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; 5-year; housing; rate; and USA.

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; 5-year; housing; rate; and USA.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The BPDA Research Division prepared Census data on total population, population by race and ethnicity, voting-age population, group quarters populations, and housing occupancy for use in the 2022 City Council redistricting process. These data reflect 2020 census block-level data from the 2020 Decennial Census P.L. 94-171 Redistricting Data aggregated to the 275 precincts (as amended April 6, 2022) and the 9 current City Council Districts. Also included are 2010 estimates for these geographies based on 2010 census block-level.

Notes on coding of Race and Ethnicity:

The data presented here follow the conventions recommended by the Department of Justice in their September 1, 2021 guidance on the use of race and ethnicity data in redistricting. This differs from other commonly reported race and ethnicity groupings in that it groups those reporting 2 races, one White and one non-White, as being members of the non-White race reported. Thus a person reporting White and Black would be categorized here as Black. All residents of Hispanic or Latino origin, regardless of reported race, are grouped together. This coding appears on page 12 of the guidance that can be found here: https://www.justice.gov/opa/press-release/file/1429486/download

Notes on 2010 data:

For 2010 data the BPDA Research Division crosswalked 2010 census block data to 2020 boundaries using a combination of block assignment and areal interpolation based on Census Tiger shapefiles and the publicly available boundary files for Boston electoral geographies. For blocks split across 2020 boundaries the entire 2010 population was assigned to one side of the boundary if no residential structures within that block existed on the other side of the boundary. In cases where residential structures were present on both sides of the boundary, areal interpolation was used to assign the block's population and housing units based on the share of the land area of the block falling on either side of the boundary. These numbers will differ from those produced using different crosswalking methods.

Graph and download economic data for Homeownership Rate (5-year estimate) for Essex County, MA (HOWNRATEACS025009) from 2009 to 2023 about Essex County, MA; Boston; homeownership; MA; 5-year; housing; rate; and USA.

HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To Measure the social impact of these events HAZUS includes detailed demographic data for the United States. This dataset pulls out the housing and real estate data from the demographic files, at the census block level for the New Hampshire section of the Boston, MA Metropolitan Statistic Area (MSA). Data attributes for housing include owner occupied single family units, owner occupied multi-family units, renter occupied single family units, vacant single family units along with others. Demographics data was recent as of May 2006. Source: http://www.fema.gov/plan/prevent/hazus/index.shtm

Graph and download economic data for Homeownership Rate (5-year estimate) for Norfolk County, MA (HOWNRATEACS025021) from 2009 to 2023 about Norfolk County, MA; Boston; homeownership; MA; 5-year; housing; rate; and USA.

Graph and download economic data for New Private Housing Structures Authorized by Building Permits for Boston-Cambridge-Newton, MA-NH (MSA) (BOST625BPPRIVSA) from Jan 1988 to Jul 2025 about Boston, NH, MA, permits, buildings, new, private, housing, and USA.

United States PH: Authorized: Boston-Cambridge-Quincy: MA-NH data was reported at 1,463.000 Unit in Jun 2018. This records a decrease from the previous number of 2,142.000 Unit for May 2018. United States PH: Authorized: Boston-Cambridge-Quincy: MA-NH data is updated monthly, averaging 885.000 Unit from Jan 2004 (Median) to Jun 2018, with 174 observations. The data reached an all-time high of 2,142.000 Unit in May 2018 and a record low of 237.000 Unit in Jan 2009. United States PH: Authorized: Boston-Cambridge-Quincy: MA-NH data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EA012: Private Housing Units: Authorized: By Metropolitan Area.

The population density picture of Boston is generally a story of two Bostons: the high density central and northern neighborhoods, and the low density southern neighborhoods.The highest density areas of Boston are particularly concentrated in Brighton, Allston, and the Fenway area, areas of the city with large numbers of college students and young adults. There is also high population density in areas such as the Back Bay, the South End, Charlestown, the North End, and South Boston. These are all relatively small areas geographically, but have housing stock conducive to population density (e.g. multi-family dwelling units, row housing, large apartment buildings). The southern neighborhoods, specifically Hyde Park and West Roxbury, have significant numbers of people living in them, but lots sizes tend to be much larger. These areas of the city also tend to have more single family dwelling units. In that, there are fewer people per square mile than places north in the city. Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, areas of highest density exceed 30,000 persons per square kilometer. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.How to make this map for your city

Graph and download economic data for Homeownership Rate (5-year estimate) for Rockingham County, NH (HOWNRATEACS033015) from 2009 to 2023 about Rockingham County, NH; Boston; NH; homeownership; 5-year; housing; rate; and USA.

United States PH: Authorized: 1 Unit: Boston-Cambridge-Newton: MA-NH data was reported at 449.000 Unit in Jun 2018. This records a decrease from the previous number of 520.000 Unit for May 2018. United States PH: Authorized: 1 Unit: Boston-Cambridge-Newton: MA-NH data is updated monthly, averaging 408.500 Unit from Jan 2004 (Median) to Jun 2018, with 174 observations. The data reached an all-time high of 853.000 Unit in Sep 2005 and a record low of 114.000 Unit in Feb 2009. United States PH: Authorized: 1 Unit: Boston-Cambridge-Newton: MA-NH data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EA013: Private Housing Units: Authorized: By Metropolitan Area: 1 Unit.

Comprehensive demographic dataset for Mission Hill, Boston, MA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

There is more to housing affordability than the rent or mortgage you pay. Transportation costs are the second-biggest budget item for most families, but it can be difficult for people to fully factor transportation costs into decisions about where to live and work. The Location Affordability Index (LAI) is a user-friendly source of standardized data at the neighborhood (census tract) level on combined housing and transportation costs to help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest. Compare eight household profiles (see table below) —which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.*$11,880 for a single person household in 2016 according to US Dept. of Health and Human Services: https://aspe.hhs.gov/computations-2016-poverty-guidelinesThis layer is symbolized by the percentage of housing and transportation costs as a percentage of income for the Median-Income Family profile, but the costs as a percentage of income for all household profiles are listed in the pop-up:Also available is a gallery of 8 web maps (one for each household profile) all symbolized the same way for easy comparison: Median-Income Family, Very Low-Income Individual, Working Individual, Single Professional, Retired Couple, Single-Parent Family, Moderate-Income Family, and Dual-Professional Family.An accompanying story map provides side-by-side comparisons and additional context.--Variables used in HUD's calculations include 24 measures such as people per household, average number of rooms per housing unit, monthly housing costs (mortgage/rent as well as utility and maintenance expenses), average number of cars per household, median commute distance, vehicle miles traveled per year, percent of trips taken on transit, street connectivity and walkability (measured by block density), and many more.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/. There you will find some background and an FAQ page, which includes the question:"Manhattan, San Francisco, and downtown Boston are some of the most expensive places to live in the country, yet the LAI shows them as affordable for the typical regional household. Why?" These areas have some of the lowest transportation costs in the country, which helps offset the high cost of housing. The area median income (AMI) in these regions is also high, so when costs are shown as a percent of income for the typical regional household these neighborhoods appear affordable; however, they are generally unaffordable to households earning less than the AMI.Date of Coverage: 2012-2016 Date Released: March 2019Date Downloaded from HUD Open Data: 4/18/19Further Documentation:LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation

These datasets include information about Airbnb listings in the Boston area processed from data released by insideairbnb.com. Inside Airbnb produces monthly data releases about Airbnb activity for select regions internationally. This data includes listings from Inside Airbnb’s “Boston” and “Cambridge” releases. AIRBNB.Listing is a listing-level file that contains information about the rental properties listed on Airbnb. Listing data has been aggregated across census tracts to generate AIRBNB.CT, which includes ecometrics that describe neighborhoods in terms of listing frequency and pricing .

These datasets include information about housing listings on Craigslist for the state of Massachusetts processed from data scraped by BARI. This release includes listings for all five Massachusetts regions designated by Craigslist (Boston, Cape Cod, South Coast, Western Mass, and Worcester). CRAIGSLIST.Listings is a listing-level file that contains information about housing listings posted on Craigslist. Listing data has been aggregated across census tracts to generate CRAIGSLIST.CT, which includes ecometrics that describe neighborhoods in terms of listing frequency and property value.

Graph and download economic data for Homeownership Rate (5-year estimate) for Plymouth County, MA (HOWNRATEACS025023) from 2009 to 2023 about Plymouth County, MA; Boston; homeownership; MA; 5-year; housing; rate; and USA.

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

Graph and download economic data for Homeownership Rate (5-year estimate) for Strafford County, NH (HOWNRATEACS033017) from 2009 to 2023 about Strafford County, NH; Boston; NH; homeownership; 5-year; housing; rate; and USA.