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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.
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TwitterIn the United States, interest rates for all mortgage types started to increase in 2021. This was due to the Federal Reserve introducing a series of hikes in the federal funds rate to contain the rising inflation. In the fourth quarter of 2024, the 30-year fixed rate rose slightly, to **** percent. Despite the increase, the rate remained below the peak of **** percent in the same quarter a year ago. Why have U.S. home sales decreased? Cheaper mortgages normally encourage consumers to buy homes, while higher borrowing costs have the opposite effect. As interest rates increased in 2022, the number of existing homes sold plummeted. Soaring house prices over the past 10 years have further affected housing affordability. Between 2013 and 2023, the median price of an existing single-family home risen by about ** percent. On the other hand, the median weekly earnings have risen much slower. Comparing mortgage terms and rates Between 2008 and 2023, the average rate on a 15-year fixed-rate mortgage in the United States stood between **** and **** percent. Over the same period, a 30-year mortgage term averaged a fixed-rate of between **** and **** percent. Rates on 15-year loan terms are lower to encourage a quicker repayment, which helps to improve a homeowner’s equity.
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The US residential real estate market, a cornerstone of the American economy, is projected to experience steady growth over the next decade. While the provided CAGR of 2.04% is a modest figure, it reflects a market maturing after a period of significant expansion. This sustained growth is driven by several key factors. Firstly, population growth and urbanization continue to fuel demand for housing, particularly in densely populated areas and emerging suburban markets. Secondly, low interest rates (historically, though this can fluctuate) have made mortgages more accessible, stimulating buyer activity. Thirdly, a robust construction sector, though facing challenges in material costs and labor shortages, is gradually increasing the housing supply, mitigating some of the upward pressure on prices. However, challenges remain. Rising inflation and potential interest rate hikes pose a risk to affordability, potentially dampening demand. Furthermore, the ongoing evolution of remote work is reshaping residential preferences, with a shift toward larger homes in suburban or exurban locations. This trend impacts the relative demand for various property types, potentially increasing the appeal of landed houses and villas compared to apartments and condominiums in certain regions. The segmentation of the market into apartments/condominiums and landed houses/villas provides crucial insights into consumer preferences and investment strategies. High-density urban areas will continue to see strong demand for apartments and condos, while suburban and rural areas are likely to experience a greater increase in landed property sales. Major players like Simon Property Group, Mill Creek Residential, and others are strategically adapting to these trends, focusing on both development and management across various property types and geographic locations. Analyzing regional data within the US (e.g., comparing growth in the Northeast versus the Southwest) will highlight market nuances and potential investment opportunities. While the global data provided is valuable for understanding broader market forces, focusing the analysis on the US market allows for a more granular understanding of the specific drivers, trends, and challenges within this significant segment of the real estate sector. The forecast period (2025-2033) suggests continued, albeit measured, expansion. Recent developments include: May 2022: Resource REIT Inc. completed the sale of all of its outstanding shares of common stock to Blackstone Real Estate Income Trust Inc. for USD 14.75 per share in an all-cash deal valued at USD 3.7 billion, including the assumption of the REIT's debt., February 2022: The largest owner of commercial real estate in the world and private equity company Blackstone is growing its portfolio of residential rentals and commercial properties in the United States. The company revealed that it would shell out about USD 6 billion to buy Preferred Apartment Communities, an Atlanta-based real estate investment trust that owns 44 multifamily communities and roughly 12,000 homes in the Southeast, mostly in Atlanta, Nashville, Charlotte, North Carolina, and the Florida cities of Jacksonville, Orlando, and Tampa.. Key drivers for this market are: Investment Plan Towards Urban Rail Development. Potential restraints include: Italy’s Fragmented Approach to Tenders. Notable trends are: Existing Home Sales Witnessing Strong Growth.
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TwitterHouse 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.
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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.
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Key information about House Prices Growth
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TwitterDataset 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?
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The equivalents of tables 581 to 588 are now published by the Office for National Statistics in the http://www.ons.gov.uk/peoplepopulationandcommunity/housing/bulletins/housepricestatisticsforsmallareas/previousReleases" class="govuk-link">house price statistics for small areas series and tables 576 to 578 in the https://www.ons.gov.uk/peoplepopulationandcommunity/housing/bulletins/housingaffordabilityinenglandandwales/previousReleases" class="govuk-link">housing affordability series.
Tables 531, 542, 563, 575 and 580 have been discontinued and are no longer being updated.
<p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute">MS Excel Spreadsheet</span>, <span class="gem-c-attachment_attribute">91 KB</span></p>
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TwitterGlobal house prices experienced a significant shift in 2022, with advanced economies seeing a notable decline after a prolonged period of growth. The real house price index (adjusted for inflation) for advanced economies peaked at nearly *** index points in early 2022 before falling to around ****** points by the fourth quarter of 2024. This represents a reversal of the upward trend that had characterized the housing market for roughly a decade. Conversely, real house prices in emerging economies resumed growing, after a brief correction in the second half of 2022. What is behind the slowdown? Inflation and slow economic growth have been the primary drivers for the cooling of the housing market. Secondly, the growing gap between incomes and house prices since 2012 has decreased the affordability of homeownership. Last but not least, homebuyers in 2024 faced dramatically higher mortgage interest rates, further contributing to worsening sentiment and declining transactions. Some markets continue to grow While many countries witnessed a deceleration in house price growth in 2022, some markets continued to see substantial increases. Turkey, in particular, stood out with a nominal increase in house prices of over ** percent in the first quarter of 2024. Other countries that recorded a two-digit growth include Russia and the United Arab Emirates. When accounting for inflation, the three countries with the fastest growing residential prices in early 2024 were the United Arab Emirates, Poland, and Bulgaria.
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TwitterSoaring interest rates are filtering through to the housing market, with lenders raising mortgage rates and pulling deals. What effect is this having on the housing market?
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TwitterThis paper shows that a macro model with segmented financial markets can generate sizable movements in housing prices in response to changes in credit conditions. We establish theoretically that reductions in mortgage rates always have a positive effect on prices, whereas the relaxation of loan-to-value constraints has ambiguous effects. A quantitative version of the model under perfect foresight accounts for about one-half of the observed price increase in the United States in the 2000s. When we include shocks to expectations about housing finance conditions, the model's ability to match house values improves significantly. The framework reconciles the observed disconnect between house prices and rents since, in general equilibrium, financial shocks can decrease rents and increase prices.
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30 Year Mortgage Rate in the United States decreased to 6.58 percent in August 14 from 6.63 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.
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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.
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This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.
Historical daily stock prices (open, high, low, close, volume)
Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)
Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)
Feature engineering based on financial data and technical indicators
Sentiment analysis data from social media and news articles
Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
Researchers investigating the effectiveness of machine learning in stock market prediction
Analysts developing quantitative trading Buy/Sell strategies
Individuals interested in building their own stock market prediction models
Students learning about machine learning and financial applications
The dataset may include different levels of granularity (e.g., daily, hourly)
Data cleaning and preprocessing are essential before model training
Regular updates are recommended to maintain the accuracy and relevance of the data
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Housing Index in the United States decreased to 434.40 points in May from 435.10 points in April 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.
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The global residential real estate market size was valued at approximately $9.7 trillion in 2023 and is projected to reach an astounding $15.4 trillion by 2032, growing at a compound annual growth rate (CAGR) of 5.2%. This growth is driven by several factors, including increasing urbanization, rising disposable incomes, and the ongoing global shift towards homeownership as a stable investment. Demographic shifts, such as the growing number of nuclear families and millennials entering the housing market, also contribute significantly to this upward trend.
One of the primary growth factors for the residential real estate market is the increasing urbanization across the globe. As more people migrate to urban areas in search of better job opportunities and a higher standard of living, the demand for residential properties in cities continues to rise. This trend is particularly pronounced in developing countries, where rapid economic growth is accompanied by significant rural-to-urban migration. Additionally, the trend of urban redevelopment and the creation of smart cities are further fueling the demand for modern residential properties.
Another crucial growth factor is the rise in disposable incomes and improved access to financing options. With strong economic growth in many parts of the world, individual incomes have been rising, allowing more people to afford homeownership. Financial institutions are also playing a critical role by offering a variety of mortgage products with attractive interest rates and flexible repayment terms. This increased access to capital has enabled a broader section of the population to invest in residential real estate, thereby expanding the market.
Technological advancements and the digital transformation of the real estate sector are also contributing to market growth. The proliferation of online platforms and real estate technology (proptech) solutions has made the process of buying, selling, and renting properties more efficient and transparent. Virtual tours, online mortgage applications, and blockchain for property transactions are some of the innovations revolutionizing the industry. These technological advancements not only improve the customer experience but also attract tech-savvy millennials and Gen Z buyers.
Regionally, the Asia-Pacific region is experiencing significant growth in the residential real estate market. Countries like China and India, with their large populations and rapid urbanization, are at the forefront of this expansion. Government initiatives aimed at providing affordable housing and improving infrastructure are also playing a pivotal role. In contrast, mature markets like North America and Europe are witnessing steady growth driven by economic stability and continued investment in housing. Meanwhile, regions like Latin America and the Middle East & Africa are also showing promise, albeit at a slower pace, due to varying economic conditions and market maturity levels.
The residential real estate market is segmented by property type, including single-family homes, multi-family homes, condominiums, townhouses, and others. Single-family homes are the most traditional and widespread type of residential property. They are particularly popular in suburban areas where space is more abundant. The demand for single-family homes continues to be driven by the desire for privacy, larger living spaces, and the ability to customize the property. These homes appeal especially to families with children and those looking to invest in a long-term residence.
Multi-family homes, which include duplexes, triplexes, and apartment buildings, are gaining traction, particularly in urban settings. These properties are attractive due to their potential for generating rental income and their ability to house multiple tenants. Investors find multi-family homes appealing as they offer a higher return on investment (ROI) compared to single-family homes. Additionally, the increasing trend of co-living and shared housing arrangements has bolstered the demand for multi-family properties in cities.
Condominiums, or condos, are another significant segment within the residential real estate market. Condos are particularly popular in urban areas where land is scarce and expensive. They offer a balance between affordability and amenities, making them an attractive option for young professionals and small families. Condominiums often come with added benefits such as maintenance services, security, and shared facilities like gyms and swimmin
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The USA home loan market is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. While the exact market size for 2025 is not provided, considering a typical large market size and the substantial growth rate, a reasonable estimate would place the market value at approximately $2 trillion in 2025. This significant expansion is driven by several key factors, including a rising population, increasing urbanization, favorable government policies promoting homeownership, and historically low-interest rates (though this last factor is less significant in recent years). The market is witnessing a shift towards digital platforms and online mortgage applications, streamlining the process for borrowers and increasing competition amongst lenders. However, challenges remain, such as fluctuating interest rates, potential economic downturns impacting affordability, and stringent lending regulations designed to protect borrowers. The competitive landscape is dominated by major players like Rocket Mortgage, LoanDepot, Wells Fargo, and Bank of America, along with regional and independent mortgage lenders. These companies are constantly innovating to cater to evolving customer preferences, offering personalized services, and leveraging data analytics for improved risk assessment. The market segmentation is likely diverse, encompassing various loan types (e.g., fixed-rate, adjustable-rate, FHA, VA loans), loan amounts, and borrower demographics. Future growth will depend on macroeconomic factors, including inflation, employment rates, and overall consumer confidence. Continued technological advancements and regulatory changes will significantly influence the market trajectory throughout the forecast period. Key drivers for this market are: Increase in digitization in mortgage lending market, Increase in innovations in software designs to speed up the mortgage-application process. Potential restraints include: Increase in digitization in mortgage lending market, Increase in innovations in software designs to speed up the mortgage-application process. Notable trends are: Growth in Nonbank Lenders is Expected to Drive the Market.
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Research in modelling housing market dynamics using agent-based models (ABMs) has grown due to the rise of accessible individual-level data. This research involves forecasting house prices, analysing urban regeneration, and the impact of economic shocks. There is a trend towards using machine learning (ML) algorithms to enhance ABM decision-making frameworks. This study investigates exogenous shocks to the UK housing market and integrates reinforcement learning (RL) to adapt housing market dynamics in an ABM. Results show agents can learn real-time trends and make decisions to manage shocks, achieving goals like adjusting the median house price without pre-determined rules. This model is transferable to other housing markets with similar complexities. The RL agent adjusts mortgage interest rates based on market conditions. Importantly, our model shows how a central bank agent learned conservative behaviours in sensitive scenarios, aligning with a 2009 study, demonstrating emergent behavioural patterns.
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Key information about House Prices Growth
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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.