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.

Graph and download economic data for Estimated Percent of People of All Ages in Poverty for United States (PPAAUS00000A156NCEN) from 1989 to 2023 about percent, child, poverty, and USA.

In February 2025, the average hourly earnings of all employees in the United States was at 11.24 U.S. dollars. The data have been seasonally adjusted. The deflators used for constant-dollar earnings shown here come from the Consumer Price Indexes Programs. The Consumer Price Index for All Urban Employees (CPI-U) is used to deflate the data for all employees. A comparison of the rate of wage growth versus the monthly inflation since 2020 rate can be accessed here. Real wages are wages that have been adjusted for inflation.

In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

In 2023, 12 percent of Missouri's population lived below the poverty line. This was a decrease from the previous year, when 13.2 percent of people in Missouri lived below the poverty line. The poverty rate for the United States can be accessed here.

This layer shows poverty status by age group. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2018-2022ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community SurveyData Preparation: Data curated from Esri Living Atlas clipped to Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 15, 2023National Figures: data.census.gov

This layer shows poverty status by age group. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2017-2021ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data curated from Esri Living Atlas clipped to Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 8, 2022National Figures: data.census.govAdditional Census data notes and data processing notes are available at the Esri Living Atlas Layer:https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

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.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.

Graph and download economic data for Estimated Percent of People Age 0-17 in Poverty for Howard County, MD (PPU18MD24027A156NCEN) from 1989 to 2023 about Howard County, MD; Baltimore; MD; under 18 years; percent; child; poverty; and USA.

Table from the American Community Survey (ACS) 5-year series on poverty and employment status related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B23025 Employment Status for the Population 16 years and over, B23024 Poverty Status by Disability Status by Employment Status for the Population 20 to 64 years, B17010 Poverty Status of Families by Family Type by Presence of Related Children under 18 years, C17002 Ratio of Income to Poverty Level in the Past 12 Months. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B23025, B23024, B17010, C17002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.<d

Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter. -----------------------------------------This layer shows poverty status by age group. This layer is Census data from Esri's Living Atlas and is clipped to only show Tempe census tracts. This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).Data is from US Census American Community Survey (ACS) 5-year estimates.

Vintage: 2015-2019

ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)

Data downloaded from: Census Bureau's API for American Community Survey

Date of Census update: December 10, 2020

National Figures: data.census.gov

Additional Census data notes and data processing notes are available at the Esri Living Atlas Layer:

https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

The population of Latin America and the Caribbean increased from 175 million in 1950 to 515 million in 2000. Where did this growth occur? What is the magnitude of change in different places? How can we visualize the geographic dimensions of population change in Latin America and the Caribbean? We compiled census and other public domain information to analyze both temporal and geographic changes in population in the region. Our database includes population totals for over 18,300 administrative districts within Latin America and the Caribbean. Tabular census data was linked to an administrative division map of the region and handled in a geographic information system. We transformed vector population maps to raster surfaces to make the digital maps comparable with other commonly available geographic information. Validation and error-checking analyses were carried out to compare the database with other sources of population information. The digital population maps created in this project have been put in the public domain and can be downloaded from our website. The Latin America and Caribbean map is part of a larger multi-institutional effort to map population in developing countries. This is the third version of the Latin American and Caribbean population database and it contains new data from the 2000 round of censuses and new and improved accessibility surfaces for creating the raster maps.

In 2023, about 15.3 percent of children under 18-years-old were living below the poverty line in the United States, significantly lower than 1990. While still high, the rate has seen a general decline throughout the last decade. Historic lows were recorded in 2019 when the child poverty rate was 14.4 percent.

A Computable General Equilibrium (CGE) model in a bottom-up approach - based on microfoundations - and a Social Accounting Matrix (SAM) for the regional economy of Chiapas are built. Methodology: This research applies a Computable General Equilibrium (CGE) model. It is a system of equations that describes an entire economy and all the interactions between productive sectors, commodity and factor markets, and institutions. All of the equations are solved simultaneously to find an economy-wide equilibrium in which demand and supply quantities are equal in every market at a certain level of prices (Burfisher, 2011). Two of the features of this model are that, on one hand, it implements a “bottom-up” approach, that is, it is focused on individual markets and economic agents. On the other hand, it is partially synthetic. In other words, most parameters can be calibrated with data from the SAM. Data framework: A Social Accounting Matrix (SAM) is a balanced square matrix that represents all income and expenditure flows between productive sectors, markets, and economic agents of an economy at a given period of time (Müller, Perez & Hubertus, 2009). It is based on the double entry bookkeeping in accounting, which requires that total revenue equals total expenditure in each single account included in the SAM (Breisinger, Thomas & Thurlow, 2010). The main features of the Chiapas SAM are that production activities are broken down in 10 sectors, according to the North American Industry Classification System (NAICS). There is one commodity per economic activity. Factors of production are disaggregated into formal and informal labor, and capital. Direct taxes are broken up into activity tax, social security contributions, household and corporate income taxes, ‘tenencia’ tax (ownership tax, i.e. a tax associated with the possession or use of vehicles), and regional payroll tax (‘nomina’). Indirect taxes, in turn, are value-added, sales and export taxes, and import tariffs. Subsidies on production by economic activity are also included. Households are disaggregated by income quintiles. Social transfers are split in non-conditional (Procampo, universal pension, PAL-Sin Hambre , temporary employment program, and the regional program Amanecer ) and Oportunidades. The latter is also broken down into its five components: food, elderly, education, child, and energy. The introduction of conditional cash transfers in the SAM is particularly relevant because it allows assessing the impact of changes in their amount and distribution on household income, poverty reduction, income inequality, and economic growth at the regional level. Data sources: - National Institute of Statistics and Geography (INEGI): 2012 National Employment and Occupation Survey 2013 Chiapas Statistical Yearbook 2012 National Household Income-Expenditure Survey 2012 Chiapas Statistical Perspective 2003-2012 Goods and Services Accounts (SCNM) 2003-2012 Institutional Sector Accounts (SCNM) 2008 Input-Output Table 2008 Supply and Use Tables - Chiapas State Committee of Statistical and Geographical Information (CEIEG): 2012 Chiapas Employment and Occupation Survey 2012 Chiapas Monthly Statistical Reports of IMSS-insured Workers - Federal Ministry of Labor and Social Welfare (STYPS): 2012 IMSS-registered Daily Salary by Economic Activity 2012 IMSS-insured Workers Quality/Lineage: With the raw data a Social Accounting Matrix for the regional economy of Chiapas was built Features: - Oportunidades broken down by component - Other non-conditional social transfers such as Procampo, PAL-Sin Hambre, Employment program, Universal pension, and the regional program 'Amanecer' - Informal wages - Satellites tables of formal and informal employment - Productive activities according to the North American Industry Classification System (NAICS) used in Mexico, Canada, and the United States of America - 10 economic activities - 10 Commodities (one per economic activity) - Factors of production: formal and informal labor and capital Purpose: 1. To assess the opportunity cost of financing "Oportunidades", Mexico's conditional cash transfers program, and its implications for rural development and rural economic growth in the regional setting of Chiapas. Moreover, 2. Pro-growth and pro-poor tax structures are also evaluated by applying standard economic analysis tools and modeling to substantially raise the federal non-oil tax revenue to finance social policy for poverty and inequality reduction. Dissertation: Viveros Añorve, J. L. (2015): The opportunity cost of financing "Oportunidades": a general equilibrium assessment for poverty reduction in Mexico. Ph.D. dissertation. Center for Development Research, Faculty of Agriculture, University of Bonn

United States US: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data was reported at 0.000 USD mn in 2017. This stayed constant from the previous number of 0.000 USD mn for 2016. United States US: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data is updated yearly, averaging 0.000 USD mn from Dec 1945 (Median) to 2017, with 73 observations. United States US: IMF Account: Fund Position: USD: UFC: Outstanding Loans: Structural Adj. Facility, Poverty Reduction and Growth Facility & Trust Fund data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s USA – Table US.IMF.IFS: IMF Account: Fund Position: Annual.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Population over 65 years in poverty of Nevada grew by 2.97% from 10 number in 2022 to 10 number in 2024.

Graph and download economic data for Estimate of Median Household Income for Sonoma County, CA (MHICA06097A052NCEN) from 1989 to 2023 about Sonoma County, CA; Santa Rosa; CA; households; median; income; and USA.

A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150