Fair Market Rents (FMRs) are used to determine payment standard amounts for the Housing Choice Voucher program, to determine initial renewal rents for some expiring project-based Section 8 contracts, to determine initial rents for housing assistance payment (HAP) contracts in the Moderate Rehabilitation Single Room Occupancy program (Mod Rehab), rent ceilings for rental units in both the HOME Investment Partnerships program and the Emergency Solution Grants program, calculation of maximum award amounts for Continuum of Care recipients and the maximum amount of rent a recipient may pay for property leased with Continuum of Care funds, and calculation of flat rents in Public Housing units. The U.S. Department of Housing and Urban Development (HUD) annually estimates FMRs for Office of Management and Budget (OMB) defined metropolitan areas, some HUD defined subdivisions of OMB metropolitan areas and each nonmetropolitan county. 42 USC 1437f requires FMRs be posted at least 30 days before they are effective and that they are effective at the start of the federal fiscal year (generally October 1).

This dataset contains Real Estate Rents listings in the Canada broken by Province and City. Data was collected via web scraping using python libraries.

You may use the dataset for Canada rents houses trend analysis (with respect to the location - province/city/longitude/latitude), regression analysis (price prediction), correlation analysis, etc.,

Content

The dataset has 1 CSV file with 18 columns -

rentfaster.csv (25k+ entries)

-**'rentfaster_id'** - id of property on https://www.rentfaster.com . Can be explore with www.rentfaster.ca/rentfaster_id -**'city'** - city of property like 'Toronto', 'Calgary', 'Vancuver' and etc. -**'province'** - province of property like 'Alberta', 'Ontario' and etc. -**'address'** - address of property like '333 Seymour St' and etc -**'latitude'** - latitude coordinate of rental property -**'longitude'** - longitude coordinate of rental property -**'lease_term'** - category of rental period like 'Long Term', 'Negotiable' and etc -**'type'** - category of type a rental property like 'House', 'Apartment', 'Basement' and etc -**'price'** - price in CAD -**'beds'** - count of bedrooms -**'baths'** - count of bathrooms -**'sq_feet'** - area of rental property in square feets -**'link'** - right side of url for getting full details of the property rentfaster.com+'link' -**'furnishing'** - Furnished or not -**'availability_date'** - Date of availability -**'smoking'** - is allow smoke -**'cats'** - is allow cats -**'dogs'** - is allow dogs

Discover the booming rental housing market! Explore key trends, drivers, and challenges impacting this multi-trillion dollar industry. Learn about top players like Airbnb and Zillow, regional market share, and future growth projections to 2033. Get insights to inform your investment or business strategy.

As of January 2025, the rent for a two-bedroom apartment in Hawaii was about 120 U.S. dollars higher than in California. The states of Hawaii and California ranked as the most expensive within the United States for apartment renters. Conversely, an apartment in Arkansas was almost three times more affordable than one in Hawaii.In 2025, the average monthly rent in the U.S. declined slightly. Nevertheless, in rents increased in most states, with West Virginia registering the highest growth.

Fair Market Rents (FMRs) represent the estimated amount (base rent + essential utilities) that a property in a given area typically rents for. The data are primarily used to determine payment standard amounts for the Housing Choice Voucher program. However, FMRs are also used to determine initial renewal rents for expiring project-based Section 8 contracts, determine initial rents for housing assistance payment (HAP) contracts in the Moderate Rehabilitation Single Room Occupancy program (Mod Rehab), rent ceilings for rental units in both the HOME Investment Partnerships program and the Emergency Solution Grants (ESG) program, calculate of maximum award amounts for Continuum of Care recipients and the maximum amount of rent a recipient may pay for property leased with Continuum of Care funds, and calculate flat rent amounts in Public Housing Units.

Virginia (VA) has the 19th highest rent in the country out of 56 states and territories. The Fair Market Rent in Virginia ranges from $701 for a 2-bedroom apartment in Grayson County, VA to $1,765 for a 2-bedroom unit in Washington-Arlington-Alexandria, DC-VA-MD HUD Metro FMR Area.

For FY 2024, the Washington-Arlington-Alexandria, DC-VA-MD HUD Metro FMR Area (Arlington County) rent for a studio or efficiency is $1,772 per month and $3,015 per month to rent a house or an apartment with 4 bedrooms. The average Fair Market Rent for a 2-bedroom home in Virginia is $1,056 per month.

Approximately 15% of Americans qualify for some level of housing assistance. The population in Virginia is around 2,038,847 people. So, there are around 305,827 people in Virginia who could be receiving housing benefits from the HUD. For FY 2025, the Washington-Arlington-Alexandria, DC-VA-MD HUD Metro FMR Area (Arlington County) rent for a studio or efficiency is $2,012 per month and $3,413 per month to rent a house or an apartment with 4 bedrooms. The average Fair Market Rent for a 2-bedroom home in Virginia is $1,059 per month.

The UK residential rental market is poised for significant growth, with forecasts indicating a cumulative increase of nearly **** percent by 2029. This surge is expected to be front-loaded, with a robust *****percent rise anticipated in 2025. Rental growth has accelerated notably since 2021, with August 2024 experiencing a decade-high annual percentage growth. The trend reflects the complex interplay between housing affordability, mortgage rates, and supply of rental homes, as the UK housing market navigates a period of transition.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

Fair Market RentsThis National Geospatial Data Asset (NGDA) dataset, shared as a Department of Housing and Urban Development (HUD) feature layer, displays fair market rents (FMR) in the United States. According to HUD, "Fair Market Rents (FMRs) represent the estimated amount (base rent + essential utilities) that a property in a given area typically rents for. The data are primarily used to determine payment standard amounts for the Housing Choice Voucher program. However, FMRs are also used to determine initial renewal rents for expiring project-based Section 8 contracts, determine initial rents for housing assistance payment (HAP) contracts in the Moderate Rehabilitation Single Room Occupancy program (Mod Rehab), rent ceilings for rental units in both the HOME Investment Partnerships program and the Emergency Solution Grants (ESG) program, calculate of maximum award amounts for Continuum of Care recipients and the maximum amount of rent a recipient may pay for property leased with Continuum of Care funds, and calculate flat rent amounts in Public Housing Units."Milwaukee-Waukesha-West Allis, WI Metropolitan Statistical Area (MSA)Data currency: current Federal service (Fair Market Rents)NGDAID: 122 (Fair Market Rents (Fair Market Rents For The Section 8 Housing Assistance Payments Program) - National Geospatial Data Asset (NGDA))For more information, please visit: Fair Market RentsSupport documentation: Fair Market Rents (FMRs)For feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

In California, the estimated fair market rent for a two-bedroom accommodation amounted to ******U.S. dollars in 2025. It was one of the least affordable states in terms of housing that year, as someone would need to earn at least twice the minimum wage to afford a two-bedroom rental unit there.

Mexico was one of the economies where house prices increased the most between 2016 and 2024, rising by nearly ** percent during that period. The growth rate of housing prices from 2015 to 2023 in Russia was even higher, but the 2024 data for that country was not yet available. Meanwhile, Poland and the U.S. were among the countries where rents increased the most from 2016 to 2024.

Small Area Fair Market Rents (SAFMRs) are FMRs calculated for ZIP Codes within Metropolitan Areas. Small Area FMRs are required to be used to set Section 8 Housing Choice Voucher payment standards in areas designated by HUD (available here). Other Housing Agencies operating in non-designated metropolitan areas may opt-in to the use of Small Area FMRs. Furthermore, Small Area FMRs may be used as the basis for setting Exception Payment Standards – PHAs may set exception payment standards up to 110 percent of the Small Area FMR. PHAs administering Public Housing units may use Small Area FMRs as an alternative to metropolitan area-wide FMRs when calculating Flat Rents. Please See HUD’s Small Area FMR Final Rule for additional information regarding the uses of Small Area FMRs.Note that this service does not denote precise SAFMR geographies. Instead, the service utilizes a relationship class to associate the information for each SAFMR with the FMR areas that its ZCTA overlaps. For example, ZCTA 94558 overlaps the Santa Rosa, Napa, and Vallejo-Fairfield MSAs. Selecting that ZCTA will reveal the SAFMR information associated with each FMR area. To learn more about the Small Area Fair Market Rents visit: https://www.huduser.gov/portal/datasets/fmr/smallarea/index.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: Fiscal Year 2026Date Update: FY2026 : Oct. 1 - Sept. 30

In California, the highest fair market rent for a two-bedroom accommodation amounted to ***** U.S. dollars in Santa Cruz-Watsonville. This made it the most expensive metro area to live in California in 2025. Renters required an hourly wage of at least ******U.S. dollars to afford this two-bedroom housing. Second in rank was San Jose that had a ***** U.S. dollar fair market rent for two-bedroom housing.

Rent estimates at the 50th percentile (or median) are calculated for all Fair Market Rent areas. Fair Market Rents (FMRs) are primarily used to determine payment standard amounts for the Housing Choice Voucher program, to determine initial renewal rents for some expiring project-based Section 8 contracts, to determine initial rents for housing assistance payment (HAP) contracts in the Moderate Rehabilitation Single Room Occupancy program (Mod Rehab), and to serve as a rent ceiling in the HOME rental assistance program. FMRs are gross rent estimates. They include the shelter rent plus the cost of all tenant-paid utilities, except telephones, cable or satellite television service, and internet service. The U.S. Department of Housing and Urban Development (HUD) annually estimates FMRs for 530 metropolitan areas and 2,045 nonmetropolitan county FMR areas. Under certain conditions, as set forth in the Interim Rule (Federal Register Vol. 65, No. 191, Monday October 2, 2000, pages 58870-58875), these 50th percentile rents can be used to set success rate payment standards.

This dataset contains state- and project-level variables used in the study “Housing Market Conditions, Land-Use Regulation, and the Effectiveness of the Low-Income Housing Tax Credit (LIHTC) Program.” It includes Fair Market Rent (FMR) data, land-use freedom indices, urbanization rates, and LIHTC project information used to analyze the interaction between rental demand and regulatory environments. These data support regression models, descriptive statistics, and scatterplots reported in the paper.

The apartment rental market in the United States has been stagnating since 2019, after increasing year-on-year for several years. In 2022, the estimated market size of apartment rental was ***** billion U.S. dollars, down from ***** billion U.S. dollars in 2021. In 2023, the market is forecast to further contract by one percent, reaching ***** billion U.S. dollars.

This dataset provides monthly rental price statistics for apartments across urban neighborhoods, including average, median, minimum, and maximum rents by apartment type and location. It enables detailed market trend analysis, investment strategy development, and urban planning by offering granular insights into rental dynamics over time. The dataset is ideal for real estate professionals, investors, and researchers seeking to understand rental market fluctuations.

In 2024, there were approximately **** million housing units occupied by renters in the United States. This number has been gradually increasing since 2010 as part of a long-term upward swing since 1975. Meanwhile, the number of unoccupied rental housing units has followed a downward trend, suggesting a growing demand and supply failing to catch up. Why are rental homes in such high demand? This high demand for rental homes is related to the shortage of affordable housing. Climbing the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home. How many owner occupied homes are there in the U.S.? In 2023, there were over ** million owner occupied homes. Owner occupied housing is when the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing and social housing.

The price for rental student housing in the U.S. was the highest for properties within *** mile away from the campus as of July 2024. The average effective rent for these properties was *** U.S. dollars, compared to the average for all student housing properties, which was *** U.S. dollars.

This dataset provides comprehensive information about rental house prices across various locations in India. It includes details such as house type, size, location, city, latitude, longitude, price, currency, number of bathrooms, number of balconies, negotiability of price, price per square foot, verification date, description of the property, security deposit, and status of furnishing (furnished, unfurnished, semi-furnished).

Note: This is Recently scraped data of April 2024.

Dataset Glossary (Column-Wise)

• House Type: Type of house (e.g., apartment, villa, duplex).
• House Size: Size of the house in square feet or square meters.
• Location: Specific area or neighborhood where the property is located.
• City: City in India where the property is situated.
• Latitude: Geographic latitude coordinates of the property location.
• Longitude: Geographic longitude coordinates of the property location.
• Price: Rental price of the house.
• Currency: Currency in which the price is denoted (e.g., INR - Indian Rupees).
• Number of Bathrooms: Total number of bathrooms in the house.
• Number of Balconies: Total number of balconies in the house.
• Negotiability: Indicates whether the price is negotiable (Yes/No).
• Price per Square Foot: Price of the house per square foot.
• Verification Date: Date when the rental information was verified.
• Description: Additional description or details about the property.
• Security Deposit: Amount of security deposit required for renting the property.
• Status: Indicates the furnishing status of the property (furnished, unfurnished, semi-furnished).

Usage

This dataset aims to provide valuable insights into the rental housing market in India, enabling analysis of rental trends, comparison of prices across different locations and property types, and understanding the impact of various factors on rental prices. Researchers, analysts, and policymakers can utilize this dataset for a wide range of applications, including real estate market analysis, urban planning, and economic research.

Acknowledgement

This Dataset is created from https://www.makaan.com/. If you want to learn more, you can visit the Website.

Cover Photo by: Playground.ai