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

Comprehensive dataset of 69 Low income housing programs in Massachusetts, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Graph and download economic data for All-Transactions House Price Index for Massachusetts (MASTHPI) from Q1 1975 to Q1 2025 about MA, appraisers, HPI, housing, price index, indexes, price, and USA.

This data set, compiled by the Fraunhofer Center for Sustainable Energy Systems, includes long-term 10-minute temperature and relative humidity data, and HVAC system state data for 79 apartments in a low-income housing complex in Revere, MA. The monitoring period spans two winters and one summer between 2011 and 2013. Data were collected as part of a project sponsored by the U.S. Department of Energy Building America program to evaluate the impact of programmable thermostat usability on occupant behavior. This project was done in conjunction with NREL as part of the US Department of Energy's Building America program.

Graph and download economic data for New Private Housing Units Authorized by Building Permits: 1-Unit Structures for Massachusetts (MABP1FHSA) from Jan 1988 to Apr 2025 about privately owned, 1-unit structures, MA, permits, family, buildings, housing, and USA.

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 Surveymore » 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.« less

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACSAnnotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.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.-9An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.-8An '-8' means that the estimate is not applicable or not available.-6A '-6' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.-5A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.-3A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.-2A '-2' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACSAnnotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.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. -9 An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small. -8 An '-8' means that the estimate is not applicable or not available. -6 A '-6' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. -5 A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. -3 A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate. -2 A '-2' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.

Graph and download economic data for Homeownership Rate (5-year estimate) for Middlesex County, MA (HOWNRATEACS025017) from 2009 to 2023 about Middlesex County, MA; Boston; homeownership; MA; housing; 5-year; rate; and USA.

United States Massachusetts: GR: OS: CM: Charges: Housing & Community Development data was reported at 391,872.000 USD th in 2015. This records an increase from the previous number of 366,824.000 USD th for 2014. United States Massachusetts: GR: OS: CM: Charges: Housing & Community Development data is updated yearly, averaging 216,501.000 USD th from Jun 1977 (Median) to 2015, with 37 observations. The data reached an all-time high of 391,872.000 USD th in 2015 and a record low of 46,057.000 USD th in 1978. United States Massachusetts: GR: OS: CM: Charges: Housing & Community Development data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.F030: Revenue & Expenditure: State and Local Government: Massachusetts.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Click here to check Short-Term Rental Eligibility

Boston's ordinance on short-term rentals is designed to incorporate the growth of the home-share industry into the City's work to create affordable housing for all residents. We want to preserve housing for residents while allowing Bostonians to benefit from this new industry. Starting on on January 1, 2019, short-term rentals in Boston will need to register with the City of Boston.

Eligibility for every unit in the City of Boston is dependant on the following six criteria:

• No affordability covenant restrictions
• Compliance with housing laws and codes
• No violations of laws regarding short-term rental use
• Owner occupied
• Two- or three-family dwelling
• Residential use classification

The Short-Term Rental Eligibility Dataset leverages information, wherever possible, about these criteria. For additional details and information about these criteria, please visit https://www.boston.gov/short-term-rentals.

ABOUT THIS DATASET

In June 2018, a citywide ordinance established new guidelines and regulations for short-term rentals in Boston. Registration opened January 1, 2019. The Short-Term Rental Eligibility Dataset was created to help residents, landlords, and City officials determine whether a property is eligible to be registered as a short-term rental.

The Short-Term Rental Eligibility Dataset currently joins data from the following datasets and is refreshed nightly:

• Live Street Address Management (SAM) Addresses.
• Assessing Online.
• Building and Property Violations
• Problem Properties
• Income-Restricted Properties
• STR Registration Data

HOW TO DETERMINE ELIGIBILITY FOR SHORT-TERM RENTAL REGISTRATION

1. ** Open** the Short-Term Rental Eligibility Dataset. In the dataset's search bar, enter the address of the property you are seeking to register.

2. Find the row containing the correct address and unit of the property you are seeking. This is the information we have for your unit.

3. Look at the columns marked as “Home-Share Eligible,” “Limited-Share Eligible,” and “Owner-Adjacent Eligible.”

   • A “yes” under any of these columns means your unit IS eligible for registration under that short-term rental type. Click here for a description of short-term rental types.
   • A “no” under any of these columns means your unit is NOT eligible for registration under that short-term rental type. Click here for a description of short-term rental types.

4. If your unit has a “yes” under “Home-Share Eligible,” “Limited-Share Eligible,” or “Owner-Adjacent Eligible,” you can register your unit here.

WHY IS MY UNIT LISTED AS “NOT ELIGIBLE”?

If you find that your unit is listed as NOT eligible, and you would like to understand more about why, you can use the Short-Term Rental Eligibility Dataset to learn more. The following columns measure each of the six eligibility criteria in the following ways:

1. No affordability covenant restrictions

   • A “yes” in the “Income Restricted” column tells you that the unit is marked as income restricted and is NOT eligible.
     
     
   • The “Income Restricted” column measures whether the unit is subject to an affordability covenant, as reported by the Department of Neighborhood Development and/or the Boston Planning and Development Agency.
     
     
   • For questions about affordability covenants, contact the Department of Neighborhood Development.
     
     

2. Compliance with housing laws and codes

   • A “yes” in the “Problem Properties” column tells you that this unit is considered a “Problem Property” by the Problem Properties Task Force and is NOT eligible.
     
     
   • Learn more about how “Problem Properties” are defined here.
     
     
   • A “yes” in the “Problem Property Owner” column tells you that the owner of this unit also owns a “Problem Property,” as reported by the Problem Properties Task Force.
     
     
   • Owners with any properties designated as a Problem Property are NOT eligible.
     
     
   • No unit owned by the owner of a “Problem Property” may register a short-term rental.
     
     
   • Learn more about how “Problem Properties” are defined here.
     
     
   • The “Open Violation Count” column tells you how many open violations the unit has. Units with any open violations are NOT eligible. Violations counted include: violations of the sanitary, building, zoning, and fire code; stop work orders; and abatement orders.
     
     
   • NOTE: Violations written before 1/1/19 that are still open will make a unit NOT eligible until these violations are resolved.
     
     
   • If your unit has an open violation, visit these links to appeal your violation(s) or pay your code violation fine(s).
     
     
   • The “Violations in the Last 6 Months” column tells you how many violations the unit has received in the last six months. Units with three or more violations, whether open or closed, are NOT eligible.
     
     
   • NOTE: Only violations written on or after 1/1/19 will count against this criteria.
     
     
   • If your unit has an open violation, visit these links to appeal your violation(s) or pay your code violation fine(s).
     
     
   • How to comply with housing laws and codes:
     
     
   • Have an open violation? Visit these links to appeal your violation(s) or pay your code violation fine(s).
     
     
   • Have questions about problem properties? Visit Neighborhood Service’s Problem Properties site.
     
     

3. No violations of laws regarding short-term rental use

   • A “yes” in the “Legally Restricted” column tells you that there is a complaint against the unit that finds

     • A legal restriction that prohibits the use of the unit as a Short-Term Rental under local, state, or federal law, OR

     • legal restriction that prohibits the use of the unit as a Short-Term Rental under condominium bylaws.

     • Units with legal restrictions found upon investigation are NOT eligible.
       
       

     • If the investigation of a complaint against the unit yields restrictions of the nature detailed above, we will mark the unit with a “yes” in this column. Until such complaint-based investigations begin, all units are marked with “no.”
       
       

     • NOTE: Currently no units have a “legally restricted” designation.
       
       

4. Owner-occupied

   • A “no” in the “Unit Owner-Occupied” column tells you that there is NO Residential Tax Exemption filed for that unit via the Assessing Department, and that unit is automatically categorized as NOT eligible for the following Short-Term Rental types:

     • Home-Share
     • Limited-Share
       
       
     • Residential Tax Exemption indicates that a unit is owner-occupied and generates a “yes” in the “Unit Owner-Occupied” column.
       
       

     • Owners are not required to file a Residential Tax Exemption in order to be eligible to register a unit as a Short-Term Rental.
       
       

     • If you would like to apply for Residential Tax Exemption, you can apply here.
       
       

     • If you are the owner-occupant of a unit and you have not filed for Residential Tax Exemption, you can still register your unit by proving owner-occupancy.
       

     • It is recommended that you submit proof of residency in your short-term rental registration application to expedite the process of proving owner-occupancy (see

Graph and download economic data for Homeownership Rate (5-year estimate) for Hampshire County, MA (HOWNRATEACS025015) from 2009 to 2023 about Hampshire County, MA; Springfield; homeownership; MA; housing; 5-year; rate; and USA.

Distribution of physical activity level with socio-demographic characteristics.

Graph and download economic data for Homeownership Rate (5-year estimate) for Suffolk County, MA (HOWNRATEACS025025) from 2009 to 2023 about Suffolk County, MA; Boston; homeownership; MA; housing; 5-year; rate; and USA.

The results of the negative binomial regression for MVPA (as a dependent variable) age, BMI, and MSD.

Research suggests that individuals experiencing homelessness have high rates of overweight and obesity. Unhealthy weights and homelessness are both associated with increased risk of poor health and mortality. Using longitudinal data from 575 participants at the Toronto site of the At Home/Chez Soi randomized controlled trial, we investigate the impact of receiving a Housing First intervention on the Body Mass Index (BMI) and waist circumference of participants with moderate and high needs for mental health support services. The ANCOVA results indicate that the intervention resulted in no significant change in BMI or waist circumference from baseline to 24 months. The findings suggest a need for a better understanding of factors contributing to overweight, obesity, and high waist circumference in populations who have histories of housing precarity and experience low-income in tandem with other concerns such as mental illness and addictions.Trial RegistrationInternational Standard Randomized Control Trial Number Register ISRCTN42520374

Graph and download economic data for New Private Housing Units Authorized by Building Permits for Massachusetts (MABPPRIV) from Jan 1988 to Apr 2025 about MA, permits, buildings, new, private, housing, and USA.

Graph and download economic data for New Private Housing Structures Authorized by Building Permits for Boston-Cambridge-Newton, MA-NH (MSA) (BOST625BPPRIV) from Jan 1988 to May 2025 about Boston, NH, MA, permits, buildings, new, private, housing, and USA.

Graph and download economic data for All-Transactions House Price Index for Plymouth County, MA (ATNHPIUS25023A) from 1975 to 2024 about Plymouth County, MA; Boston; MA; HPI; housing; price index; indexes; price; and USA.