Rent Inflation in the United States decreased to 3.60 percent in August from 3.70 percent in July of 2025. This dataset includes a chart with historical data for the United States Rent Inflation.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in U.S. City Average (CUUR0000SEHA) from Dec 1914 to Aug 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

Rent Inflation in the United Kingdom decreased to 4.40 percent in August from 4.50 percent in July of 2025. This dataset includes a chart with historical data for the United Kingdom Rent Inflation.

This table contains data described by the following dimensions (Not all combinations are available): Geography (247 items: Carbonear; Newfoundland and Labrador; Corner Brook; Newfoundland and Labrador; Grand Falls-Windsor; Newfoundland and Labrador; Gander; Newfoundland and Labrador ...), Type of structure (4 items: Apartment structures of three units and over; Apartment structures of six units and over; Row and apartment structures of three units and over; Row structures of three units and over ...), Type of unit (4 items: Two bedroom units; Three bedroom units; One bedroom units; Bachelor units ...).

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.

Median monthly rental prices for the private rental market in England by bedroom category, region and administrative area, calculated using data from the Valuation Office Agency and Office for National Statistics.

This dataset provides values for RENT INFLATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Commercial rents services price index (CRSPI) by North American Industry Classification System (NAICS). Monthly data are available from January 2006 for the total index and from January 2019 for all other indexes. The table presents data for the most recent reference period and the last five periods. The base period for the index is (2019=100).

Where is the data from?

The data was scraped from Immoscout24, the biggest real estate platform in Germany. Immoscout24 has listings for both rental properties and homes for sale, however, the data only contains offers for rental properties. The scraping process is described in this blog post and the corresponding code for scraping and minimal processing afterwards can be found in this Github repo. At a given time, all available offers were scraped from the site and saved. This process was repeated three times, so the data set contains offers from the dates 2018-09-22, 2019-05-10 and 2019-10-08.

Content

The data set contains most of the important properties, such as living area size, the rent, both base rent as well as total rent (if applicable), the location (street and house number, if available, ZIP code and state), type of energy etc. It also has two variables containing longer free text descriptions: description with a text describing the offer and facilities describing all available facilities, newest renovation etc. The date column was added to give the time of scraping.

Inspiration

Did rents increase over time? Which areas are the most expensive? Which areas saw the largest increase, which areas became cheaper? Are there any duplicates? How many? What could be gained from a text analysis of the free text variables?

Acknowledgements

The data belongs to www.immobilienscount24.de and is for research purposes only. The data was created with .

Rent Inflation in Japan remained unchanged at 0.30 percent in August. This dataset includes a chart with historical data for Japan Rent Inflation.

The dataset contains current data on low rent and Section 8 units in PHA's administered by HUD. The Section 8 Rental Voucher Program increases affordable housing choices for very low-income households by allowing families to choose privately owned rental housing. Through the Section 8 Rental Voucher Program, the administering housing authority issues a voucher to an income-qualified household, which then finds a unit to rent. If the unit meets the Section 8 quality standards, the PHA then pays the landlord the amount equal to the difference between 30 percent of the tenant's adjusted income (or 10 percent of the gross income or the portion of welfare assistance designated for housing) and the PHA-determined payment standard for the area. The rent must be reasonable compared with similar unassisted units.

Rent Inflation in Canada decreased to 4.50 percent in August from 5.10 percent in July of 2025. This dataset includes a chart with historical data for Canada Rent Inflation.

A. SUMMARY Beginning in 2022, the law requires owners of residential housing units in San Francisco to report certain information about their units to the San Francisco Rent Board on an annual basis. For units (other than condominium units) in buildings of 10 residential units or more, owners were required to begin reporting this information to the Rent Board by July 1, 2022, with updates due on March 1, 2023 and every March 1 thereafter. For condominium units and units in buildings with less than 10 residential units, reporting began on March 1, 2023 with updates due every March 1 thereafter. Owners are also required to inform the Rent Board within 30 days of any change in the name or business contact information of the owner or designated property manager. The Rent Board uses this information to create and maintain a “housing inventory” of all units in San Francisco that are subject to the Rent Ordinance.

B. HOW THE DATASET IS CREATED The Rent Board has developed a secure website portal that provides an interface for owners to submit the required information (The Housing Inventory). The Rent Board uses the information provided to generate reports and surveys, to investigate and analyze rents and vacancies, to monitor compliance with the Rent Ordinance, and to assist landlords and tenants and other City departments as needed. The Rent Board may not use the information to operate a “rental registry” within the meaning of California Civil Code Sections 1947.7 – 1947.8.

C. UPDATE PROCESS The Housing Inventory is continuously updated as it receives submissions from the public. The portal is available to the public 24/7. The Rent Board Staff also makes regular updates to the data during regular business hours, and the data is shared to DataSF every 24 hours.

D. HOW TO USE THIS DATASET It is important to note that this dataset contains information submitted by residential property owners and tenants. The Rent Board does not review or verify the accuracy of the data submitted. Please note that historical data is subject to change.

Notes for Analysis - Addresses have been anonymized to the block level - Latitude & Longitude are the closest mid-block point to the unit - Each row is a unit. To count total units, first select a year then count unique ids. Do not sum unit count.

Rent Inflation in Germany increased to 2.20 percent in August from 2.10 percent in July of 2025. This dataset includes a chart with historical data for Germany Rent Inflation.

The rental housing developments listed below are among the thousands of affordable units that are supported by City of Chicago programs to maintain affordability in local neighborhoods. The list is updated periodically when construction is completed for new projects or when the compliance period for older projects expire, typically after 30 years. The list is provided as a courtesy to the public. It does not include every City-assisted affordable housing unit that may be available for rent, nor does it include the hundreds of thousands of naturally occurring affordable housing units located throughout Chicago without City subsidies. For information on rents, income requirements and availability for the projects listed, contact each property directly. For information on other affordable rental properties in Chicago and Illinois, call (877) 428-8844, or visit www.ILHousingSearch.org.

The median rent for one- and two-bedroom apartments in Denver, Colorado, amounted to about ***** U.S. dollars by the end of 2023. While rents decreased slightly after the beginning of the coronavirus pandemic, the annual rental growth fell by more than *** percent in December 2023. Among the different states in the U.S., Colorado ranks as one of the more expensive rental markets.

The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]

How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.

The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.

Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.

Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.

[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.

[2] Ibid.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).

Commercial rents services price index (CRSPI) by North American Industry Classification System (NAICS). Quarterly data are available from the first quarter of 2006 for the total index and from the first quarter of 2019 for all other indexes. The table presents data for the most recent reference period and the last five periods. The base period for the index is (2019=100).

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

Quarterly summary of median private rent in South Australia by: suburb, postcode, State Government regions and Local Government Areas. The information relates to bonds lodged with Consumer and Business Services for private rental properties in South Australia.