100+ datasets found
  1. V

    Low Income Communities

    • data.virginia.gov
    • vgin.vdem.virginia.gov
    • +3more
    Updated Nov 25, 2025
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    Virginia Department of Environmental Quality (2025). Low Income Communities [Dataset]. https://data.virginia.gov/dataset/low-income-communities
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    csv, geojson, kml, zip, arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Nov 25, 2025
    Dataset provided by
    {{source}}
    Authors
    Virginia Department of Environmental Quality
    Description
  2. Low-Income or Disadvantaged Communities Designated by California

    • data.cnra.ca.gov
    • data.ca.gov
    • +5more
    Updated Jun 11, 2025
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    California Energy Commission (2025). Low-Income or Disadvantaged Communities Designated by California [Dataset]. https://data.cnra.ca.gov/dataset/low-income-or-disadvantaged-communities-designated-by-california
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    html, csv, zip, kml, arcgis geoservices rest api, geojsonAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    California
    Description

    This layer shows census tracts that meet the following definitions: Census tracts with median household incomes at or below 80 percent of the statewide median income or with median household incomes at or below the threshold designated as low income by the Department of Housing and Community Development’s list of state income limits adopted under Healthy and Safety Code section 50093 and/or Census tracts receiving the highest 25 percent of overall scores in CalEnviroScreen 4.0 or Census tracts lacking overall scores in CalEnviroScreen 4.0 due to data gaps, but receiving the highest 5 percent of CalEnviroScreen 4.0 cumulative population burden scores or Census tracts identified in the 2017 DAC designation as disadvantaged, regardless of their scores in CalEnviroScreen 4.0 or Lands under the control of federally recognized Tribes.


    Data downloaded in May 2022 from https://webmaps.arb.ca.gov/PriorityPopulations/.

  3. Low and Moderate Income Areas Map

    • data.mesaaz.gov
    • citydata.mesaaz.gov
    csv, xlsx, xml
    Updated Aug 24, 2023
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    Housing and Urban Development (HUD) (2023). Low and Moderate Income Areas Map [Dataset]. https://data.mesaaz.gov/Census/Low-and-Moderate-Income-Areas-Map/rpdt-ydtu
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    xml, xlsx, csvAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Housing and Urban Development (HUD)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    FY2024 full and partial census tracts that qualify as Low-Moderate Income Areas (LMA) where 51% or more of the population are considered as having Low-Moderate Income. The low- and moderate-income summary data (LMISD) is based on the 2016-2020 American Community Survey (ACS). As of August 1, 2024, to qualify any new low- and moderate-income area (LMA) activities, Community Development Block Grant (CDBG) grantees should use this map and data.

    For more information about LMA/LMI click the following link to open in new browser tab https://www.hudexchange.info/programs/cdbg/cdbg-low-moderate-income-data/

  4. Low to Moderate Income Population by Tract

    • catalog.data.gov
    • datasets.ai
    Updated Mar 1, 2024
    + more versions
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    U.S. Department of Housing and Urban Development (2024). Low to Moderate Income Population by Tract [Dataset]. https://catalog.data.gov/dataset/low-to-moderate-income-population-by-tract
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    This service identifies U.S. Census Tracts in which 51% or more of the households earn less than 80 percent of the Area Median Income (AMI). The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income.

  5. HUD Low and Moderate Income Areas

    • data.wu.ac.at
    • data.amerigeoss.org
    api, bin
    Updated Jan 1, 2015
    + more versions
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    Department of Housing and Urban Development (2015). HUD Low and Moderate Income Areas [Dataset]. https://data.wu.ac.at/schema/data_gov/MWY4Nzc1MzUtYTM0YS00YjIzLThjYmItMDUwOWEzMTZiMWU0
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    bin, apiAvailable download formats
    Dataset updated
    Jan 1, 2015
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

  6. s

    Persistent low income

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Sep 17, 2025
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    Race Disparity Unit (2025). Persistent low income [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/pay-and-income/low-income/latest
    Explore at:
    csv(81 KB), csv(302 KB)Available download formats
    Dataset updated
    Sep 17, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Between 2019 and 2023, people living in households in the Asian and ‘Other’ ethnic groups were most likely to be in persistent low income before and after housing costs

  7. IRA Low-Income Community Bonus Credit Program Layers

    • catalog.data.gov
    • data.openei.org
    • +1more
    Updated Jan 20, 2025
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    Office of Economic Impact & Diversity US Department of Energy (2025). IRA Low-Income Community Bonus Credit Program Layers [Dataset]. https://catalog.data.gov/dataset/ira-low-income-community-bonus-credit-program-layers-3d4e4
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    Dataset updated
    Jan 20, 2025
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Description

    These geospatial data resources and the linked mapping tool below reflect currently available data on three categories of potentially qualifying Low-Income communities: Census tracts that meet the CDFI's New Market Tax Credit Program's threshold for Low Income, thereby are able to apply to Category 1. Census tracts that meet the White House's Climate and Economic Justice Screening Tool's threshold for disadvantage in the 'Energy' category, thereby are able to apply for Additional Selection Criteria Geography. Counties that meet the USDA's threshold for Persistent Poverty, thereby are able to apply for Additional Selection Criteria Geography. Note that Category 2 - Indian Lands are not shown on this map. Note that Persistent Poverty is not calculated for US Territories. Note that CEJST Energy disadvantage is not calculated for US Territories besides Puerto Rico. The excel tool provides the land area percentage of each 2023 census tract meeting each of the above categories. To examine geographic eligibility for a specific address or latitude and longitude, visit the program's mapping tool. Additional information on this tax credit program can be found on the DOE Landing Page for the 48e program at https://www.energy.gov/diversity/low-income-communities-bonus-credit-program or the IRS Landing Page at https://www.irs.gov/credits-deductions/low-income-communities-bonus-credit. Maps last updated: September 1st, 2024 Next map update expected: December 7th, 2024 Disclaimer: The spatial data and mapping tool is intended for geolocation purposes. It should not be relied upon by taxpayers to determine eligibility for the Low-Income Communities Bonus Credit Program. Source Acknowledgements: The New Market Tax Credit (NMTC) Tract layer using data from the 2016-2020 ACS is from the CDFI Information Mapping System (CIMS) and is created by the U.S. Department of Treasury Community Development Financial Institutions Fund. To learn more, visit CDFI Information Mapping System (CIMS) | Community Development Financial Institutions Fund (cdfifund.gov). https://www.cdfifund.gov/mapping-system. Tracts are displayed that meet the threshold for the New Market Tax Credit Program. The 'Energy' Category Tract layer from the Climate and Economic Justice Screening Tool (CEJST) is created by the Council on Environmental Quality (CEQ) within the Executive Office of the President. To learn more, visit https://screeningtool.geoplatform.gov/en/. Tracts are displayed that meet the threshold for the 'Energy' Category of burden. I.e., census tracts that are at or above the 90th percentile for (energy burden OR PM2.5 in the air) AND are at or above the 65th percentile for low income. The Persistent Poverty County layer is created by joining the U.S. Department of Agriculture, Economic Research Service's Poverty Area Official Measures dataset, with relevant county TIGER/Line Shapefiles from the US Census Bureau. To learn more, visit https://www.ers.usda.gov/data-products/poverty-area-measures/. Counties are displayed that meet the thresholds for Persistent Poverty according to 'Official' USDA updates. i.e. 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). Until Dec 7th, 2024 both the USDA estimates using 2007-2011 and 2017-2021 ACS 5-year data. On Dec 8th, 2024, only the USDA estimates using 2017-2021 data will be accepted for program eligibility.

  8. v

    Low Income Community Census Tracts - 2016-2020 ACS

    • anrgeodata.vermont.gov
    • data-smpdc.opendata.arcgis.com
    • +2more
    Updated Oct 11, 2023
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    momentumx (2023). Low Income Community Census Tracts - 2016-2020 ACS [Dataset]. https://anrgeodata.vermont.gov/datasets/7f445b2577fd400086fa7a3a0b726359
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    Dataset updated
    Oct 11, 2023
    Dataset authored and provided by
    momentumx
    Area covered
    Description

    This layer contains American Community Survey (ACS) 2016-2020 5-year estimates in order to determine if a Census tract is considered an opportunity zone/low income community. According to Tax Code Section 45D(e), low income Census Tracts are based on the following criteria:The poverty rate is at least 20 percent, ORThe median family income does not exceed 80 percent of statewide median family income or, if in a metropolitan area, the greater of 80 percent statewide median family income or 80 percent of metropolitan area median family incomeThe layer is visualized to show if a tract meets these criteria, and the pop-up provides poverty figures as well as tract, metropolitan area, and state level figures for median family income. When a tract meets the above criteria, it may also qualify for grants or findings such Opportunity Zones. These zones are designed to encourage economic development and job creation in communities throughout the country by providing tax benefits to investors who invest eligible capital into these communities. Another way this layer can be used is to gain funding through the Inflation Reduction Act of 2022. The data was downloaded on October 5, 2022 from the US Census Bureau via data.census.gov:Table B17020: Poverty Status in the Past 12 Months - TractsTable B19113: Median Family Income in the Past 12 Months (in 2020 inflation-adjusted dollars) - Tracts, Metropolitan area, StateVintage of the data: 2016-2020 American Community SurveyBoundaries used for analysis: TIGER 2020 Tract, Metro, and State Boundaries with large hydrography removed from tractsData was processed within ArcGIS Pro 3.0.2 using ModelBuilder to spatially join the metropolitan and state geographies to tracts.To see the same qualification on 2010-based Census tracts, there is also an older 2012-2016 version of the layer.

  9. Bangladesh - Chattogram Low Income Area Gender, Inclusion, and Poverty...

    • datacatalog.worldbank.org
    html
    Updated Oct 21, 2021
    + more versions
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    Johannes Hoogeveen, World Bank (Poverty and Equity GP) (2021). Bangladesh - Chattogram Low Income Area Gender, Inclusion, and Poverty Survey 2019 [Dataset]. https://datacatalog.worldbank.org/search/dataset/0047409/bangladesh-chattogram-low-income-area-gender-inclusion-and-poverty-survey-2019
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Oct 21, 2021
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    License

    https://datacatalog.worldbank.org/public-licenses?fragment=researchhttps://datacatalog.worldbank.org/public-licenses?fragment=research

    Area covered
    Chattogram, Bangladesh
    Description

    The main objective of the 2019 Chattogram for Low Income Area Gender, Inclusion, and Poverty (CITY) study is to collect primary data from male and female residents in slum and non-slum poor neighborhoods in Chattogram, the second largest city of Bangladesh, and build the evidence base about their constraints to access more and better jobs. The CITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh as well as to identify key constraints and solutions for low-income women trying to obtain better jobs.

    A broad array of information was collected on issues related to women's economic empowerment, ranging from demographic and socioeconomic characteristics to detailed work history, time use, attitudes about work, and perceptions of work. The key feature of this survey is to collect economic data directly from the main household members, generally the main couples, unlike traditional surveys which only interviewed the heads of households (who tend to be men in most cases); thus, failed to gather valuable information from the female population.

  10. School Neighborhood Poverty Estimates, 2020-21

    • catalog.data.gov
    • data-nces.opendata.arcgis.com
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2020-21 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2020-21
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    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.

  11. Data from: Public Use Data (2008-10) on Long-Term Neighborhood Effects on...

    • icpsr.umich.edu
    Updated Jan 15, 2014
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    Ludwig, Jens; Duncan, Greg J.; Gennetian, Lisa A.; Katz, Lawrence; Kessler, Ronald; Kling, Jeffrey; Sanbonmatsu, Lisa (2014). Public Use Data (2008-10) on Long-Term Neighborhood Effects on Low-Income Families (Adult Data Only) from All Five Sites of the Moving to Opportunity Experiment [Dataset]. http://doi.org/10.3886/ICPSR34976.v1
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    Dataset updated
    Jan 15, 2014
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Ludwig, Jens; Duncan, Greg J.; Gennetian, Lisa A.; Katz, Lawrence; Kessler, Ronald; Kling, Jeffrey; Sanbonmatsu, Lisa
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/34976/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/34976/terms

    Time period covered
    2008 - 2010
    Area covered
    Illinois, Baltimore, Massachusetts, Maryland, New York (state), California, United States, New York City, Los Angeles, Chicago
    Description

    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 experimental group (also called the low-poverty voucher (LPV) 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 Section 8 group (also called the traditional voucher (TRV) 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 (1994-98) through the long-term evaluation survey fielding period (2008-10) with the purpose of determining the effects of "neighborhood" on participating families. This data collection contains data from the 3,273 adult interviews completed as part of the MTO long-term evaluation and are comprised of adult variables that have been analyzed. Using data from the long-term evaluation, the associated article reports that moving from a high-poverty to lower-poverty neighborhood leads to long-term (10- to 15-year) improvements in adult physical and mental health and subjective well-being, despite not affecting economic self-sufficiency. The data contain all adult outcomes and mediators analyzed for the associated article as well as a variety of demographic and other baseline measures that were controlled for in the analysis.

  12. Vital Signs: Poverty - by city

    • data.bayareametro.gov
    • open-data-demo.mtc.ca.gov
    csv, xlsx, xml
    Updated Dec 12, 2018
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    U.S. Census Bureau (2018). Vital Signs: Poverty - by city [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-by-city/if2n-3uk8
    Explore at:
    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Dec 12, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Description

    VITAL SIGNS INDICATOR Poverty (EQ5)

    FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

    LAST UPDATED December 2018

    DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

    DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

    U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

    METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

    For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

    For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

    To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

  13. Income Limits by County

    • data.ca.gov
    • catalog.data.gov
    csv, docx
    Updated Feb 7, 2024
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    California Department of Housing and Community Development (2024). Income Limits by County [Dataset]. https://data.ca.gov/dataset/income-limits-by-county
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    docx(31186), csv(15447), csv(15546)Available download formats
    Dataset updated
    Feb 7, 2024
    Dataset provided by
    California Department of Housing & Community Developmenthttps://hcd.ca.gov/
    Authors
    California Department of Housing and Community Development
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    California State Income Limits reflect updated median income and household income levels for acutely low-, extremely low-, very low-, low- and moderate-income households for California’s 58 counties (required by Health and Safety Code Section 50093). These income limits apply to State and local affordable housing programs statutorily linked to HUD income limits and differ from income limits applicable to other specific federal, State, or local programs.

  14. Dhaka Low Income Area Gender, Inclusion, and Poverty Survey 2018 -...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Mar 9, 2020
    + more versions
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    The World Bank Group (2020). Dhaka Low Income Area Gender, Inclusion, and Poverty Survey 2018 - Bangladesh [Dataset]. https://microdata.worldbank.org/index.php/catalog/3635
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    Dataset updated
    Mar 9, 2020
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    The World Bank Group
    Time period covered
    2018
    Area covered
    Bangladesh
    Description

    Abstract

    The 2018 Dhaka Low Income Area Gender, Inclusion, and Poverty (DIGNITY) survey attempts to fill in the data and knowledge gaps on women's economic empowerment in urban areas, specifically the factors that constrain women in slums and low-income neighborhoods from engaging in the labor market and supplying their labor to wage earning or self-employment. While an array of national-level datasets has collected a wide spectrum of information, they rarely comprise all of the information needed to study the drivers of Female Labor Force Participation (FLFP). This data gap is being filled by the primary data collection of the specialized DIGNITY survey; it is representative of poor urban areas and is specifically designed to address these limitations. The DIGNITY survey collected information from 1,300 urban households living in poor areas of Dhaka in 2018 on a range of issues that affect FLFP as identified through the literature. These range from household composition and demographic characteristics to socioeconomic characteristics such as detailed employment history and income (including locational data and travel details); and from technical and educational attributes to issues of time use, migration history, and attitudes and perceptions.

    The DIGNITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh. It has two main modules: the traditional household module (in which the head of household is interviewed on basic information about the household); and the individual module, in which two respondents from each household are interviewed individually. In the second module, two persons - one male and one female from each household, usually the main couple, are selected for the interview. The survey team deployed one male and one female interviewer for each household, so that the gender of the interviewers matched that of the respondents. Collecting economic data directly from a female and male household member, rather than just the head of the household (who tend to be men in most cases), was a key feature of the DIGNITY survey.

    Geographic coverage

    The DIGNITY survey is representative of low-income areas and slums of the Dhaka City Corporations (North and South, from here on referred to as Dhaka CCs), and an additional low-income site from the Greater Dhaka Statistical Metropolitan Area (SMA).

    Analysis unit

    • Household
    • Individual

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling procedure followed a two-stage stratification design. The major features include the following steps (they are discussed in more detail in a copy of the study's report and the sampling document located in "External Resources"):

    FIRST STAGE: Selection of the PSUs

    Low-income primary sampling units (PSUs) were defined as nonslum census enumeration areas (EAs), in which the small-sample area estimate of the poverty rate is higher than 8 percent (using the 2011 Bangladesh Poverty Map). The sampling frame for these low-income areas in the Dhaka City Corporations (CCs) and Greater Dhaka is based on the population census of 2011. For the Dhaka CCs, all low-income census EAs formed the sampling frame. In the Greater Dhaka area, the frame was formed by all low-income census EAs in specific thanas (i.e. administrative unit in Bangladesh) where World Bank project were located.

    Three strata were used for sampling the low-income EAs. These strata were defined based on the poverty head-count ratios. The first stratum encompasses EAs with a poverty headcount ratio between 8 and 10 percent; the second stratum between 11 and 14 percent; and the third stratum, those exceeding 15 percent.

    Slums were defined as informal settlements that were listed in the Bangladesh Bureau of Statistics' slum census from 2013/14. This census was used as sampling frame of the slum areas. Only slums in the Dhaka City Corporations are included. Again, three strata were used to sample the slums. This time the strata were based on the size of the slums. The first stratum comprises slums of 50 to 75 households; the second 76 to 99 households; and the third, 100 or more households. Small slums with fewer than 50 households were not included in the sampling frame. Very small slums were included in the low-income neighborhood selection if they are in a low-income area.

    Altogether, the DIGNITY survey collected data from 67 PSUs.

    SECOND STAGE: Selection of the Households

    In each sampled PSU a complete listing of households was done to form the frame for the second stage of sampling: the selection of households. When the number of households in a PSU was very large, smaller sections of the neighborhood were identified, and one section was randomly selected to be listed. The listing data collected information on the demographics of the household to determine whether a household fell into one of the three categories that were used to stratify the household sample:

    i) households with both working-age male and female members; ii) households with only a working-age female; iii) households with only a working-age male.

    Households were selected from each stratum with the predetermined ratio of 16:3:1. In some cases there were not enough households in categories (ii) and (iii) to stick to this ratio; in this case all of the households in the category were sampled, and additional households were selected from the first category to bring the total number of households sampled in each PSU to 20.

    The total sample consisted of 1,300 households (2,378 individuals).

    Sampling deviation

    The sampling for 1300 households was planned after the listing exercise. During the field work, about 115 households (8.8 percent) could not be interviewed due to household refusal or absence. These households were replaced with reserved households in the sample.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The questionnaires for the survey were developed by the World Bank, with assistance from the survey firm, DATA. Comments were incorporated following the pilot tests and practice session/pretest.

    Cleaning operations

    Collected data was entered into a computer by using the customized MS Access data input software developed by Data Analysis and Technical Assistance (DATA). Once data entry was completed, two different techniques were employed to check consistency and validity of data as follows:

    1. Five (5%) percent of the filled-in questionnaire was checked against entered data to measure the transmission error or typos, and;
    2. A logical consistency checking technique was employed to identify inconsistencies using SPSS and or STATA software.
  15. U.S. poverty rate 2024, by race and ethnicity

    • statista.com
    Updated Nov 5, 2025
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    Statista (2025). U.S. poverty rate 2024, by race and ethnicity [Dataset]. https://www.statista.com/statistics/200476/us-poverty-rate-by-ethnic-group/
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    Dataset updated
    Nov 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    In 2024, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the overall poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States The poverty threshold for a single person in the United States was measured at an annual income of ****** U.S. dollars in 2023. Among families of four, the poverty line increases to ****** U.S. dollars a year. Women and children are more likely to suffer from poverty. This is due to the fact that women are more likely than men to stay at home, to care for children. Furthermore, the gender-based wage gap impacts women's earning potential. Poverty data Despite being one of the wealthiest nations in the world, the United States has some of the highest poverty rates among OECD countries. While, the United States poverty rate has fluctuated since 1990, it has trended downwards since 2014. Similarly, the average median household income in the U.S. has mostly increased over the past decade, except for the covid-19 pandemic period. Among U.S. states, Louisiana had the highest poverty rate, which stood at some ** percent in 2024.

  16. d

    Connecticut Qualified Census Tracts

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Jun 21, 2025
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    data.ct.gov (2025). Connecticut Qualified Census Tracts [Dataset]. https://catalog.data.gov/dataset/ct-qualified-census-tracts
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.ct.gov
    Area covered
    Connecticut
    Description

    This dataset provides access to Qualified Census Tracts (QCTs) in Connecticut to assist in administration of American Rescue Plan (ARP) funds. The Secretary of HUD must designate QCTs, which are areas where either 50 percent or more of the households have an income less than 60 percent of the AMGI for such year or have a poverty rate of at least 25 percent. HUD designates QCTs based on new income and poverty data released in the American Community Survey (ACS). Specifically, HUD relies on the most recent three sets of ACS data to ensure that anomalous estimates, due to sampling, do not affect the QCT status of tracts. QCTs are identified for the purpose of Low-Income Housing Credits under IRC Section 42, with the purpose of increasing the availability of low-income rental housing by providing an income tax credit to certain owners of newly constructed or substantially rehabilitated low-income rental housing projects. Also included are the number of households from the 2010 census (the “p0150001” variable), the average poverty rate using the 2014-2018 ACS data (the “pov_rate_18” variable), and the ratio of Tract Average Household Size Adjusted Income Limit to Tract Median Household Income using the 2014-2018 ACS data (the “inc_factor_18” variable). For the last variable mentioned in the previous paragraph, the income limit is the limit for being considered a very low income household (size-adjusted and based on Area Mean Gross Income). This value is divided by the median household income for the given tract, to get a sense of how the limit and median incomes compare. For example, if ratio>1, it implies that the tract is very low income because the limit income is greater than the median income. This ratio is a compact way to include the separate variables for the household income limit and median household income for each tract.

  17. g

    Low-Income Housing Tax Credit (LIHTC) Qualified Census Tracts | gimi9.com

    • gimi9.com
    + more versions
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    Low-Income Housing Tax Credit (LIHTC) Qualified Census Tracts | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_qualified-census-tracts/
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    Description

    A Qualified Census Tract (QCT) is any census tract (or equivalent geographic area defined by the Census Bureau) in which at least 50% of households have an income less than 60% of the Area Median Gross Income (AMGI). HUD has defined 60% of AMGI as 120% of HUD's Very Low Income Limits (VLILs), which are based on 50% of area median family income, adjusted for high cost and low income areas.

  18. g

    Low-Income Housing Tax Credit (LIHTC) Qualified Census Tracts | gimi9.com

    • gimi9.com
    + more versions
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    Low-Income Housing Tax Credit (LIHTC) Qualified Census Tracts | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_low-income-housing-tax-credit-lihtc-qualified-census-tracts/
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    Description

    This dataset provides data on Qualified Census Tracts for the Low-Income Housing Tax Credit Program for 2024. LIHTC Qualified Census Tracts, as defined under the section 42(d)(5)(C) of the of the Internal Revenue Code of 1986, include any census tract (or equivalent geographic area defined by the Bureau of the Census) in which at least 50 percent of households have an income less than 60 percent of the Area Median Gross Income (AMGI), or which has a poverty rate of at least 25 percent. Maps of Qualified Census Tracts and Difficult Development Areas are available at: huduser.gov/sadda/sadda_qct.html .

  19. Qualified Census Tracts

    • data.wu.ac.at
    • catalog.data.gov
    • +1more
    bin
    Updated Jan 1, 2015
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    Department of Housing and Urban Development (2015). Qualified Census Tracts [Dataset]. https://data.wu.ac.at/schema/data_gov/ZjIyZmJkNTAtYjcyNy00ZTZlLTliZTItMzM1YzVjNTE2NjZk
    Explore at:
    binAvailable download formats
    Dataset updated
    Jan 1, 2015
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    A Qualified Census Tract (QCT) is any census tract (or equivalent geographic area defined by the Census Bureau) in which at least 50% of households have an income less than 60% of the Area Median Gross Income (AMGI). HUD has defined 60% of AMGI as 120% of HUD's Very Low Income Limits (VLILs), which are based on 50% of area median family income, adjusted for high cost and low income areas.

  20. Children in low income families: local area statistics 2014 to 2024

    • gov.uk
    Updated Mar 27, 2025
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    Department for Work and Pensions (2025). Children in low income families: local area statistics 2014 to 2024 [Dataset]. https://www.gov.uk/government/statistics/children-in-low-income-families-local-area-statistics-2014-to-2024
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    Dataset updated
    Mar 27, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Work and Pensions
    Description

    This release has replaced DWP’s Children in out-of-work benefit households and HMRC’s Personal tax credits: Children in low-income families local measure releases.

    For both Relative and Absolute measures, Before Housing Costs, these annual statistics include counts of children by geography, including by:

    • local authority

    • Westminster parliamentary constituency

    • Ward

    • Middle Super Output Area

    • year (2014 to 2023)

    • age of child

    • gender of child

    • family type

    • work status of the family

    Explore the statistics with our interactive tool

    Find further breakdowns of these statistics on https://stat-xplore.dwp.gov.uk/">Stat-Xplore, an online tool for exploring some of DWP’s main statistics.

    Future releases and developments

    Find future release dates in the statistics release calendar and more about DWP statistics on the Statistics at DWP page.

    Future developments to DWP official statistics and any changes to statistical methodology are outlined in the statistical work programme.

    Tell us what you think

    Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/the-code/">Code of Practice for Statistics that all producers of official statistics should adhere to. You are welcome to contact us directly with any comments about how we meet these standards.

    Email  stats.consultation-2018@dwp.gov.uk

    Alternatively, you can contact OSR by emailing  regulation@statistics.gov.uk or via the OSR website.

    For media enquiries please contact the DWP press office.

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Virginia Department of Environmental Quality (2025). Low Income Communities [Dataset]. https://data.virginia.gov/dataset/low-income-communities

Low Income Communities

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csv, geojson, kml, zip, arcgis geoservices rest api, htmlAvailable download formats
Dataset updated
Nov 25, 2025
Dataset provided by
{{source}}
Authors
Virginia Department of Environmental Quality
Description
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