100+ datasets found
  1. Fastest growing housing markets worldwide 2024

    • statista.com
    Updated May 28, 2025
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    Statista (2025). Fastest growing housing markets worldwide 2024 [Dataset]. https://www.statista.com/statistics/1041586/price-growth-fastest-growing-home-markets-worldwide/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Turkey experienced the highest annual change in house prices in 2024, followed by Bulgaria and Russia. In the fourth quarter of the year, the nominal house price in Turkey grew by **** percent, while in Bulgaria and Russia, the increase was ** and ** percent, respectively. Meanwhile, many countries saw prices fall throughout the year. That has to do with an overall cooling of the global housing market that started in 2022. When accounting for inflation, house price growth was slower, and even more countries saw the market shrink.

  2. U.S. Housing Prices: Regional Trends (2000 - 2023)

    • kaggle.com
    Updated Dec 6, 2024
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    Praveen Chandran (2024). U.S. Housing Prices: Regional Trends (2000 - 2023) [Dataset]. https://www.kaggle.com/datasets/praveenchandran2006/u-s-housing-prices-regional-trends-2000-2023
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 6, 2024
    Dataset provided by
    Kaggle
    Authors
    Praveen Chandran
    Area covered
    United States
    Description

    Dataset Overview

    This dataset provides historical housing price indices for the United States, covering a span of 20 years from January 2000 onwards. The data includes housing price trends at the national level, as well as for major metropolitan areas such as San Francisco, Los Angeles, New York, and more. It is ideal for understanding how housing prices have evolved over time and exploring regional differences in the housing market.

    Why This Dataset?

    The U.S. housing market has experienced significant shifts over the last two decades, influenced by economic booms, recessions, and post-pandemic recovery. This dataset allows data enthusiasts, economists, and real estate professionals to analyze long-term trends, make forecasts, and derive insights into regional housing markets.

    What’s Included?

    Time Period: January 2000 to the latest available data (specific end date depends on the dataset). Frequency: Monthly data. Regions Covered: 20+ U.S. cities, states, and aggregates.

    Columns Description

    Each column represents the housing price index for a specific region or aggregate, starting with a date column:

    Date: Represents the date of the housing price index measurement, recorded with a monthly frequency. U.S. National: The national-level housing price index for the United States. 20-City Composite: The aggregate housing price index for the top 20 metropolitan areas in the U.S. CA-San Francisco: The housing price index for San Francisco, California. CA-Los Angeles: The housing price index for Los Angeles, California. WA-Seattle: The housing price index for Seattle, Washington. NY-New York: The housing price index for New York City, New York. Additional Columns: The dataset includes more columns with housing price indices for various U.S. cities, which can be viewed in the full dataset preview.

    Potential Use Cases

    Time-Series Analysis: Investigate long-term trends and patterns in housing prices. Forecasting: Build predictive models to forecast future housing prices using historical data. Regional Comparisons: Analyze how housing prices have grown in different cities over time. Economic Insights: Correlate housing prices with economic factors like interest rates, GDP, and inflation.

    Who Can Use This Dataset?

    This dataset is perfect for:

    Data scientists and machine learning practitioners looking to build forecasting models. Economists and policymakers analyzing housing market dynamics. Real estate investors and analysts studying regional trends in housing prices.

    Example Questions to Explore

    Which cities have experienced the highest housing price growth over the last 20 years? How do housing price trends in coastal cities (e.g., Los Angeles, Miami) compare to midwestern cities (e.g., Chicago, Detroit)? Can we predict future housing prices using time-series models like ARIMA or Prophet?

  3. Metros where homes sold the fastest in the U.S. 2024, by number of days

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Metros where homes sold the fastest in the U.S. 2024, by number of days [Dataset]. https://www.statista.com/statistics/889984/cities-homes-sold-fastest-usa-by-days/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2024
    Area covered
    United States
    Description

    Homes in San Jose, Hartford, and Washington, DC were the hottest housing markets in the United States in April 2024, when considering the time needed to sell a house. In San Jose, listings took on average ** days to go to pending. Nationwide, the average number of days on market was ** days.

  4. Number of newly built and existing homes for sale in the U.S. 2013-2025

    • statista.com
    Updated May 30, 2016
    + more versions
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    Statista Research Department (2016). Number of newly built and existing homes for sale in the U.S. 2013-2025 [Dataset]. https://www.statista.com/study/10748/residential-housing-in-the-us-statista-dossier/
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    Dataset updated
    May 30, 2016
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    The number of existing homes for sale in the United States decreased overall since 2013, while the number of newly built homes for sale followed the opposite trend. As of May 2025, there were 1.54 million existing and 507,000 newly built housing units for sale. Unlike new homes, the existing housing inventory typically increased in the second and third quarters of the year when the housing market is more active.

  5. U

    United States House Prices Growth

    • ceicdata.com
    Updated Feb 15, 2020
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    CEICdata.com (2020). United States House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/house-prices-growth
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    Dataset updated
    Feb 15, 2020
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    United States
    Description

    Key information about House Prices Growth

    • US house prices grew 5.2% YoY in Dec 2024, following an increase of 5.4% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 1992 to Dec 2024, with an average growth rate of 5.4%.
    • House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

    CEIC calculates House Prices Growth from quarterly House Price Index. Federal Housing Finance Agency provides House Price Index with base January 1991=100.

  6. T

    United States Nahb Housing Market Index

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 18, 2025
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    TRADING ECONOMICS (2025). United States Nahb Housing Market Index [Dataset]. https://tradingeconomics.com/united-states/nahb-housing-market-index
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    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Aug 18, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1985 - Aug 31, 2025
    Area covered
    United States
    Description

    Nahb Housing Market Index in the United States decreased to 32 points in August from 33 points in July of 2025. This dataset provides the latest reported value for - United States Nahb Housing Market Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  7. F

    Housing Inventory: Median Days on Market in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in the United States [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMARUS
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    jsonAvailable download formats
    Dataset updated
    Jul 31, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Jul 2025 about median and USA.

  8. European real estate market prospects 2025, by city

    • statista.com
    Updated Aug 5, 2025
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    Statista (2025). European real estate market prospects 2025, by city [Dataset]. https://www.statista.com/statistics/377422/europe-real-estate-investment-existing-big-cities-ranking/
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    Dataset updated
    Aug 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Europe
    Description

    London maintains its dominance in European real estate with the highest prospect score of 2.72 for 2025, significantly ahead of Madrid and Paris, which scored 2.12 and 2.07, respectively. This ranking reflects a comprehensive assessment of factors that real estate investors consider crucial, including market size, economic performance, and connectivity. The gap between London and other major cities highlights its resilience despite Brexit concerns and points to continued investor confidence in the British capital's property market fundamentals. Key factors driving city rankings Market size, liquidity, and economic performance emerge as the most critical factors determining a city's investment attractiveness for 2025. London's top position is reinforced by its established market infrastructure and global connectivity, while Madrid and Paris benefit from strong economic forecasts. However, investors face mounting challenges that could impact these markets, with construction costs, capital expenditure requirements, and increasing environmental sustainability regulations cited as major concerns. Industry experts note that these factors could particularly affect development-heavy investments in emerging European markets. (1062070, 376877) Sectoral growth opportunities Data centers represent the most promising real estate investment sector in Europe for 2025, with London, Frankfurt, and Dublin emerging as primary destinations due to their growing data center capacity. New energy infrastructure and student housing follow closely as high-potential sectors. This trend reflects the broader shift toward technology-driven and specialized real estate assets. While traditional suburban offices face diminishing prospects, cities with strong digital infrastructure like London and Frankfurt are positioned to capitalize on the demand for data-focused real estate developments, potentially strengthening their overall market position in the coming years.

  9. T

    BAL_2011 Housing Market Typology

    • data.opendatanetwork.com
    application/rdfxml +5
    Updated May 9, 2014
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    (2014). BAL_2011 Housing Market Typology [Dataset]. https://data.opendatanetwork.com/w/5mq8-hzk8/default?cur=WFs1n7wQ2OA&from=9qaL08466kJ
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    tsv, csv, application/rssxml, json, xml, application/rdfxmlAvailable download formats
    Dataset updated
    May 9, 2014
    Description

    The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city’s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City’s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City’s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

  10. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 2025
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    (2025). Average Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/ASPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    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.

  11. d

    2011 Housing Market Typology.

    • datadiscoverystudio.org
    csv, json, rdf, xml
    Updated Feb 3, 2018
    + more versions
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    (2018). 2011 Housing Market Typology. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/ce139e562b2346ad8c64d799bc2eed7e/html
    Explore at:
    rdf, json, csv, xmlAvailable download formats
    Dataset updated
    Feb 3, 2018
    Description

    description: The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city_s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City_s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City_s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.; abstract: The Typology will assist city government, local foundations and non-profits to understand local market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. In addition, the typology will inform neighborhood level planning efforts and provide residents with an understanding of the local housing market conditions in their communities. Regional Choice: Competitive housing markets with high owner-occupancy rates and high property values in comparison to all other market types. Foreclosure, vacancy and abandonment rates are low. Middle Market Choice: Housing prices above the city_s average with strong ownership rates, and low vacancies, but with slightly increased foreclosure rates. Middle Market: Median sales values of $91,000 (above the City_s average of $65,000) as well as high homeownership rates. These markets experienced higher foreclosure rates when compared to higher value markets, with slight population loss. Middle Market Stressed: Slightly lower home sale values than the City_s average, and have not shown significant sales price appreciation. Vacancies and foreclosure rates are high, and the rate of population loss has increased in this market type, according to the 2010 Census data. Distressed Market: , Have experienced significant deterioration of the housing stock. This market category contains the highest vacancy rates and the lowest homeownership rates, compared to the other market types. It also has experienced some of the most substantial population losses in the City during the past decade.

  12. d

    Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No...

    • datarade.ai
    Updated Nov 7, 2023
    + more versions
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    APISCRAPY (2023). Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No Infra Cost | Pre-built AI & Automation | 50% Cost Saving | Free Sample [Dataset]. https://datarade.ai/data-products/zillow-real-estate-data-extraction-real-time-real-estate-ma-apiscrapy
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 7, 2023
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Spain, Bulgaria, Iceland, Isle of Man, Liechtenstein, Albania, Croatia, Portugal, Canada, Belgium
    Description

    Note:- Only publicly available data can be worked upon

    APISCRAPY collects and organizes data from Zillow's massive database, whether it's property characteristics, market trends, pricing histories, or more. Because of APISCRAPY's first-rate data extraction services, tracking property values, examining neighborhood trends, and monitoring housing market variations become a straightforward and efficient process.

    APISCRAPY's Zillow real estate data scraping service offers numerous advantages for individuals and businesses seeking valuable insights into the real estate market. Here are key benefits associated with their advanced data extraction technology:

    1. Real-time Zillow Real Estate Data: Users can access real-time data from Zillow, providing timely updates on property listings, market dynamics, and other critical factors. This real-time information is invaluable for making informed decisions in a fast-paced real estate environment.

    2. Data Customization: APISCRAPY allows users to customize the data extraction process, tailoring it to their specific needs. This flexibility ensures that the extracted Zillow real estate data aligns precisely with the user's requirements.

    3. Precision and Accuracy: The advanced algorithms utilized by APISCRAPY enhance the precision and accuracy of the extracted Zillow real estate data. This reliability is crucial for making well-informed decisions related to property investments and market trends.

    4. Efficient Data Extraction: APISCRAPY's technology streamlines the data extraction process, saving users time and effort. The efficiency of the extraction workflow ensures that users can access the desired Zillow real estate data without unnecessary delays.

    5. User-friendly Interface: APISCRAPY provides a user-friendly interface, making it accessible for individuals and businesses to navigate and utilize the Zillow real estate data scraping service with ease.

    APISCRAPY provides real-time real estate market data drawn from Zillow, ensuring that consumers have access to the most up-to-date and comprehensive real estate insights available. Our real-time real estate market data services aren't simply a game changer in today's dynamic real estate landscape; they're an absolute requirement.

    Our dedication to offering high-quality real estate data extraction services is based on the utilization of Zillow Real Estate Data. APISCRAPY's integration of Zillow Real Estate Data sets it different from the competition, whether you're a seasoned real estate professional or a homeowner wanting to sell, buy, or invest.

    APISCRAPY's data extraction is a key element, and it is an automated and smooth procedure that is at the heart of the platform's operation. Our platform gathers Zillow real estate data quickly and offers it in an easily consumable format with the click of a button.

    [Tags;- Zillow real estate scraper, Zillow data, Zillow API, Zillow scraper, Zillow web scraping tool, Zillow data extraction, Zillow Real estate data, Zillow scraper, Zillow scraping API, Zillow real estate da extraction, Extract Real estate Data, Property Listing Data, Real estate Data, Real estate Data sets, Real estate market data, Real estate data extraction, real estate web scraping, real estate api, real estate data api, real estate web scraping, web scraping real estate data, scraping real estate data, real estate scraper, best real, estate api, web scraping real estate, api real estate, Zillow scraping software ]

  13. Annual home price appreciation in the U.S. 2025, by state

    • statista.com
    Updated Aug 11, 2025
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    Statista (2025). Annual home price appreciation in the U.S. 2025, by state [Dataset]. https://www.statista.com/statistics/1240802/annual-home-price-appreciation-by-state-usa/
    Explore at:
    Dataset updated
    Aug 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    House prices grew year-on-year in most states in the U.S. in the first quarter of 2025. Hawaii was the only exception, with a decline of **** percent. The annual appreciation for single-family housing in the U.S. was **** percent, while in Rhode Island—the state where homes appreciated the most—the increase was ******percent. How have home prices developed in recent years? House price growth in the U.S. has been going strong for years. In 2025, the median sales price of a single-family home exceeded ******* U.S. dollars, up from ******* U.S. dollars five years ago. One of the factors driving house prices was the cost of credit. The record-low federal funds effective rate allowed mortgage lenders to set mortgage interest rates as low as *** percent. With interest rates on the rise, home buying has also slowed, causing fluctuations in house prices. Why are house prices growing? Many markets in the U.S. are overheated because supply has not been able to keep up with demand. How many homes enter the housing market depends on the construction output, whereas the availability of existing homes for purchase depends on many other factors, such as the willingness of owners to sell. Furthermore, growing investor appetite in the housing sector means that prospective homebuyers have some extra competition to worry about. In certain metros, for example, the share of homes bought by investors exceeded ** percent in 2025.

  14. T

    China Newly Built House Prices YoY Change

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2023
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    TRADING ECONOMICS (2023). China Newly Built House Prices YoY Change [Dataset]. https://tradingeconomics.com/china/housing-index
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    May 15, 2023
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 2011 - Jul 31, 2025
    Area covered
    China
    Description

    Housing Index in China decreased by 2.80 percent in July from -3.20 percent in June of 2025. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  15. D

    Luxury Real Estate Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Luxury Real Estate Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-luxury-real-estate-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Luxury Real Estate Market Outlook




    The global luxury real estate market size was valued at approximately USD 289.6 billion in 2023 and is projected to reach around USD 515.3 billion by 2032, growing at a CAGR of 6.5% from 2024 to 2032. The growth of this market is primarily driven by increasing urbanization, rising disposable incomes, and a growing number of high-net-worth individuals (HNWIs) worldwide.




    One of the primary growth factors contributing to the expansion of the luxury real estate market is the surge in the population of high-net-worth individuals. According to recent data, the number of millionaires and billionaires is increasing globally, especially in emerging economies. This demographic tends to invest heavily in luxury properties to diversify their asset portfolios and leverage real estate as a stable investment. Additionally, many of these HNWIs are inclined towards acquiring properties in prime locations, further fueling the demand for high-end real estate.




    Another significant factor driving the luxury real estate market is the growing trend of second homes and vacation properties. With the rise in global travel and tourism, affluent individuals are purchasing luxury vacation homes in exotic locations, such as beachfront properties, mountain retreats, and exclusive urban residences. This trend is particularly evident in regions like the Mediterranean, the Caribbean, and Southeast Asia. The availability of luxury amenities, coupled with the desire for privacy and exclusivity, makes these properties highly attractive investments.




    Technological advancements and the adoption of smart home technologies have also played a crucial role in the growth of the luxury real estate market. High-end properties are increasingly equipped with state-of-the-art home automation systems, energy-efficient solutions, and top-notch security features. These technological innovations not only enhance the living experience but also significantly boost the property's market value. Furthermore, the integration of eco-friendly and sustainable building practices in luxury properties is becoming a growing trend, appealing to environmentally conscious buyers.



    The concept of Property Franchise is gaining traction in the luxury real estate sector, offering a unique business model that combines the benefits of franchising with the lucrative potential of high-end properties. By leveraging established brand names and proven business systems, property franchises provide investors with a structured approach to entering the luxury market. This model allows franchisees to tap into the expertise and resources of a larger network, while maintaining the flexibility to cater to local market demands. As the luxury real estate market continues to expand, property franchises are becoming an attractive option for entrepreneurs seeking a foothold in this competitive industry. The ability to offer a consistent brand experience across various locations is a key advantage, appealing to both investors and clients looking for reliability and prestige in their property transactions.




    From a regional perspective, the Asia Pacific region is witnessing substantial growth in the luxury real estate market. Countries such as China, India, and Australia are experiencing rapid urbanization and economic growth, leading to an increasing demand for luxury properties. In North America, the United States and Canada continue to dominate the market, driven by strong economic fundamentals and high levels of disposable income. Europe remains a key player in the luxury real estate market, with cities like London, Paris, and Berlin attracting global investors due to their historical significance and robust real estate infrastructure. The Middle East and Africa region is also emerging as a significant market, particularly in cities like Dubai and Cape Town, renowned for their luxury real estate offerings.



    Property Type Analysis




    The luxury real estate market can be segmented by property type into residential, commercial, and industrial properties. The residential segment dominates the luxury real estate market, driven by the high demand for luxurious homes, villas, and apartments in prime locations. High-net-worth individuals and affluent families seek exclusive residential properties that offer privacy, security, and top-notch amenities. The trend of owning multiple residen

  16. l

    San Diego Real Estate Market Data August 2025

    • luxurysocalrealty.com
    html
    Updated Aug 8, 2025
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    LUXURYSOCALREALTY (2025). San Diego Real Estate Market Data August 2025 [Dataset]. https://www.luxurysocalrealty.com/blog/san-diego-real-estate-market/
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    LUXURYSOCALREALTY
    Time period covered
    Aug 2025
    Area covered
    Description

    Comprehensive dataset of San Diego real estate prices, trends, and market metrics for August 2025

  17. T

    United States FHFA House Price Index

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States FHFA House Price Index [Dataset]. https://tradingeconomics.com/united-states/housing-index
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1991 - Jun 30, 2025
    Area covered
    United States
    Description

    Housing Index in the United States decreased to 433.80 points in June from 434.60 points in May of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  18. T

    United States House Price Index YoY

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 15, 2025
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    TRADING ECONOMICS (2025). United States House Price Index YoY [Dataset]. https://tradingeconomics.com/united-states/house-price-index-yoy
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1992 - Jun 30, 2025
    Area covered
    United States
    Description

    House Price Index YoY in the United States decreased to 2.60 percent in June from 2.90 percent in May of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

  19. F

    Housing Inventory: Median Days on Market in Hot Springs, AR (CBSA)

    • fred.stlouisfed.org
    json
    Updated Jul 31, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in Hot Springs, AR (CBSA) [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMAR26300
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 31, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    Hot Springs, Arkansas
    Description

    Graph and download economic data for Housing Inventory: Median Days on Market in Hot Springs, AR (CBSA) (MEDDAYONMAR26300) from Jul 2016 to Jul 2025 about Hot Springs, AR, median, and USA.

  20. M

    Global Lenticular Filter Housing Market Industry Best Practices 2025-2032

    • statsndata.org
    excel, pdf
    Updated Jul 2025
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    Stats N Data (2025). Global Lenticular Filter Housing Market Industry Best Practices 2025-2032 [Dataset]. https://www.statsndata.org/report/lenticular-filter-housing-market-42139
    Explore at:
    pdf, excelAvailable download formats
    Dataset updated
    Jul 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The Lenticular Filter Housing market is witnessing substantial growth as industries increasingly prioritize efficient filtration solutions. These specialized housings, designed to hold lenticular filter cartridges, are integral to various applications including water treatment, pharmaceuticals, food and beverage pro

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2025). Fastest growing housing markets worldwide 2024 [Dataset]. https://www.statista.com/statistics/1041586/price-growth-fastest-growing-home-markets-worldwide/
Organization logo

Fastest growing housing markets worldwide 2024

Explore at:
Dataset updated
May 28, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Turkey experienced the highest annual change in house prices in 2024, followed by Bulgaria and Russia. In the fourth quarter of the year, the nominal house price in Turkey grew by **** percent, while in Bulgaria and Russia, the increase was ** and ** percent, respectively. Meanwhile, many countries saw prices fall throughout the year. That has to do with an overall cooling of the global housing market that started in 2022. When accounting for inflation, house price growth was slower, and even more countries saw the market shrink.

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