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Residential Real Estate Market Size 2025-2029

The residential real estate market size is forecast to increase by USD 485.2 billion at a CAGR of 4.5% between 2024 and 2029.

The market is experiencing significant growth, fueled by increasing marketing initiatives that attract potential buyers and tenants. This trend is driven by the rising demand for housing solutions that cater to the evolving needs of consumers, particularly in urban areas. However, the market's growth trajectory is not without challenges. Regulatory uncertainty looms large, with changing policies and regulations posing a significant threat to market stability. Notably, innovative smart home technologies, such as voice-activated assistants and energy-efficient appliances, are gaining traction, offering enhanced convenience and sustainability for homeowners.
As such, companies seeking to capitalize on the opportunities presented by the growing the market must navigate these challenges with agility and foresight. The residential construction industry's expansion is driven by urbanization and the rising standard of living in emerging economies, including India, China, Thailand, Malaysia, and Indonesia. By staying abreast of regulatory changes and implementing innovative marketing strategies, they can effectively meet the evolving needs of consumers and maintain a competitive edge. These regulatory shifts can impact everything from property prices to financing options, making it crucial for market players to stay informed and adapt quickly.

What will be the Size of the Residential Real Estate Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the dynamic housing market analysis, small flats continue to be a popular choice for both investors and first-time homebuyers, driven by affordability and urban growth. International investment in housing projects, including apartments and condominiums, remains strong, offering attractive investment returns. Real estate syndication and property management software facilitate efficient property ownership and management. Real estate loans, property insurance, and urban planning are essential components of the housing market, ensuring the development of affordable housing and addressing the needs of the middle class and upper middle class. Property disputes, property tax assessments, and real estate litigation are ongoing challenges, requiring careful attention from stakeholders.
Property search engines streamline the process of finding the perfect property, from studio apartments to luxury homes. Real estate auctions, land banking, and nano apartments are innovative solutions in the market, while property flipping and short sales provide opportunities for savvy investors. Urban growth and community development are key trends, with a focus on sustainable, planned cities and the integration of technology, such as real estate blockchain, into the industry. Developers secure building permits, review inspection reports, and manage escrow accounts during real estate transactions. Key services include contract negotiation, dispute resolution, and tailored investment strategies for portfolio management. Financial aspects cover tax implications, estate planning, retirement planning, taxdeferred exchanges, capital gains, tax deductions, and maintaining positive cash flow for sustained returns.

How is this Residential Real Estate Industry segmented?

The residential real estate industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Mode Of Booking

  Sales
  Rental or lease


Type

  Apartments and condominiums
  Landed houses and villas


Location

  Urban
  Suburban
  Rural


End-user

  Mid-range housing
  Affordable housing
  Luxury housing


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    Australia
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Mode Of Booking Insights

The sales segment is estimated to witness significant growth during the forecast period. The sales segment dominates the global residential real estate market and will continue to dominate during the forecast period. The sales segment includes the sale of any property that is majorly used for residential purposes, such as single-family homes, condos, cooperatives, duplexes, townhouses, and multifamily residences. With the growing population and urbanization, the demand for homes is also increasing, which is the major factor driving the growth of the sales segment. Moreover, real estate firms work with developers to sel

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.

The dataset "aus_real_estate.csv" encapsulates comprehensive real estate information pertaining to Australia, showcasing diverse attributes essential for property assessment and market analysis. This dataset, comprising 5000 entries across 10 distinct columns, offers a detailed portrayal of various residential properties in cities across Australia.

The dataset encompasses crucial factors influencing property valuation and purchase decisions. The 'Price' column represents the property's cost, spanning a range between $100,000 and $2,000,000. Attributes such as 'Bedrooms' and 'Bathrooms' highlight the accommodation specifics, varying from one to five bedrooms and one to three bathrooms, respectively. 'SqFt' denotes the square footage of the properties, varying between 800 and 4000 square feet, elucidating their size and spatial dimensions.

The 'City' column encompasses major Australian urban centers, including Sydney, Melbourne, Brisbane, Perth, and Adelaide, delineating the geographical distribution of the properties. 'State' further categorizes the locations into New South Wales (NSW), Victoria (VIC), Queensland (QLD), Western Australia (WA), and South Australia (SA).

The dataset encapsulates temporal information through the 'Year_Built' attribute, spanning from 1950 to 2023, providing insights into the age and vintage of the properties. Moreover, property types are delineated within the 'Type' column, encompassing variations such as 'Apartment,' 'House,' and 'Townhouse.' The binary 'Garage' column signifies the presence (1) or absence (0) of a garage, while 'Lot_Area' provides an understanding of the land area, ranging from 1000 to 10,000 square feet.

This dataset offers a comprehensive outlook into the Australian real estate landscape, facilitating multifaceted analyses encompassing property valuation, market trends, and regional preferences. Its diverse attributes make it a valuable resource for researchers, analysts, and stakeholders within the real estate domain, enabling robust investigations and informed decision-making processes regarding property investments and market dynamics in Australia.

The United States Residential Real Estate Market is Segmented by Property Type (Apartments and Condominiums, and Villas and Landed Houses), by Price Band (Affordable, Mid-Market and Luxury), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (Northeast, Midwest, Southeast, West and Southwest). The Market Forecasts are Provided in Terms of Value (USD)

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.

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes:

• Residential Real Estate Sales
• Mortgage Foreclosures
• Residential Vacancy
• Parcel Year Built
• Parcel Condition
• Building Violations
• Owner Occupancy
• Subsidized Housing Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

With Zillow Real Estate Data at its core, it excels in real-time Data Extraction, delivering up-to-the-minute and comprehensive Real Estate Market Data. APISCRAPY's Data Extraction services are your key to staying informed in today's fast-paced real estate landscape.

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.

Extract detailed property data points — address, URL, prices, floor space, overview, parking, agents, and more — from any real estate listings. The Rankings data contains the ranking of properties as they come in the SERPs of different property listing sites. Furthermore, with our real estate agents' data, you can directly get in touch with the real estate agents/brokers via email or phone numbers.

A. Usecase/Applications possible with the data:

1. Property pricing - accurate property data for real estate valuation. Gather information about properties and their valuations from Federal, State, or County level websites. Monitor the real estate market across the country and decide the best time to buy or sell based on data

2. Secure your real estate investment - Monitor foreclosures and auctions to identify investment opportunities. Identify areas within special economic and opportunity zones such as QOZs - cross-map that with commercial or residential listings to identify leads. Ensure the safety of your investments, property, and personnel by analyzing crime data prior to investing.

3. Identify hot, emerging markets - Gather data about rent, demographic, and population data to expand retail and e-commerce businesses. Helps you drive better investment decisions.

4. Profile a building’s retrofit history - a building permit is required before the start of any construction activity of a building, such as changing the building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Use building permits to profile a city’s building retrofit history.

5. Study market changes - New construction data helps measure and evaluate the size, composition, and changes occurring within the housing and construction sectors.

6. Finding leads - Property records can reveal a wealth of information, such as how long an owner has currently lived in a home. US Census Bureau data and City-Data.com provide profiles of towns and city neighborhoods as well as demographic statistics. This data is available for free and can help agents increase their expertise in their communities and get a feel for the local market.

7. Searching for Targeted Leads - Focusing on small, niche areas of the real estate market can sometimes be the most efficient method of finding leads. For example, targeting high-end home sellers may take longer to develop a lead, but the payoff could be greater. Or, you may have a special interest or background in a certain type of home that would improve your chances of connecting with potential sellers. In these cases, focused data searches may help you find the best leads and develop relationships with future sellers.

How does it work?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

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.

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.

Residential Real Estate Market is Segmented by Property Type (Apartments & Condominiums, and Landed Houses & Villas), by Price Band (Affordable, Mid-Market, and Luxury/Super-prime), by Business Model (Sales and Rental), by Mode of Sale (Primary and Secondary), and by Region (North America, South America, Europe, Asia-Pacific, and Middle East & Africa). The Market Forecasts are Provided in Terms of Value (USD).

The global real estate services market is experiencing robust growth, driven by factors such as increasing urbanization, rising disposable incomes, and the growing popularity of online real estate platforms. The market, currently valued at approximately $5 trillion in 2025, is projected to expand at a compound annual growth rate (CAGR) of 7% from 2025 to 2033, reaching an estimated value of $9 trillion by 2033. This growth is fueled by both the residential and commercial sectors, with significant contributions from various service types, including trading and rental services. The increasing demand for professional real estate services, particularly in emerging markets, further contributes to this expansion. Technological advancements, such as the integration of artificial intelligence and big data analytics, are transforming the industry, leading to increased efficiency and improved customer experiences. Key players are adopting innovative strategies like virtual tours and property management software to cater to the evolving needs of clients. Segmentation analysis reveals a significant share held by the residential sector within the application segment, while trading services constitute a larger portion of the overall service type segment. North America and Asia-Pacific currently dominate the market, but emerging economies in regions like South America and Africa are showing promising growth potential. The market's growth, however, is not without its challenges. Regulatory changes, economic fluctuations, and the cyclical nature of the real estate market pose potential restraints. Despite these challenges, the overall outlook for the real estate services market remains positive, with consistent growth projected throughout the forecast period. The increasing adoption of technology and the growing demand for specialized services across diverse geographical areas continue to drive market expansion. The industry is undergoing a transformation, and companies are adapting their strategies to remain competitive in this dynamic landscape. Successful businesses are effectively leveraging data analytics, enhancing customer engagement, and building strategic partnerships to capitalize on emerging opportunities and maintain a robust market position.

In 2017, the County Department of Economic Development, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for Allegheny County. A similar MVA was completed with the Pittsburgh Urban Redevelopment Authority in 2016. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

The 2016 Allegheny County MVA does not include the City of Pittsburgh, which was characterized at the same time in the fourth update of the City of Pittsburgh’s MVA. All calculations herein therefore do not include the City of Pittsburgh. While the methodology between the City and County MVA's are very similar, the classification of communities will differ, and so the data between the two should not be used interchangeably.

Allegheny County's MVA utilized data that helps to define the local real estate market. Most data used covers the 2013-2016 period, and data used in the analysis includes:

•Residential Real Estate Sales; • Mortgage Foreclosures; • Residential Vacancy; • Parcel Year Built; • Parcel Condition; • Owner Occupancy; and • Subsidized Housing Units.

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

During the research process, staff from the County and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

Please refer to the report (included here as a pdf) for more information about the data, methodology, and findings.

Snapshot img

Real Estate Market Size 2025-2029

The real estate market size is forecast to increase by USD 1,258.6 billion at a CAGR of 5.6% between 2024 and 2029.

The market is experiencing significant shifts and innovations, with both residential and commercial sectors adapting to new trends and challenges. In the commercial realm, e-commerce growth is driving the demand for logistics and distribution centers, while virtual reality technology is revolutionizing property viewings. Europe's commercial real estate sector is witnessing a rise in smart city development, incorporating LED lighting and data centers to enhance sustainability and efficiency. In the residential sector, wellness real estate is gaining popularity, focusing on health and well-being. Real estate software and advertising services are essential tools for asset management, streamlining operations, and reaching potential buyers. Regulatory uncertainty remains a challenge, but innovation in construction technologies, such as generators and renewable energy solutions, is helping mitigate risks.

What will be the Size of the Real Estate Market During the Forecast Period?

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The market continues to exhibit strong activity, driven by rising population growth and increasing demand for personal household space. Both residential and commercial sectors have experienced a rebound in home sales and leasing activity. The trend towards live-streaming rooms and remote work has further fueled demand for housing and commercial real estate. Economic conditions and local market dynamics influence the direction of the market, with interest rates playing a significant role in investment decisions. Fully furnished, semi-furnished, and unfurnished properties, as well as rental properties, remain popular options for buyers and tenants. Offline transactions continue to dominate, but online transactions are gaining traction.
The market encompasses a diverse range of assets, including land, improvements, buildings, fixtures, roads, structures, utility systems, and undeveloped property. Vacant land and undeveloped property present opportunities for investors, while the construction and development of new housing and commercial projects contribute to the market's overall growth.

How is this Real Estate Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Residential
  Commercial
  Industrial


Business Segment

  Rental
  Sales


Manufacturing Type

  New construction
  Renovation and redevelopment
  Land development


Geography

  APAC

    China
    India
    Japan
    South Korea


  North America

    Canada
    US


  Europe

    Germany
    UK


  South America

    Brazil


  Middle East and Africa

By Type Insights

The residential segment is estimated to witness significant growth during the forecast period.

The market encompasses the buying and selling of properties designed for dwelling purposes, including buildings, single-family homes, apartments, townhouses, and more. Factors fueling growth in this sector include the increasing homeownership rate among millennials and urbanization trends. The Asia Pacific region, specifically China, dominates the market due to escalating homeownership rates. In India, the demand for affordable housing is a major driver, with initiatives like Pradhan Mantri Awas Yojana (PMAY) spurring the development of affordable housing projects catering to the needs of lower and middle-income groups. The commercial real estate segment, consisting of office buildings, shopping malls, hotels, and other commercial properties, is also experiencing growth.

Furthermore, economic and local market conditions, interest rates, and investment opportunities in fully furnished, semi-furnished, unfurnished properties, and rental properties influence the market dynamics. Technological integration, infrastructure development, and construction projects further shape the real estate landscape. Key sectors like transportation, logistics, agriculture, and the e-commerce sector also impact the market.

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The Residential segment was valued at USD 1440.30 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 64% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions, Request Free Sample

The Asia Pacific region holds the largest share of The market, dr

The Europe Residential Real Estate Market is Segmented by Property Type (Apartments & Condominiums and Villas & Landed Houses), Price Band (Affordable, Mid-Market and Luxury), Mode of Sale (Primary and Secondary), Business Model (Sales and Rental) and Country (Germany, United Kingdom, France, Spain, Italy, Netherlands, Sweden, Denmark, Norway and Rest of Europe). The Market Forecasts are Provided in Terms of Value (USD).

Overview: This dataset was collected and curated to support research on predicting real estate prices using machine learning algorithms, specifically Support Vector Regression (SVR) and Gradient Boosting Machine (GBM). The dataset includes comprehensive information on residential properties, enabling the development and evaluation of predictive models for accurate and transparent real estate appraisals.Data Source: The data was sourced from Department of Lands and Survey real estate listings.Features: The dataset contains the following key attributes for each property:Area (in square meters): The total living area of the property.Floor Number: The floor on which the property is located.Location: Geographic coordinates or city/region where the property is situated.Type of Apartment: The classification of the property, such as studio, one-bedroom, two-bedroom, etc.Number of Bathrooms: The total number of bathrooms in the property.Number of Bedrooms: The total number of bedrooms in the property.Property Age (in years): The number of years since the property was constructed.Property Condition: A categorical variable indicating the condition of the property (e.g., new, good, fair, needs renovation).Proximity to Amenities: The distance to nearby amenities such as schools, hospitals, shopping centers, and public transportation.Market Price (target variable): The actual sale price or listed price of the property.Data Preprocessing:Normalization: Numeric features such as area and proximity to amenities were normalized to ensure consistency and improve model performance.Categorical Encoding: Categorical features like property condition and type of apartment were encoded using one-hot encoding or label encoding, depending on the specific model requirements.Missing Values: Missing data points were handled using appropriate imputation techniques or by excluding records with significant missing information.Usage: This dataset was utilized to train and test machine learning models, aiming to predict the market price of residential properties based on the provided attributes. The models developed using this dataset demonstrated improved accuracy and transparency over traditional appraisal methods.Dataset Availability: The dataset is available for public use under the [CC BY 4.0]. Users are encouraged to cite the related publication when using the data in their research or applications.Citation: If you use this dataset in your research, please cite the following publication:[Real Estate Decision-Making: Precision in Price Prediction through Advanced Machine Learning Algorithms].

In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies. Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016: • Median Sales Price • Variance of Sales Price • Percent Households Owner Occupied • Density of Residential Housing Units • Percent Rental with Subsidy • Foreclosures as a Percent of Sales • Permits as a Percent of Housing Units • Percent of Housing Units Built Before 1940 • Percent of Properties with Assessed Condition “Poor” or worse • Vacant Housing Units as a Percentage of Habitable Units The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources. During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

Graph and download economic data for Residential Property Prices for United States (QUSN368BIS) from Q1 1971 to Q1 2025 about residential, housing, price, and USA.

In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016:

• Median Sales Price

• Variance of Sales Price

• Percent Households Owner Occupied

• Density of Residential Housing Units

• Percent Rental with Subsidy

• Foreclosures as a Percent of Sales

• Permits as a Percent of Housing Units

• Percent of Housing Units Built Before 1940

• Percent of Properties with Assessed Condition “Poor” or worse

• Vacant Housing Units as a Percentage of Habitable Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.