the Census Bureau for the United States Department of Health, Education, and Welfare (HEW). Although national estimates of the number of children in poverty were available each year from the Census Bureau's Current Population Survey (CPS), those estimates were not statistically reliable on a state-by-state basis. In enacting the Educational Amendments of 1974, Congress mandated that HEW conduct a survey to obtain reliable state-by-state data on the numbers of school-age children in local areas with family incomes below the federal poverty level. This was the statistic that determined the amount of grant a local educational agency was entitled to under Title 1, Elementary and Secondary Education Act of 1965. (Such funds were distributed by HEW's Office of Education.) The SIE was the survey created to fulfill that mandate. Its questions include those used in the Current Population Survey regarding current employment, past work experience, and income. Additional questions covering school enrollment, disability, health insurance, bilingualism, food stamp recipiency, assets, and housing costs enabled the study of the poverty concept and of program effectiveness in reaching target groups. Basic household information also was recorded, including tenure of unit (a determination of whether the occupants of the living quarters owned, rented, or occupied the unit without rent), type of unit, household language, and for each member of the household: age, sex, race, ethnicity, marital history, and education.

This layer highlights the education status of women 25 or older, living below the poverty line. Compare this map to the Education Level of Men in Poverty for additional perspective, or use the Education Level of Women and Men in Poverty in the United States app to do a side by side comparison. The poverty line varies due to family size, state of residence, and other factors. The US Census normalizes the data by placing each respondent into an income category related to the poverty line. The Census then reports education levels for men and women above and below the poverty line. The US Census American Community Survey is an ongoing survey. These estimates were created from data collected from 2010 to 2014 and shown at the tract level. The tract borders are not shown to emphasize patterns.

This dataset contains poverty estimates at school district level for population of 5 to 17 years old based on US Census Bureau program, Small Area Income and Poverty Estimates (SAIPE). The information regarding counties and states where these schools are located is also available in the dataset.

As of February 2024, 41 percent of all surveyed public school leaders were either extremely or moderately concerned about students meeting academic standards in the United States. In comparison, 54 percent of public school leaders located in high poverty neighborhoods and 57 percent of leaders from public schools where students of color made up 75 percent or more of the student population also shared this concern.

The predecessor data, CHILDREN_POVERTY_2011_USCB_IN.SHP is a polygon shapefile of 2011 unified school districts in Indiana. It also contains 2011 census data showing percentages of children in poverty for each school district for the state of Indiana. Poverty data were provided by personnel of the Indiana Business Research Center (Rachel Strange, Geodemographic Analyst, Managing Editor, IBRC), which were obtained from the Web page of the U. S. Department of Commerce, U. S. Census Bureau, titled "Small Area Income and Poverty Estimates," http://www.census.gov/did/www/saipe/data/interactive/#. Discussion of these data, which are estimates produced under the Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program, are provided at http://www.census.gov/did/www/saipe/about/index.html.The following is excerpted from an Adobe Acrobat PDF document named "TGRSHP2011_TECHDOC.PDF (U.S. Census Bureau) and also from the Web page of the SAIPE program:"School Districts are single-purpose administrative units within which local officials provide public educational services for the area's residents. The Census Bureau obtains school district boundaries, names, local education agency codes, grade ranges, and school district levels biennially from state school officials. The Census Bureau collects this information for the primary purpose of providing the U.S. Department of Education with annual estimates of the number of children in poverty within each school district, county, and state. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts."The 2011 TIGER/Line Shapefiles include separate shapefiles for elementary, secondary, and unified school districts. The 2011 shapefiles contain information from the 2009-2010 school year. The 2009-2010 school districts represent districts in operation as of January 1, 2010."The elementary school districts provide education to the lower grade/age levels and the secondary school districts provide education to the upper grade/age levels. The unified school districts are districts that provide education to children of all school ages. In general, where there is a unified school district, no elementary or secondary school district exists (see exceptions described below), and where there is an elementary school district the secondary school district may or may not exist (see explanation below)."The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program provides annual estimates of income and poverty statistics for all school districts, counties, and states. The main objective of this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs."The SAIPE program produces the following county and state estimates: Total number of people in poverty. Number of children under age 5 in poverty (for states only). Number of related children ages 5 to 17 in families in poverty. Number of children under age 18 in poverty. Median household income."

In 2024, Saxony achieved the best result in comparison with other German federal states, with a score of 76.6 points on the educational monitor scale. In contrast, Bremen scored -10.9 points, indicating that it had the highest level of educational poverty out of all the German states. The average for the whole of Germany was 35.2 points. Educational poverty is measured by the share of successful graduates from the vocational preparation year (Berufsvorbereitungsjahres - BVJ) and the size of risk groups in different subject areas. The educational monitor has the aim, according to the source, to work out the strengths and weaknesses of the education systems in individual federal states and document the changes over time. The study included several indicators that are assigned to 12 action areas and measure the quality, efficiency, and effectiveness of education systems.

CHILDREN_POVERTY_2013_USCB_IN.SHP is a polygon shapefile showing 2013 census data showing percentages of children in poverty for each 2013-2014 school district within Indiana. Poverty data were provided by personnel of the Indiana Business Research Center (Rachel Strange, Geodemographic Analyst, Managing Editor, IBRC), which were obtained from the Web page of the U. S. Department of Commerce, U. S. Census Bureau, titled "Small Area Income and Poverty Estimates," http://www.census.gov/did/www/saipe/data/interactive/#. Discussion of these data, which are estimates produced under the Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program, are provided at http://www.census.gov/did/www/saipe/about/index.html.The following is excerpted from metadata of the U.S. Census Bureau (2013-2014 School Districts) and also from the Web page of the SAIPE program ( http://www.census.gov/did/www/saipe/downloads/sd13/README.txt ) :"School Districts are single-purpose administrative units within which local officials provide public educational services for the area's residents. The Census Bureau obtains school district boundaries, names, local education agency codes, grade ranges, and school district levels biennially from state school officials. The Census Bureau collects this information for the primary purpose of providing the U.S. Department of Education with annual estimates of the number of children in poverty within each school district, county, and state. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts."The 2014 TIGER/Line Shapefiles include separate shapefiles for elementary, secondary, and unified school districts. The 2014 shapefiles contain information from the 2013-2014 school year. The 2013-2014 school districts represent districts in operation as of January 1, 2014."The elementary school districts provide education to the lower grade/age levels and the secondary school districts provide education to the upper grade/age levels. The unified school districts are districts that provide education to children of all school ages. In general, where there is a unified school district, no elementary or secondary school district exists (see exceptions described below), and where there is an elementary school district the secondary school district may or may not exist (see explanation below)."The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program provides annual estimates of income and poverty statistics for all school districts, counties, and states. The main objective of this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs."The SAIPE program produces the following county and state estimates: Total number of people in poverty. Number of children under age 5 in poverty (for states only). Number of related children ages 5 to 17 in families in poverty. Number of children under age 18 in poverty. Median household income."

The 2017-2018 School Neighborhood Poverty Estimates are based on school locations from the 2017-2018 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2014-2018 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The 2016-2017 School Neighborhood Poverty Estimates are based on school locations from the 2016-2017 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2013-2017 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Between 2023 and 2024, the share of school districts that reported providing or having plans to provide AI training for teachers increased for all districts in the United States, regardless of their poverty status. By 2025, ** percent of low-poverty districts were projected to provide AI training for teachers, compared to ** percent of middle-poverty districts and ** percent of high-poverty districts.

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

The 2015-2016 School Neighborhood Poverty Estimates are based on school locations from the 2015-2016 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2012-2016 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools. All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program provides annual estimates of income and poverty statistics for all school districts, counties, and states. The main objective of this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. In order to implement provisions under Title I of the Elementary and Secondary Education Act as amended, we produce total population, number of children ages 5 to 17, and number of related children ages 5 to 17 in families in poverty estimates for school districts.

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.