The dataset titled "Overview of affordable housing indicators" is a comprehensive resource that provides insights into the affordability of housing across OECD member countries. The data spans from 2010 to 2020 and is updated annually. The dataset, published by the Organisation for Economic Co-operation and Development (OECD) on May 27, 2021, is available in PDF format and can be accessed openly. However, the OECD restricts the posting of its material on the internet, although linking, sharing, and embedding are permitted. The dataset does not contain data about individuals or identifiable individuals. The metadata for this dataset was created on November 15, 2023, and last modified on April 8, 2025. The dataset provides a range of economic indicators related to housing affordability, including house-price-to-income and housing-expenditure-to-income ratio measures. It also includes more data-intensive indicators such as residual income measures, which focus on the income households have left after paying for housing. The dataset is tagged with keywords such as Affordability, Affordable Housing, Economic Indicators, Expenditure, Housing Potential, Income, and Indicator. The dataset is owned by the OECD, and they can be contacted via telephone or fax for any queries. The dataset is available in English and the description of the dataset is provided. The dataset's source and location are provided, but the license is not specified.

The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building.This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by County Date of Coverage: 2016-2020

The Location Affordability Index (LAI) estimates the percentage of a family’s income dedicated to the combined cost of housing and transportation in a given location. Because what is “affordable” is different for everyone, users can choose among a diverse set of family profiles—which vary by household income, size, and number of commuters—and see the affordability landscape for each in a given neighborhood, city, or region. The Location Affordability Index (LAI) estimates three dependent variables of transportation behavior (auto ownership, auto use, and transit use) as functions of 14 independent variables (median income, per capita income, average household size, average commuters per household, residential density, gross density, block density, intersection density, transit connectivity, transit frequency of service, transit access shed, employment access, job diversity, and average commute distance). To hone in on the built environment’s influence on transportation costs, the independent household variables (income, household size, and commuters per household) are set at fixed values to control for any variation they might cause. The LAI also estimates two dependent variables of housing costs (Selected Monthly Owner Costs and Gross Rent) as functions of 16 independent variables: regional median selected monthly owner costs and regional median gross rent in addition to the 14 variables used in the transportation model.

To learn more about the Location Affordability Index (v.1.0) visit: https://www.locationaffordability.info/LAPMethods.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Location Affordability Indev v.1.0. Date of Coverage: 2005-2009 https://www.locationaffordability.info/LAPMethodsV2.pdf

The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building. This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by Tract Date of Coverage: 2016-2020

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

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Affordability ratios calculated by dividing house prices by gross annual workplace-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

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Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Affordability ratios calculated by dividing house prices by gross annual workplace-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

The Affordable Housing Inventory is a statewide resource for anyone seeking affordable housing information in Oregon. The Oregon Health Authority (OHA) is not the originator of this information. The inventory has been assembled from a variety of various industry databases that are intended to provide information on affordable and subsidized housing in Oregon. OHA makes no warranties or guarantees about the accuracy or effectiveness of the information in the housing inventory. OHA will continue to assess data quantity and quality, making corrections as needed or warranted. Information regarding changes to the information in this inventory may be submitted to affordablehousing.inventory@dhsoha.state.or.us.

The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building. This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by State Date of Coverage: 2016-2020

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

The dataset comes from CouncilStat, which is used by many NYC Council district offices to enter and track constituent cases that can range from issues around affordable housing, to potholes and pedestrian safety. This dataset aggregates the information that individual staff have input. However, district staffs handle a wide range of complex issues. Each offices uses the program differently, and thus records cases, differently and so comparisons between accounts may be difficult. Not all offices use the program. For more info - http://labs.council.nyc/districts/data/

LOW TRANSPORTATION COST INDEXSummaryThe Low Transportation Cost Index is based on estimates of transportation expenses for a family that meets the following description: a 3-person single-parent family with income at 50% of the median income for renters for the region (i.e. CBSA). The estimates come from the Location Affordability Index (LAI). The data correspond to those for household type 6 (hh_type6_) as noted in the LAI data dictionary. More specifically, among this household type, we model transportation costs as a percent of income for renters (t_rent). Neighborhoods are defined as census tracts. The LAI data do not contain transportation cost information for Puerto Rico.InterpretationValues are inverted and percentile ranked nationally, with values ranging from 0 to 100. The higher the transportation cost index, the lower the cost of transportation in that neighborhood. Transportation costs may be low for a range of reasons, including greater access to public transportation and the density of homes, services, and jobs in the neighborhood and surrounding community.

Data Source: Location Affordability Index (LAI) data, 2012-2016.Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 11.

References: www.locationaffordability.infohttps://lai.locationaffordability.info//lai_data_dictionary.pdf

To learn more about the Low Transportation Cost Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This database was created to accompany a report prepared by Joe Daniels, PhD, and Martine August, PhD, entitled “Acquisitions Programs for Affordable Housing: Creating non-market supply and preserving affordability with existing multi-family housing.” The database and report form part of the work performed under the HART project, and the report can be found at HART’s website: HART.ubc.ca. The database is a single table that summarizes 11 key elements, plus notes and references, of a growing list of policies from governments across the world. There are currently 108 policies included in the database. The authors expect to update this database with additional policies from time to time. The authors hope this database will serve as a resource for governments looking to become familiar with a variety of policies in order to help them evaluate what policies might be most applicable in their communities. Data Fields: List of data fields (15 total): 1. Government Order 2. Government Jurisdiction 3. Policy Name/Action 4. Acquisition Target 5. Years Active 6. Funder/Funding 7. Funding Amount (Program) 8. Funding Form 9. Affordability Standard 10. Affordability Term 11. Features/Requirements 12. Comments 13. Reference link 1 14. Reference link 2 15. Reference link 3 Description of data fields (15) 1. Government Order: - Categorizes the relative political authority in terms of one of three categories: Municipal (responsible for a city or small region), Provincial (responsible for multiple municipalities), or Country (responsible for multiple provinces; highest political authority). - This field may be used to help identify those policies most relevant to the reader. 2. Government Jurisdiction: - Indicates the name of the government. - For example, a country might be named “Canada,” a province might be named “Quebec,” and a municipality might be named “Calgary.” 3. Policy Name/Action: - Indicates the name of the policy. - This generally serves as the unique identifier for the record. However, there may be some programs that are only known by a common term; for example, “Right of First Refusal.” 4. Acquisition Target: - Describes the type of housing asset that the policy is concerned with. For example, acquiring land, acquiring existing rental buildings, renovating existing supportive housing. 5. Years Active: - The time period that the policy has been active. - Typically formatted as “[Year started] - [Year ended]”. If just a single year is listed (e.g. “2009”) that means the policy was only active that one year. - If the policy is active with no end date, then the format will be “[Year started] - ongoing.” If the policy has a specified end date in the future, that year will be listed instead: “[Year started] – [Expected final year].” 6. Funder/Funding: - The government, government agency, or organization responsible for the use of those funds made available through the policy. 7. Funding Amount (Program): - The dollar value of funds connected to the policy. - Sometimes this is the total value of funds available to the policy, and sometimes it is the actual value of funds that were used. - The funds indicated here do not necessarily correspond to the time period indicated in the ‘Years Active’ field. Additional detail will be added to clarify whenever possible. - If policy has “N/A” listed here, see ‘Features/Requirements’ for more information. 8. Funding Form: - Indicates the type of financial tools available to the policy. For example, “capital funding,” “forgivable loans,” or “rent supplements.” - If policy has “N/A” listed here, see ‘Features/Requirements’ for more information. 9. Affordability Standard: - Indicates whether the policy includes an explicit standard or benchmark of affordability that is used to guide or otherwise inform the policy’s goals. 10. Affordability Term: - Indicates whether the affordability standard applies to a specific time period. - This field may also contain other information on time periods that are relevant to the policy; for example, an operating loan guaranteed to be active for a specific number of years. 11. Features/Requirements: - Describes the broad objectives of the policy as well as any specific guidelines that the policy must follow. 12. Comments: - Author’s commentary on the policy. 13. Reference link 1: - A web address (URL) or citation indicating the source of the details on the policy. 14. Reference link 2: - A second web address (URL) or citation indicating the source of the details on the policy. 15. Reference link 3: - A third web address (URL) or citation indicating the source of the details on the policy. File list (1): 1. Property Acquisition Policy Database.xlsx

Analysis of ‘Affordable Housing Inventory’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/59b3e47f-b84a-43b9-af65-8ce173a3f83e on 26 January 2022.

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

The Affordable Housing Inventory is a statewide resource for anyone seeking affordable housing information in Oregon. The Oregon Health Authority (OHA) is not the originator of this information. The inventory has been assembled from a variety of industry databases that are intended to provide information on affordable and subsidized housing in Oregon. OHA makes no warranties or guarantees about the accuracy or effectiveness of the information in the housing inventory. OHA will continue to assess data quantity and quality, making corrections as needed or warranted. Information regarding changes to the information in this inventory may be submitted to affordablehousing.inventory@dhsoha.state.or.us.

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

Explore our extensive sneaker products dataset, featuring a wide range of stylish and affordable sneakers.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Housing Index in the United States decreased to 434.40 points in May from 435.10 points in April of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.