Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comprehensive dataset containing 62 verified Low income housing program businesses in Massachusetts, United States with complete contact information, ratings, reviews, and location data.
Facebook
TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
This data, maintained by the Mayor’s Office of Housing (MOH), is an inventory of all income-restricted units in the city. This data includes public housing owned by the Boston Housing Authority (BHA), privately- owned housing built with funding from DND and/or on land that was formerly City-owned, and privately-owned housing built without any City subsidy, e.g., created using Low-Income Housing Tax Credits (LIHTC) or as part of the Inclusionary Development Policy (IDP). Information is gathered from a variety of sources, including the City's IDP list, permitting and completion data from the Inspectional Services Department (ISD), newspaper advertisements for affordable units, Community Economic Development Assistance Corporation’s (CEDAC) Expiring Use list, and project lists from the BHA, the Massachusetts Department of Housing and Community Development (DHCD), MassHousing, and the U.S. Department of Housing and Urban Development (HUD), among others. The data is meant to be as exhaustive and up-to-date as possible, but since many units are not required to report data to the City of Boston, MOH is constantly working to verify and update it. See the data dictionary for more information on the structure of the data and important notes.
The database only includes units that have a deed-restriction. It does not include tenant-based (also known as mobile) vouchers, which subsidize rent, but move with the tenant and are not attached to a particular unit. There are over 22,000 tenant-based vouchers in the city of Boston which provide additional affordability to low- and moderate-income households not accounted for here.
The Income-Restricted Housing report can be directly accessed here:
https://www.boston.gov/sites/default/files/file/2023/04/Income%20Restricted%20Housing%202022_0.pdf
Learn more about income-restricted housing (as well as other types of affordable housing) here: https://www.boston.gov/affordable-housing-boston#income-restricted
Facebook
TwitterData and code to replicate the results "How Affordable Housing Can Exclude: The Political Economy of Subsidized Housing." All data on subsidized housing units provided by Housing Navigator Massachusetts (https://housingnavigatorma.org/). All demographic data retrieved from the 2018-2022 American Community Survey 5-year averages.
Facebook
TwitterThe feature set indicates the locations, and tenant characteristics of public housing development buildings for the San Francisco Bay Region. This feature set, extracted by the Metropolitan Transportation Commission, is from the statewide public housing buildings feature layer provided by the California Department of Housing and Community Development (HCD). HCD itself extracted the California data from the United States Department of Housing and Urban Development (HUD) feature service depicting the location of individual buildings within public housing units throughout the United States.
According to HUD's Public Housing Program, "Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by some 3,300 housing agencies. HUD administers federal aid to local housing agencies that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments.
HUD administers Federal aid to local Housing Agencies (HAs) that manage housing for low-income residents at rents they can afford. Likewise, HUD furnishes technical and professional assistance in planning, developing, and managing the buildings that comprise low-income housing developments. This feature set provides the location, and resident characteristics of public housing development buildings.
Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes:
‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green)
‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green)
‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow)
‘T’ - Census tract centroid (low degree of accuracy, symbolized as red)
‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red)
‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red)
‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red)
Null - Could not be geocoded (does not appear on the map)
For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information, the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10.
HCD downloaded the HUD data in April 2021. They sourced the data from https://hub.arcgis.com/datasets/fedmaps::public-housing-buildings.
To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/.
Facebook
TwitterFinancial overview and grant giving statistics of Southeastern Massachusetts Affordable Housing Corporation
Facebook
TwitterThis 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.
Facebook
TwitterFinancial overview and grant giving statistics of Massachusetts Affordable Housing Alliance Inc.
Facebook
Twitter
According to our latest research, the affordable housing market size reached USD 69.2 billion globally in 2024, driven by rapid urbanization, supportive government policies, and rising demand for cost-effective housing solutions. The market is projected to expand at a robust CAGR of 6.1% from 2025 to 2033, reaching an estimated USD 117.4 billion by the end of the forecast period. The growth is primarily attributed to increasing urban migration, widening income disparities, and a surge in public and private investments aimed at addressing the global housing deficit. As per our latest research, the affordable housing sector is undergoing significant transformation as stakeholders focus on innovative construction methods, sustainable materials, and digital technologies to streamline project delivery and reduce costs.
One of the primary growth drivers for the affordable housing market is the escalating rate of urbanization, particularly in emerging economies. Urban populations are swelling at an unprecedented pace, with millions migrating to cities in search of better employment opportunities and improved living standards. This mass migration has led to a surge in demand for affordable, quality housing, placing immense pressure on urban infrastructure and local governments. Consequently, both public and private sector players are ramping up investments in affordable housing projects, leveraging innovative financing models and partnerships to bridge the housing gap. Furthermore, the emergence of smart city initiatives and sustainable urban planning is fostering the development of integrated, affordable housing solutions that cater to the diverse needs of low- and middle-income populations.
Another significant factor propelling the affordable housing market is the increasing involvement of governments and international organizations in addressing the global housing crisis. Numerous policy interventions, such as subsidies, tax incentives, and relaxed regulatory frameworks, are being introduced to stimulate the supply of affordable homes. Governments are also collaborating with private developers through public-private partnerships (PPPs) to expedite project execution and ensure long-term sustainability. Additionally, multilateral agencies and non-governmental organizations are providing technical and financial assistance to support large-scale affordable housing initiatives, particularly in regions with acute housing shortages. These concerted efforts are not only enhancing access to affordable housing but also fostering socio-economic development and reducing urban poverty.
Technological advancements in construction methods and materials are further accelerating the growth of the affordable housing market. The adoption of modular and prefabricated construction techniques is enabling developers to deliver high-quality housing units at lower costs and within shorter timeframes. These innovative approaches are also contributing to improved energy efficiency, reduced environmental impact, and enhanced structural durability. Moreover, the integration of digital technologies, such as Building Information Modeling (BIM) and project management software, is streamlining the design, planning, and execution of affordable housing projects. As a result, stakeholders are increasingly embracing technology-driven solutions to optimize resource utilization, minimize risks, and ensure compliance with stringent regulatory standards.
From a regional perspective, Asia Pacific continues to dominate the affordable housing market, accounting for the largest share in 2024, followed by North America and Europe. The region's rapid urbanization, burgeoning population, and proactive government policies are driving significant investments in affordable housing infrastructure. Countries such as China, India, and Indonesia are at the forefront, implementing ambitious housing schemes and leveraging innovative construction technologies to address the growing demand. Meanwhile, developed regions like North America and Europe are witnessing renewed interest in affordable housing, fueled by rising property prices, income inequality, and shifting demographic trends. Latin America and the Middle East & Africa are also emerging as promising markets, supported by favorable regulatory environments and increased foreign direct investments.
Facebook
TwitterNot all households in San Mateo County enjoy the opportunities that its high-performing economy has to offer. DOH's goal is to increase the rate at which the County’s low-income residents are able to access the opportunities the county has to offer by encouraging affordable housing development in High and Highest Resource areas. High and Highest Resource areas are mapped here: CTCAC/HCD Opportunity Area Map: https://www.treasurer.ca.gov/ctcac/opportunity.asp. This map identifies areas in every region of the state whose characteristics have been shown by research to be associated with positive economic, educational, and health outcomes for low-income families—particularly long-term outcomes for children. DOH will use its development pipeline dashboard to map the location of DOH-investments in affordable housing projects within these higher resource areas. The AHF Notice of Funding Opportunity will continue to prioritize developments located in higher resource areas. The definition for high and highest opportunity areas may change in the future but will be informed by State guidance and methodology. This performance measure shows the percentage of affordable housing development projects completed in the high and highest resource areas in a fiscal year. Project completion was selected as a benchmark as this is the time when low-income families gain access to affordable housing. DOH disaggregates the data showing the percentage of units, from the completed projects in a fiscal year, by income level and a special population served known as County Clients.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comprehensive dataset containing 10 verified Public housing businesses in Massachusetts, United States with complete contact information, ratings, reviews, and location data.
Facebook
TwitterThe map displays parcels currently owned by UDOT that may be suitable for future affordable housing development. The analysis focuses on publicly owned land to streamline feasibility and reduce development barriers.To support equitable, transit-oriented housing, the map also includes key transportation infrastructure:Public transportation are shown to highlight transit access.This resource supports internal planning, helping to prioritize agency-owned sites for further study or partnership opportunities related to affordable and low-income housing.The Right of Way (ROW) team is responsible for maintaining and updating this parcel layer as needed to reflect changes in ownership, availability, or planning priorities. This app uses the map Potential Sites for Affordable Housing Development . For questions on the data, please contact ROW GIS team at rowgis@utah.gov
Facebook
TwitterThis map shows households that spend 30 percent or more of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities: Enroll eligible households in programs designed to assist them.Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.
Facebook
TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
San Mateo County Affordable Rental Housing for Low & Moderate Income Households broken down by city. This affordable housing list is updated as needed by us and the cities, property owners and developers listed.
For a real-time housing list of San Mateo County properties, you can visit SMCHousingSearch: http://www.smchousingsearch.org/
Facebook
TwitterCoastal Risk Screening Tool: Affordable HousingThe affordable housing map allows users to explore what affordable housing in the U.S. could be threatened by sea level rise and coastal flooding in the coming decades, under multiple pollution scenarios. The map allows users to examine affordable housing at risk by state, city, county, congressional district, state legislative district, or zip code.
Facebook
TwitterThe map displays parcels currently owned by UDOT that may be suitable for future affordable housing development. The analysis focuses on publicly owned land to streamline feasibility and reduce development barriers.To support equitable, transit-oriented housing, the map also includes key transportation infrastructure:Public transportation are shown to highlight transit access.This resource supports internal planning, helping to prioritize agency-owned sites for further study or partnership opportunities related to affordable and low-income housing.The Right of Way (ROW) team is responsible for maintaining and updating this parcel layer as needed to reflect changes in ownership, availability, or planning priorities. This app uses the map Potential Sites for Affordable Housing Development . For questions on the data, please contact ROW GIS team at rowgis@utah.gov
Facebook
Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
City map highlighting 2024 qualified census tracts (QCT) in Mesa. Low-Income Housing Tax Credit Qualified Census Tracts must have 50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more. Maps of Qualified Census Tracts are available at: https://www.huduser.gov/portal/datasets/qct.html
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The DC Housing Authority provides quality affordable housing to extremely low- through moderate-income households, fosters sustainable communities, and cultivates opportunities for residents to improve their lives. The following is a subset of the District Government Land (Owned, Operated, and or managed) dataset that include buildings with a "public housing" use type.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment.
Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11.
The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document).
For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below.
For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.
Facebook
Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
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/
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for All-Transactions House Price Index for Massachusetts (MASTHPI) from Q1 1975 to Q2 2025 about MA, appraisers, HPI, housing, price index, indexes, price, and USA.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comprehensive dataset containing 62 verified Low income housing program businesses in Massachusetts, United States with complete contact information, ratings, reviews, and location data.