This table includes figures on the average increase of rent broken down by income class. A distinction is made here between rental of regulated dwellings by social and other landlords and liberalised rental.

Data available from: 2015.

Status of the figures: The figures in this table are definitive.

Changes as of 20 May 2025: The figures broken down by income class have been removed from this table for the categories of liberalised rents and total. These figures are not applicable and were previously published in error. Landlords can only request income data for regulated rents, which form the basis for this table.

Changes as of 4 September 2024: The figures of 2024 have been published.

Changes as of 8 September 2023: The category 'middle income' has been added to the table.

When will new figures be published? New figures of 2025 will become available in September 2025.

This dataset contains information about the percent of income households spend on rent in cities in San Mateo County. This data is for renters only, not those who live in owner-occupied homes with or without a mortgage. This data was extracted from the United States Census Bureau's American Community Survey 2014 5 year estimates.

Price to Rent Ratio in the United States increased to 134.20 in the fourth quarter of 2024 from 133.60 in the third quarter of 2024. This dataset includes a chart with historical data for the United States Price to Rent Ratio.

Chart and data created/acquired for the La Crosse County Comprehensive Plan 2022 from the American Community Survey.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

The feature set indicates the locations, and tenant characteristics of public housing development buildings for the San Francisco Bay Region. This feature set, extracted by the Metropolitan Transportation Commission, is from the statewide public housing buildings feature layer provided by the California Department of Housing and Community Development (HCD). HCD itself extracted the California data from the United States Department of Housing and Urban Development (HUD) feature service depicting the location of individual buildings within public housing units throughout the United States.

According to HUD's Public Housing Program, "Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by some 3,300 housing agencies. HUD administers federal aid to local housing agencies that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments.

HUD administers Federal aid to local Housing Agencies (HAs) that manage housing for low-income residents at rents they can afford. Likewise, HUD furnishes technical and professional assistance in planning, developing, and managing the buildings that comprise low-income housing developments. This feature set provides the location, and resident characteristics of public housing development buildings.

Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes:

‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) 
‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) 
‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) 
‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) 
‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) 
 ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) 
‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) 
Null - Could not be geocoded (does not appear on the map) 

For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information, the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10.

HCD downloaded the HUD data in April 2021. They sourced the data from https://hub.arcgis.com/datasets/fedmaps::public-housing-buildings.

To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/.

Housing Affordability Supply and Demand Data. Number of South Australian households paying more than 25% of their household income on housing (rent or mortgage) broken down by very low, low and moderate income brackets. This dataset relates to section 4, Housing Stress, of the Affordability master reports produced by the SA Housing Authority. Each master report covers one Local Government Area and is entitled ‘Housing Affordability – Demand and Supply by Local Government Area’. The Demand for Supply for LGA reports are available online at: https://data.sa.gov.au/data/dataset/housing-affordability-demand-and-supply-by-local-government-area Explanatory Notes: Data sourced from the Australian Bureau of Statistics (ABS), Census for Population and Housing and it is updated every 5 years in line with the ABS Census. The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Census housing stress data is best used in comparing results over Censuses (ie did it increase or decrease in an area) rather than using it to ascertain what proportion of households were in rental stress. Income bands are based on household income. High income households can also experience rental stress. These households are included in the total but not identified separately. Data is representative of households in very low, low and moderate income brackets. Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

Percentage of total monthly household income spent on private rent, by country and by regions of England, financial years ending 2013 to 2023.

Philippines PTE: House Rent data was reported at 12.200 % in 2015. Philippines PTE: House Rent data is updated yearly, averaging 12.200 % from Dec 2015 (Median) to 2015, with 1 observations. Philippines PTE: House Rent data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Chart and data created/acquired for the La Crosse County Comprehensive Plan 2022 from the American Community Survey.

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of lessors of residential buildings and dwellings (except social housing projects) (NAICS 531111), annual, for five years of data.

Price to Rent Ratio in the United Kingdom increased to 113.72 in the first quarter of 2025 from 113.62 in the fourth quarter of 2024. This dataset includes a chart with historical data for the United Kingdom Price to Rent Ratio.

This table contains 14 series, with data for years 1926 - 1990 (not all combinations necessarily have data for all years), and was last released on 2000-02-19. This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Nova Scotia; Prince Edward Island ...), Net income (1 items: Net income of non-farm unincorporated business including rent ...).

This table contains 516 series, with data for years 1996 - 1996 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (173 items: Canada; Newfoundland and Labrador; Health and Community Services St. John's Region, Newfoundland and Labrador; Health and Community Services Eastern Region, Newfoundland and Labrador; ...);  Occupancy status (3 items: Total, households; Renters; Owners).

Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by over 3,300 housing agencies (HAs). HUD administers Federal aid to local housing agencies (HAs) that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Public Housing Authorities Date Updated: Q1 2025

This table contains 5 series, with data for years 1997 - 2012 (not all combinations necessarily have data for all years), and was last released on 2015-07-14. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), North American Industry Classification System (NAICS) (1 items: Automotive equipment rental and leasing ...), Summary statistics (5 items: Operating revenue; Operating profit margin; Operating expenses; Salaries; wages and benefits ...).

Table from the American Community Survey (ACS) 5-year series on housing tenure and cost related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B25003 Tenure of Occupied Housing Units, B25070 Gross Rent as a Percentage of Household Income in the Past 12 Months, B25063 Gross Rent, B25091 Mortgage Status by Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months, B25087 Mortgage Stauts and Selected Monthly Owner Costs, B25064 Median Gross Rent, B25088 Median Selected Monthly Owner Costs by Mortgage Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B25003, B25070, B25063, B25091, B25087, B25064, B25088Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACS<a href='https://www.census.gov/programs-surveys/acs/technical-documentation.html' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit;' target='