Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

The average sales price of new homes in the United States experienced a slight decrease in 2024, dropping to 512,2000 U.S. dollars from the peak of 521,500 U.S. dollars in 2022. This decline came after years of substantial price increases, with the average price surpassing 400,000 U.S. dollars for the first time in 2021. The recent cooling in the housing market reflects broader economic trends and changing consumer sentiment towards homeownership. Factors influencing home prices and affordability The rapid rise in home prices over the past few years has been driven by several factors, including historically low mortgage rates and increased demand during the COVID-19 pandemic. However, the market has since slowed down, with the number of home sales declining by over two million between 2021 and 2023. This decline can be attributed to rising mortgage rates and decreased affordability. The Housing Affordability Index hit a record low of 98.1 in 2023, indicating that the median-income family could no longer afford a median-priced home. Future outlook for the housing market Despite the recent cooling, experts forecast a potential recovery in the coming years. The Freddie Mac House Price Index showed a growth of 6.5 percent in 2023, which is still above the long-term average of 4.4 percent since 1990. However, homebuyer sentiment remains low across all age groups, with people aged 45 to 64 expressing the most pessimistic outlook. The median sales price of existing homes is expected to increase slightly until 2025, suggesting that affordability challenges may persist in the near future.

Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q2 2025 about sales, housing, and USA.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

The U.S. housing market continues to evolve, with the median home price forecast to reach ******* U.S. dollars by the second quarter of 2026. This projection comes after a period of significant growth and recent fluctuations, reflecting the complex interplay of economic factors affecting the real estate sector. The rising costs have not only impacted home prices, but also down payments, with the median down payment more than doubling since 2012. Regional variations in housing costs Home prices and down payments vary dramatically across the United States. While the national median down payment stood at approximately ****** U.S. dollars in early 2024, homebuyers in states like California, Massachusetts, and Hawaii faced down payments exceeding ****** U.S. dollars. This disparity highlights the challenges of homeownership in high-cost markets and underscores the importance of location in determining housing affordability. Market dynamics and future outlook The housing market has shown signs of cooling after years of rapid growth, with more modest price increases of *** percent in 2022 and *** percent in 2023. This slowdown can be attributed in part to rising mortgage rates, which have tempered demand. Despite these challenges, most states continued to see year-over-year price growth in the fourth quarter of 2023, with Rhode Island and Vermont leading the pack at over ** percent appreciation. As the market adjusts to new economic realities, potential homebuyers and investors alike will be watching closely for signs of stabilization or renewed growth in the coming years.

Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet in the United States (MEDLISPRIPERSQUFEEUS) from Jul 2016 to Jul 2025 about square feet, listing, median, price, and USA.

The online residential home sale listings industry is experiencing significant changes in its dynamics because of the increased number of homes for sale. The growth in listings is because of various factors, including a climb in the number of homeowners choosing to sell, the easing of the mortgage rate lock-in effect, and economic concerns driving the sale of investment properties. These conditions and the shift from a seller's market towards a more balanced, or even a buyer's market, translate into increased traffic and engagement on home sale platforms. This presents an opportunity for these online platforms to enhance their user experience, refine search tools and offer data analytics to help buyers navigate the increased options. By the end of 2025, industry revenue has climbed at a CAGR of 3.0% and is expected to total $2.2 billion in 2025. In 2025, revenue is expected to strengthen by an estimated 4.2%. Despite enjoying growth, the industry faces challenges with the elevated mortgage rates reducing demand for home purchases, leading to a market freeze. Despite the gain in home listings, actual transaction volumes have remained subdued, creating a challenging environment for the online residential home sale listing platforms. To stay competitive, these platforms are pivoting to offer enhanced tools for price comparisons, real-time mortgage calculators and in-depth educational content to help buyers understand the increased cost of borrowing and also navigate the high inventory but low turnover market. Industry profit has climbed as revenue has outpaced wage growth through the end of 2025. Through the end of 2030, online platforms must position themselves for demographic shifts and changing consumer preferences. Gen Z and younger millennials, who are entering homebuying age, are demanding a more tech-driven, seamless and mobile-first experience. The industry will also continue to see online platforms transform into comprehensive, one-stop digital destinations offering integrated services for every stage of the housing journey. Embracing changes such as artificial intelligence and data analytics to enhance user experience, streamlining listings uploads and offering real-time communication between buyers, sellers, and agents will be crucial for future success. Platforms that offer user-friendly, one-stop experiences and are equipped to provide advanced, feature-rich mobile experiences are set to capture greater market share. Overall, industry revenue will gain at a CAGR of 3.3% through 2030 to total $2.6 billion.

Existing Home Sales in the United States decreased to 3930 Thousand in June from 4040 Thousand in May of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

House prices in the second most populous state in the United States, Texas, have increased more than two-fold since 2011. In 2023, the median house price reached ******* U.S. dollars, a decrease of *** percent from the previous year. Texas is one of the more affordable states for buying a home with house prices below the national average.

The median sales price of new homes sold in the United States increased steadily from 1965 to 2023. In 2023, a newly built home cost approximately ******* U.S. dollars. That was a decline of nearly ****** U.S. dollars and the first decrease since 2018. Prices varied greatly across different regions in the country, with the most expensive housing found in the Northeast region.

New Home Sales in the United States increased to 627 Thousand units in June from 623 Thousand units in May of 2025. This dataset provides the latest reported value for - United States New Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Real Residential Property Prices for United States (QUSR628BIS) from Q1 1970 to Q1 2025 about residential, HPI, housing, real, price index, indexes, price, and USA.

Context

This dataset includes the median list price divided by the square footage of a 1-bedroom home for a select number of neighborhoods around the United States.

Content

When available, data includes median price per square foot on a monthly basis between January 2010 and September 2016.

Selected neighborhoods include:

• Upper East Side, New York, NY
• Spring Valley, Las Vegas, NV
• Hollywood, Los Angeles, CA
• Williamsburg, New York, NY
• Harlem, New York, NY
• Enterprise, Las Vegas,NV
• Downtown, San Jose, CA
• Sheepshead Bay, New York, NY
• Forest Hills, New York, NY
• Jackson Heights, New York, NY
• Gramercy, New York, NY
• Flagami, Miami, FL
• Downtown, Memphis, TN
• Chelsea, New York, NY
• Oak Lawn, Dallas, TX
• Greater Uptown, Houston, TX
• South Loop, Chicago, IL
• Makiki-Lower Punchbowl-Tantalus, Honolulu, HI
• Downtown, Los Angeles, CA
• Capitol Hill, Seattle, WA
• Clinton, New York, NY
• Alexandria West, Alexandria, VA
• Financial District, New York, NY
• Flatiron District, New York, NY
• Landmark-Van Dom, Alexandria, VA
• Flamingo Lummus, Miami Beach, FL
• Winchester, Las Vegas, NV
• Brickell, Miami, FL
• Waikiki, Honolulu, HI
• Back Bay, Boston, MA
• Sutton Place, New York, NY
• and several others

Inspiration

• What neighborhoods have the most expensive real estate per square foot? Least expensive?
• Which neighborhoods and/or cities have the fastest growth rates in price?
• Are there any neighborhoods that remain relatively steady in price?
• Given that this metric is listing price per square foot, is there a similar dataset that could help you compare median square footage in a 1-bedroom home across neighborhoods?

Acknowledgement

This dataset is part of Zillow Data, and the original source can be found here, under the Neighborhoods link.

Graph and download economic data for Housing Inventory: Median Listing Price in Utah (MEDLISPRIUT) from Jul 2016 to Jul 2025 about UT, listing, median, price, and USA.

Housing Starts in the United States increased to 1321 Thousand units in June from 1263 Thousand units in May of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q1 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

Zillow reigns supreme in the U.S. real estate website landscape, attracting a staggering ***** million monthly visits in 2024. This figure dwarfs its closest competitor, Realtor.com, which garnered less than half of Zillow's traffic. Online platforms are extremely popular, with the majority of homebuyers using a mobile device during the buying process. The rise of Zillow Founded in 2006, the Seattle-headquartered proptech Zillow has steadily grown over the years, establishing itself as the most popular U.S. real estate website. In 2023, the listing platform recorded about *** million unique monthly users across its mobile applications and website. Despite holding an undisputed position as a market leader, Zillow's revenue has decreased since 2021. A probable cause for the decline is the plummeting of housing transactions and the negative housing sentiment. Performance and trends in the proptech market The proptech market has shown remarkable performance, with companies like Opendoor and Redfin experiencing significant stock price increase in 2023. This growth is particularly notable in the residential brokerage segment. Meanwhile, major players in proptech fundraising, such as Fifth Wall and Hidden Hill Capital, have raised billions in direct investment, further fueling the sector's development. As technology continues to reshape the real estate industry, online platforms like Zillow are likely to play an increasingly crucial role in how people search for and purchase homes. (1477916, 1251604)

This layer shows housing costs as a percentage of household income by age. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. This layer is symbolized to show the predominant housing type for householders where the householder is age 65+ and spending at least 30% of their income on housing. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25072, B25093 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Graph and download economic data for Housing Inventory: Median Listing Price per Square Feet in Arkansas (MEDLISPRIPERSQUFEEAR) from Jul 2016 to Jul 2025 about AR, square feet, listing, median, price, and USA.

This layer shows housing costs as a percentage of household income. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. This layer is symbolized to show the count and percent of renter households that spend 30.0% or more of their household income on gross rent (contract rent plus tenant-paid utilities). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2015-2019ACS Table(s): B25070, B25091Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 10, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.