Apartment rents in two states and the District of Columbia in the U.S. exceeded ***** U.S. dollars in April 2025. In Hawaii, the median rent was about ***** U.S. dollars, nearly *** U.S. dollars higher than the national average. At the other end of the spectrum was Nebraska, where renters paid about ***** U.S. dollars for the median new lease. Overall, most states saw rental rates increase year-on-year.

The monthly median asking rent for unfurnished apartments in the United States rose by about ** U.S. dollars in 2024. In the third quarter of 2024, the median rent amounted to ***** U.S. dollars, up from ***** U.S. dollars in 2023. This increase was in line with a decade of steady growth, interrupted only in 2020 during the COVID-19 pandemic and in 2023. The U.S. rental market As rental apartment vacancy rates fall, rents are on the rise. This makes it more difficult for Americans to, first, find an apartment to rent, and second, find an apartment which they can afford. Nevertheless, renting has become much more common in recent years, with the number of renter households having substantially increased in the past two decades. In 2024, there were approximately **** million renter households in the U.S. Rents in different states Of course, rents vary from state to state. The most expensive rents are found in Hawaii, California, District of Colombia, New Jersey, and Florida. Following the COVID-19 pandemic, growth was the strongest in the Sun Belt states, and especially in states with lower costs of living, such as Texas. In Austin, TX, the average rent soared by nearly ** percent in 2021, and remained elevated, despite a slight decline in 2023.

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 May 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

In 2023, Alaska reported the highest rent for public housing among all the states in the United States. The average monthly rent in Alaska amounted to 715 U.S. dollars for government-subsidized housing. California, New York, and Hawaii were some of the states with the highest average rent, with rental costs above 550 U.S. dollars. On the other hand, Puerto Rico offered the most affordable public housing with the lowest rent among all states, coming in at just 121 U.S. dollars. Some other affordable states for low-income families were Arkansas, Alabama, Oklahoma, and Ohio, all costing less than 320 U.S. dollars.

The average monthly rent for all apartment types in the U.S. soared in 2021 and 2022, followed by a slight decline in the next two years. In April 2025, the monthly rent for a two-bedroom apartment amounting to ***** U.S. dollars. That was an increase from ***** U.S. dollars in January 2021, but a decline from the peak value of ***** U.S. dollars in August 2022. Where are the most expensive apartments in the U.S.? Apartment rents vary widely from state to state. To afford a two-bedroom apartment in California, for example, a renter needed to earn an average hourly wage of nearly ** U.S. dollars, which was approximately double the average wage in North Carolina and three times as much as the average wage in Arkansas. In fact, rental costs were considerably higher than the hourly minimum wage in all U.S. states. How did rents change in different states in the U.S.? In 2024, some of the most expensive states to rent an apartment only saw a moderate increase in rental prices. Nevertheless, rents increased in most states as of April 2025. In West Virginia, the annual rental growth was the highest, at ***** percent.

Rent Inflation in the United States decreased to 3.90 percent in May from 4 percent in April of 2025. This dataset includes a chart with historical data for the United States Rent Inflation.

The average rent price of residential property in Austria has increased year-on-year since the beginning of the reporting period. In 2023, the average rent in Austria was approximately 9.4 euros per square meter. Salzburg had the highest prices, at 11.3 euros per square meter. Across the major European housing markets, house prices and rents have been increasing steadily in recent years.

Graph and download economic data for Rental Vacancy Rate in the United States (RRVRUSQ156N) from Q1 1956 to Q1 2025 about vacancy, rent, rate, and USA.

United States US: Price to Rent Ratio: sa data was reported at 134.118 2015=100 in 2024. This records an increase from the previous number of 133.710 2015=100 for 2023. United States US: Price to Rent Ratio: sa data is updated yearly, averaging 99.069 2015=100 from Dec 1970 (Median) to 2024, with 55 observations. The data reached an all-time high of 137.672 2015=100 in 2022 and a record low of 89.669 2015=100 in 1997. United States US: Price to Rent Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by rent price indices

In 2024, New York, NY, was the most expensive rental market for one-bedroom apartments in the United States. The median monthly rental rate of an apartment in New York was ***** U.S. dollars, while in San Francisco, CA which ranked second highest, renters paid on average ***** U.S. dollars.

Graph and download economic data for Expenditures: Total Average Annual Expenditures by Housing Tenure: Renter (CXUTOTALEXPLB1705M) from 1984 to 2023 about rent, average, expenditures, housing, and USA.

Rents in the United States declined year-on-year for the first time in June 2023, after surging for two years in a row. In November 2021, rents soared by over ** percent annually — the highest increase on record, and in August 2022, the average rental price reached an all-time high of over ***** U.S. dollars. Rental growth has since mellowed, with January 2025 recording a decline of about *** percent from the same period one year ago. Despite the softening of the market, many states still experienced rising rents.

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 ...).

Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q1 2025 about sales, housing, and USA.

Context of the project Knowledge of the level of rents is important to ensure the proper functioning of the rental market and the conduct of national and local housing policies. In 2018, the Directorate-General for Planning, Housing and Nature (DGALN) launched the “rent map” project by partnering with a research team in economics from Agrosup Dijon and the Institut national de la recherche en agronomique (INRAE) and SeLoger and leboncoin. In 2020, the project was taken over by the National Agency for Housing Information (ANIL), which published, in 2022 and 2023, new versions of the map. This innovative partnership has made it possible to rebuild a database with 8 million rental ads. Based on these data, the research team and ANIL have developed a methodology for estimating indicators, at the municipal level, of rent (including charges) per m² for apartments and houses. These experimental indicators are put online in order to be usable by all: State services, local authorities, real estate professionals, private landlords and tenants. Starting in 2022, the maps are updated and published annually by ANIL. This project provides additional information to that offered by the Local Observatories of Homes (OLL), deployed since 2013 and reinforced since 2018 by the Elan Law. Today, this associative network of about thirty OLL publishes each year precise information on rents charged in about fifty French agglomerations. Presentation of the dataset The data disseminated are indicators of ad rents, at the municipal level. The field covered is the entire France, outside of Mayotte. The geography of the municipalities is the one in force on January 1, 2023. Rent indicators are calculated through the use of ad data published on the Leboncoin and SeLoger Group platforms over the period 2018-2023. Rent indicators are provided inclusive of standard leased property leased empty and leased in Q3 2023 with the following reference characteristics: — For an apartment (all types): area of 52 m² and average area per room of 22.2 m² — For apartment type T1-T2: area of 37 m² and average area per room of 23.0 m² — For apartment type T3 and more: area of 72 m² and average area per room of 21.2 m² — For a house: surface area of 92 m² and average area per room of 22.4 m² Conditions for use of data These indicators are freely usable, provided that the source is mentioned in the following form: “Anil estimates, based on data from the SeLoger Group and leboncoin”. Precautions for use The rent indicators are calculated charges included, on unfurnished ad data. The data were duplicated but without being able to rely on highly discriminatory photos and features. The mesh size method implies, for municipalities without rented accommodation via an advertisement on at least one of the two platforms over the period in question, that the rent indicator is that estimated for a larger mesh comprising neighbouring municipalities with similar characteristics. Users are advised to consider with caution rent indicators in municipalities where the coefficient of determination (R2) is less than 0.5, the number of observations in the municipality is less than 30 or the prediction interval is very wide. Moreover, compared to the previous version of the indicators published in 2022, this new map makes it possible to compare rents only in cases where indicators are calculated at municipal level in both 2022 and 2023.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

In January 2025, apartment rents recorded an annual growth in most U.S. states. Nevertheless, the national average rent declined by about *** percent. West Virginia was the state with the largest rental increase, while Colorado measured the largest decline. California, one of the most expensive states to rent an apartment, such as California, saw an increase of about *** percent from the previous year. How much should you earn to afford to rent an apartment in different states in the U.S.? Both employment opportunities and the living costs vary widely across the country. In California, which is among the most competitive housing markets in the U.S., the hourly wage needed to afford a two-bedroom apartment rental was roughly ** U.S. dollars, more than twice higher than in North Carolina, Louisiana, or Michigan in 2024. When it comes to the median household income, on the other hand, California does not even make it in the top ten states. How much should you earn to afford a home in some of U.S. largest metros? In 2022, the annual salary needed to buy a median-priced home in the U.S. was ****** U.S. dollars. However, in some of the largest metropolitan areas in the United States, where housing prices are up to two or three times higher, homebuyers would have to earn more than 100,000 U.S. dollars to afford a home. In San Jose, which was the most expensive metro, the annual salary needed for a median-priced home was approximately ******* U.S. dollars.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

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.

The monthly rent of mobile homes in the U.S. has gradually increased since 2010, peaking in 2024. In the third quarter of that year, the average monthly rent for manufactured homes was 717 U.S. dollars. Similarly, apartment rents also soared in 2022, followed by a slight decline in the next two years. Where in the U.S. are manufactured homes most popular? States with a growing economy and large population provide the best opportunities for manufactured housing. In September 2023, Texas had the highest number of mobile homes in the United States. Other states with a high number of mobile homes were North Carolina and Florida. Moreover, Texas also boasted the highest number of manufactured home production plants. Affordability of mobile homes across the U.S. Manufactured homes are considerably less expensive than regular homes, which makes them an attractive option for people looking to purchase property without breaking the bank. Mobile homes are cheaper because manufacturers benefit from economies of scale due to large-scale production, which allows them to lower costs per unit. Additionally, mobile homes lose value faster than traditional homes, which can make them more affordable to purchase initially. The average sales price for a new mobile home has been on the rise, but during the housing boom in 2021, it increased dramatically.