Housing Starts Multi Family in the United States decreased to 316 Thousand units in May from 454 Thousand units in April of 2025. This dataset includes a chart with historical data for the United States Housing Starts Multi Family.

This dataset contains existing multifamily rental sites in the City of Detroit with housing units that have been preserved as affordable since 2018 with assistance from the public sector.Over time, affordable units are at risk of falling off line, either due to obsolescence or conversion to market-rate rents. This dataset contains occupied multifamily rental housing sites (typically 5+ units) in the City of Detroit, including those that have units that have been preserved as affordable since 2015 through public funding, regulatory agreements, and other means of assistance from the public sector. Data are collected from developers, other governmental departments and agencies, and proprietary data sources by various teams within the Housing and Revitalization Department, led by the Preservation Team. Data have been tracked since 2018 in service of citywide housing preservation goals. This reflects HRD's current knowledge of multifamily units in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

This dataset contains multifamily affordable and market-rate housing sites (typically 5+ units) in the City of Detroit that have been built or rehabbed since 2015, or are currently under construction. Most sites are rental housing, though some are for sale. The data are collected from developers, other government departments and agencies, and proprietary data sources in order to track new multifamily and affordable housing construction and rehabilitation occurring in throughout the city, in service of the City's multifamily affordable housing goals. Data are compiled by various teams within the Housing and Revitalization Department (HRD), led by the Preservation Team. This dataset reflects HRD's current knowledge of multifamily units under construction in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

This dataset contains existing multifamily rental sites in the City of Detroit with housing units that have been preserved as affordable since 2018 with assistance from the public sector.Over time, affordable units are at risk of falling off line, either due to obsolescence or conversion to market-rate rents. This dataset contains occupied multifamily rental housing sites (typically 5+ units) in the City of Detroit, including those that have units that have been preserved as affordable since 2015 through public funding, regulatory agreements, and other means of assistance from the public sector. Data are collected from developers, other governmental departments and agencies, and proprietary data sources by various teams within the Housing and Revitalization Department, led by the Preservation Team. Data have been tracked since 2018 in service of citywide housing preservation goals. This reflects HRD's current knowledge of multifamily units in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

What is Rental Data?

Rental data encompasses detailed information about residential rental properties, including single-family homes, multifamily units, and large apartment complexes. This data often includes key metrics such as rental prices, occupancy rates, property amenities, and detailed property descriptions. Advanced rental datasets integrate listings directly sourced from property management software systems, ensuring real-time accuracy and eliminating reliance on outdated or scraped information.

Additional Rental Data Details

The rental data is sourced from over 20,000 property managers via direct feeds and property management platforms, covering over 30 percent of the national rental housing market for diverse and broad representation. Real-time updates ensure data remains current, while verified listings enhance accuracy, avoiding errors typical of survey-based or scraped datasets. The dataset includes 14+ million rental units with detailed descriptions, rich photography, and amenities, offering address-level granularity for precise market analysis. Its extensive coverage of small multifamily and single-family rentals sets it apart from competitors focused on premium multifamily properties.

Rental Data Includes:

• Property Types
• Single-Family Rentals
• Small Multi-family Units
• Premium Apartments
• 16,000+ ZIP Codes
• 800+ MSAs
• Pricing Trends
• Lease Terms Amenities

Displacement risk indicator classifying census tracts according to apartment rent prices in census tracts. We classify apartment rent along two dimensions:The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development

This dataset contains property sales data, including information such as PropertyID, property type (e.g., Commercial or Residential), tax keys, property addresses, architectural styles, exterior wall materials, number of stories, year built, room counts, finished square footage, units (e.g., apartments), bedroom and bathroom counts, lot sizes, sale dates, and sale prices. Explore this dataset to gain insights into real estate trends and property characteristics.

Data.milwaukee.gov, (2023). Property Sales Data. [online] Available at: https://data.milwaukee.gov [Accessed 9th October 2023].

Open Definition. (n.d.). Creative Commons Attribution 4.0 International Public License (CC BY 4.0). [online] Available at: http://www.opendefinition.org/licenses/cc-by [Accessed 9th October 2023].

The Maryland Department of Housing and Community Development offers multifamily finance programs for the construction and rehabilitation of affordable rental housing units for low to moderate income families, senior citizens and individuals with disabilities. Our multifamily bond programs issues tax-exempt and taxable revenue mortgage bonds to finance the acquisition, preservation and creation of affordable multifamily rental housing units in priority funding areas. By advocating for increased production of rental housing units, we help create much-needed jobs and leverage opportunities to live, work and prosper for hardworking Maryland families, senior citizens, and individuals with disabilities throughout the state.​ DISCLAIMER: Some of the information may be tied to the Department’s bond funded loan programs and should not be relied upon in making an investment decision. The Department provides comprehensive quarterly and annual financial information and operating data regarding its bonds and bond funded loan programs, all of which is posted on the publicly-accessible Electronic Municipal Market Access system website (commonly known as EMMA) that is maintained by the Municipal Securities Rulemaking Board, and on the Department’s website under Investor Information. More information accessible here: http://dhcd.maryland.gov/Investors/Pages/default.aspx

The U.S. Department of Energys Zero Energy Ready Home (ZERH) recognition program builds upon the building science requirements of ENERGY STAR Certified Homes, Version 3 and best practices tested by the Building America research and demonstration program. Multifamily units (units in buildings with five or more apartments) comprise an increasingly important segment in the U.S. new housing market. Over the past 30 years, this segment has averaged 24% of residential building permits and since the recession in 2008 averages 34% of new residential building permits. This study analyses two multifamily homes, one townhouse and one apartment. The study looks to improve the efficiency of these homes to meet ENERGY STAR standards.

Apartment - 2 bedroom apartment unit Townhome - 3 bedroom townhome unit

VITAL SIGNS INDICATOR List Rents (EC9)

FULL MEASURE NAME List Rents

LAST UPDATED October 2016

DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

DATA SOURCE real Answers (1994 – 2015) no link

Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

Inflation-adjusted data are presented to illustrate how rents have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

This dataset contains income restricted housing units across the 4-county PSRC region (King, Kitsap, Pierce, and Snohomish Counties). They are summarized here by county, and then grouped into various AMI (area median income) bands. A breakdown of unit size by number of bedrooms is also included. This dataset was updated May 1, 2025 to capture improvements in the geographic placement of properties, and corrections to the unit counts for some properties in Snohomish CountyAll jurisdictions within the 4-county PSRC region are included, even those with zero income restricted units. Note that while we attempt to capture all income restricted units in the region, the IRHD (Income Restricted Housing Database) is not an exhaustive list. Some properties also include units that are not income restricted - it was not always possible to disaggregate these units. For example, the bedroom size data includes some market rate units. Where the data was available in King County, units created through various incentive programs were included, such as IZ (incentive zoning), MHA (Mandatory Housing Affordability) and MFTE (Multi Family Tax Exemption) units. Units created under these programs across the region are undercounted due to data availability.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Multifamily Performance Program (MPP) serves residential buildings with five or more units. Funds are targeted at energy efficiency measures that help to reduce on-site electricity, oil, natural gas, steam, and propane energy demand and energy consumption in multi-unit residential buildings. All buildings receive program support for energy assessments to identify and determine cost-effective measures, expected energy savings, and installation costs. Our dataset is then compiled from the information. The dataset includes information collected throughout the project application process and energy assessments from several NYSERDA-funded programs, including Multifamily Performance Program-Existing Buildings, Multifamily Performance Program-New Construction, and Multifamily Performance Program-Energy Star Pilot. The Multifamily Residential Existing and New Construction Energy Efficiency Projects Reported by NYSERDA: Beginning 2005 dataset includes the following data points for completed projects: Project Name, Program Type, Building Address1, Building City, Building ZIP, Property County, Electric Utility, Gas Utility, Market Type, Number of Buildings, Number of Units, Application NYSERDA Approved Date, Project Completed Date, Funding Amount, Proposed Install Unit Cost, Total Estimated Electric Savings, Total Estimated Annual Energy Savings, and Total Estimated Electric Demand Reduction (MW). Information about the Projects’ measures, measure category, and estimated energy savings by fuel type can be found in the Multifamily Residential Existing and New Construction Energy Efficiency Measures Reported by NYSERDA: Beginning 2005 dataset. Reported savings account for interactive effects between measures.

The Multifamily Performance Program (MPP) serves residential buildings with five or more units. Funds are targeted at energy efficiency measures that help to reduce on-site electricity, oil, natural gas, steam, and propane energy demand and energy consumption in multi-unit residential buildings. All buildings receive program support for energy assessments to determine cost-effective measures, expected energy savings, and installation costs. The dataset includes information collected throughout the project application process and energy assessments from several NYSERDA-funded programs, including Multifamily Performance Program-Existing Buildings, Multifamily Performance Program-New Construction, and Multifamily Performance Program-Energy Star Pilot.

Information about the Projects’ location, utility, market type, number of buildings and units, and funding amount can be found in the Multifamily Residential Existing and New Construction Energy Efficiency Projects Reported by NYSERDA: Beginning 2005 dataset.

Reported measure savings account for interactive effects between measures.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

Analysis of ‘Multifamily Residential Existing and New Construction Energy Efficiency Measures Reported By NYSERDA: Beginning 2005’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/2fc534e0-f13e-4d34-a3db-318cc3acb69c on 12 February 2022.

--- Dataset description provided by original source is as follows ---

The Multifamily Performance Program (MPP) serves residential buildings with five or more units. Funds are targeted at energy efficiency measures that help to reduce on-site electricity, oil, natural gas, steam, and propane energy demand and energy consumption in multi-unit residential buildings. All buildings receive program support for energy assessments to determine cost-effective measures, expected energy savings, and installation costs. The dataset includes information collected throughout the project application process and energy assessments from several NYSERDA-funded programs, including Multifamily Performance Program-Existing Buildings, Multifamily Performance Program-New Construction, and Multifamily Performance Program-Energy Star Pilot.

Information about the Projects’ location, utility, market type, number of buildings and units, and funding amount can be found in the Multifamily Residential Existing and New Construction Energy Efficiency Projects Reported by NYSERDA: Beginning 2005 dataset.

Reported measure savings account for interactive effects between measures.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

--- Original source retains full ownership of the source dataset ---

Note: Vacancy rate calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.

Analysis of ‘ Zillow Housing Aspirations Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/zillow-housing-aspirations-reporte on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

Additional Data Products

Product: Zillow Housing Aspirations Report

Date: April 2017

Definitions

Home Types and Housing Stock

• All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.
• Condo/Co-op: Condominium and co-operative homes.
• Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.
• Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Additional Data Products

• Zillow Home Value Forecast (ZHVF): The ZHVF is the one-year forecast of the ZHVI. Our forecast methodology is methodology post.
• Zillow creates our negative equity data using our own data in conjunction with data received through our partnership with TransUnion, a leading credit bureau. We match estimated home values against actual outstanding home-related debt amounts provided by TransUnion. To read more about how we calculate our negative equity metrics, please see our here.
• Cash Buyers: The share of homes in a given area purchased without financing/in cash. To read about how we calculate our cash buyer data, please see our research brief.
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio, Historical ZHVI, Historical ZHVI and Houshold Income are calculated as a part of Zillow’s quarterly Affordability Indices. To calculate mortgage affordability, we first calculate the mortgage payment for the median-valued home in a metropolitan area by using the metro-level Zillow Home Value Index for a given quarter and the 30-year fixed mortgage interest rate during that time period, provided by the Freddie Mac Primary Mortgage Market Survey (based on a 20 percent down payment). Then, we consider what portion of the monthly median household income (U.S. Census) goes toward this monthly mortgage payment. Median household income is available with a lag. For quarters where median income is not available from the U.S. Census Bureau, we calculate future quarters of median household income by estimating it using the Bureau of Labor Statistics’ Employment Cost Index. The affordability forecast is calculated similarly to the current affordability index but uses the one year Zillow Home Value Forecast instead of the current Zillow Home Value Index and a specified interest rate in lieu of PMMS. It also assumes a 20 percent down payment. We calculate rent affordability similarly to mortgage affordability; however we use the Zillow Rent Index, which tracks the monthly median rent in particular geographical regions, to capture rental prices. Rents are chained back in time by using U.S. Census Bureau American Community Survey data from 2006 to the start of the Zillow Rent Index, and Decennial Census for all other years.
• The mortgage rate series is the average mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate mortgage in 15-minute increments during business hours, 6:00 AM to 5:00 PM Pacific. It does not include quotes for jumbo loans, FHA loans, VA loans, loans with mortgage insurance or quotes to consumers with credit scores below 720. Federal holidays are excluded. The jumbo mortgage rate series is the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours, 6:00 AM to 5:00 PM Pacific Time. It does not include quotes to consumers with credit scores below 720. Traditional federal holidays and hours with insufficient sample sizes are excluded.

About Zillow Data (and Terms of Use Information)

• Zillow is in the process of transitioning some data sources with the goal of producing published data that is more comprehensive, reliable, accurate and timely. As this new data is incorporated, the publication of select metrics may be delayed or temporarily suspended. We look forward to resuming our usual publication schedule for all of our established datasets as soon as possible, and we apologize for any inconvenience. Thank you for your patience and understanding.
• All data accessed and downloaded from this page is free for public use by consumers, media, analysts, academics etc., consistent with our published Terms of Use. Proper and clear attribution of all data to Zillow is required.
• For other data requests or inquiries for Zillow Real Estate Research, contact us here.
• All files are time series unless noted otherwise.
• To download all Zillow metrics for specific levels of geography, click here.
• To download a crosswalk between Zillow regions and federally defined regions for counties and metro areas, click here.
• Unless otherwise noted, all series cover single-family residences, condominiums and co-op homes only.

Source: https://www.zillow.com/research/data/

This dataset was created by Zillow Data and contains around 200 samples along with Unnamed: 1, Unnamed: 0, technical information and other features such as: - Unnamed: 1 - Unnamed: 0 - and more.

How to use this dataset

• Analyze Unnamed: 1 in relation to Unnamed: 0
• Study the influence of Unnamed: 1 on Unnamed: 0
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Zillow Data

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

This dataset is an authoritative inventory of new housing units constructed in the City of Saint Paul from 2010 through the end of Q1 2025. The data originates from two sources: the City's permitting system, and from the City's records on housing affordability. The dataset helps provide a deeper understanding of trends in market rate and affordable housing production. This dataset is updated quarterly, generally by the 15th of the month following the end of each quarter.For the purposes of this dataset, the delineation of "affordable units" is tied to the construction of the new units: does the project — its development financing or the regulatory framework under which it was built — require units be affordable upon the completion of construction?
This definition of affordability does not include units that are affordable only because of a post-construction subsidy or other similar subsequent commitment to affordability, such as through the city's Rental Rehab Loan Program or 4d Affordable Housing Incentive Program. It does, however, include units that are affordable under the terms of zoning district-based density bonuses for affordability. Projects built under a zoning-based density bonus currently comprise a very small portion of the larger total, and are identified in the Notes column of the associated table.This dataset will be updated quarterly, given the manual work currently involved in bringing it up-to-date. It is the product of work over five years across three City departments.Field definitions are available below. In addition to being available for download through the Open Information website, this data is perhaps more easily accessible in an interactive Housing Production Dashboard.This data is designed under a methodology specific to the City of Saint Paul. Other government entities use the same originating permit data, but somewhat divergent methodologies, which can produce very different results. We believe this particular methodology gives the fullest and most timely depiction of housing production available. For specific details, see the "Methodologies Compared" tab at the bottom of the Housing Production Dashboard.Technical detailsThis dataset is generally designed to have one record (row) per building project that creates new units. A project may be the result of one or more building permits. In cases when a project contains both subsidized / affordable and unsubsidized / market rate units, the project is split across two records (rows).

Fields (Columns) Defined

PropertyRSN: An internal unique identifier for the address point with which the permit is associated.

Property Address: The street address at which the permit work took place.

ParcelID: The county-assigned unique identifier for the parcel on which the permit work took place.

Type of Work: The kind of work undertaken at the site. CHOICES: New · Addition · Remodel

Residence Type: What is the physical form of the dwelling units that were created under this building permit? CHOICES: 2-Family/Duplex · Mixed (Commercial/Residential) · Residential (Multi-Fam) · Single Family DwellingDwelling Unit Type: The type of financial structure tied to the new dwelling units created under this permit. CHOICES:Market Rate Unit: Units that did not receive some sort of direct public subsidy or assistance outside normal market sources.Affordable Unit: Units that contractually ensure affordability / access for those in need, at the level of 80% of Area Median Income (AMI) and below. This definition does include units that are affordable under the terms of zoning-based density bonuses, which comprise a very small portion of the overall total. This demarcation of affordable units does not include units that received financial assistance in preparing the site for redevelopment, for activities such as pollution remediation. Further, the affordability included here are only those contractually included at the closing of the development financing of the project, and does not include units restricted as affordable at a later date, such as through the City's 4(d) Affordable Housing Incentive Program, or the Rental Rehab Loan Program.

Commercial to Housing Conversion: The units shown were produced by converting formerly commercial space (including retail, commercial, institutional and industrial type uses) into residential space (including single family, duplex, 3-4 unit, multifamily and congregate-type residential uses). CHOICES:Yes: The housing units shown were converted from commercial space.No: The housing units shown were not converted from commercial space.Project Permit Issue Date: The date the first permit was issued for the project that created the new dwelling units.

Project Permit Issue Year: The year the first permit was issued for the project that created the new dwelling units.

Existing Dwelling Units: The number of dwelling units that existed just prior to the start of the project under the definition of "dwelling unit" in the International Building Code.

New Dwelling Units: The number of new dwelling units created under the building permit(s) under the definition of "dwelling unit" in the International Building Code.

Total Final Dwelling Units: The number of dwelling units existing upon completion of the associated building permit(s), under the definition of "dwelling unit" in the International Building Code.

Notes: This field contains notes on specific unique circumstances. In particular, a few building permits produced both subsidized / affordable and unsubsidized / market rate dwelling units. To make building permits in this scenario function as needed within data systems, we split such permits into two lines, one for each type of unit, and made a notation in this field to reflect that division.

This dataset contains income restricted housing units across the 4-county PSRC region (King, Kitsap, Pierce, and Snohomish Counties). They are summarized here by county, and then grouped into various AMI (area median income) bands. A breakdown of unit size by number of bedrooms is also included. This dataset was updated May 1, 2025 to capture improvements in the geographic placement of properties, and corrections to the unit counts for some properties in Snohomish CountyAll jurisdictions within the 4-county PSRC region are included, even those with zero income restricted units. Note that while we attempt to capture all income restricted units in the region, the IRHD (Income Restricted Housing Database) is not an exhaustive list. Some properties also include units that are not income restricted - it was not always possible to disaggregate these units. For example, the bedroom size data includes some market rate units. Where the data was available in King County, units created through various incentive programs were included, such as IZ (incentive zoning), MHA (Mandatory Housing Affordability) and MFTE (Multi Family Tax Exemption) units. Units created under these programs across the region are undercounted due to data availability.

Displacement risk indicator classifying community reporting areas according to apartment vacancy rates. Vacancy rates are calculated at the Community Reporting Area level, which are a combination of one or more census tracts. We visualize them as census tracts here, but columns should not be summed to make a total. We include both vacancy rates and change in year over year vacancy rates.

This dataset contains income restricted housing units across the 4-county PSRC region (King, Kitsap, Pierce, and Snohomish Counties). They are summarized here by jurisdiction then by county, and then grouped into various AMI (area median income) bands. A breakdown of unit size by number of bedrooms is also included. This dataset was updated May 1, 2025 to capture improvements in the geographic placement of properties, and corrections to the unit counts for some properties in Snohomish CountyAll jurisdictions within the 4-county PSRC region are included, even those with zero income restricted units. Note that while we attempt to capture all income restricted units in the region, the IRHD (Income Restricted Housing Database) is not an exhaustive list. Some properties also include units that are not income restricted - it was not always possible to disaggregate these units. For example, the bedroom size data includes some market rate units. Where the data was available in King County, units created through various incentive programs were included, such as IZ (incentive zoning), MHA (Mandatory Housing Affordability) and MFTE (Multi Family Tax Exemption) units. Units created under these programs across the region are undercounted due to data availability.