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.

Description:

This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.

Key Features:

• BROKERTITLE: Title of the broker
• TYPE: Type of the house
• PRICE: Price of the house
• BEDS: Number of bedrooms
• BATH: Number of bathrooms
• PROPERTYSQFT: Square footage of the property
• ADDRESS: Full address of the house
• STATE: State of the house
• MAIN_ADDRESS: Main address information
• ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
• LOCALITY: Locality information
• SUBLOCALITY: Sublocality information
• STREET_NAME: Street name
• LONG_NAME: Long name
• FORMATTED_ADDRESS: Formatted address
• LATITUDE: Latitude coordinate of the house
• LONGITUDE: Longitude coordinate of the house

Potential Use Cases:

• Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
• Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
• Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
• Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
• Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.

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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.

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.

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.

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.

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.

Real Estate Market size was valued at USD 79.7 Trillion in 2024 and is projected to reach USD 103.6 Trillion by 2031, growing at a CAGR of 5.1% during the forecasted period 2024 to 2031

Global Real Estate Market Drivers

Population Growth and Urbanization: In order to meet the demands of businesses, housing needs, and infrastructure development, there is a constant need for residential and commercial properties as populations and urban areas rise.

Low Interest Rates: By making borrowing more accessible, low interest rates encourage both individuals and businesses to make real estate investments. Reduced borrowing costs result in reduced mortgage rates, opening up homeownership and encouraging real estate investments and purchases.

Economic Growth: A thriving real estate market is a result of positive economic growth indicators like GDP growth, rising incomes, and low unemployment rates. Robust economies establish advantageous circumstances for real estate investment, growth, and customer assurance in the housing sector. Job growth and income increases: As more people look for rental or purchase close to their places of employment, housing demand is influenced by these factors. The housing market is driven by employment opportunities and rising salaries, which in turn drive home buying, renting, and property investment activity. Infrastructure Development: The demand and property values in the surrounding areas can be greatly impacted by investments made in infrastructure projects such as public facilities, utilities, and transportation networks. Accessibility, convenience, and beauty are all improved by improved infrastructure, which encourages real estate development and investment.

Government Policies and Incentives: Tax breaks, subsidies, and first-time homebuyer programs are a few examples of government policies and incentives that can boost the real estate market and homeownership. Market stability and growth are facilitated by regulatory actions that promote affordable housing, urban redevelopment, and real estate development.

Foreign Investment: Foreign capital can be used to stimulate demand, diversify property portfolios, and pump capital into the real estate market through direct property purchases or real estate investment funds. Foreign investors are drawn to the local real estate markets by favorable exchange rates, stable political environments, and appealing returns.

Demographic Trends: Shifting demographic trends affect housing preferences and demand for various property kinds. These trends include aging populations, household formation rates, and migration patterns. It is easier for real estate developers and investors to match supply with changing market demand when they are aware of demographic fluctuations.

Technological Innovations: New technologies that are revolutionizing the marketing, transactions, and management of properties include digital platforms, data analytics, and virtual reality applications. In the real estate industry, technology adoption increases market reach, boosts customer experiences, and increases operational efficiency.

Environmental Sustainability: Decisions about real estate development and investment are influenced by the growing knowledge of environmental sustainability and green building techniques. Market activity in environmentally aware real estate categories is driven by demand for eco-friendly neighborhoods, sustainable design elements, and energy-efficient buildings.

There are a large number of Housing spreadsheets that provide the latest, most useful or most popular data, presented by type and other variables, including by geographical area or on a temporal basis. These spreadsheets are mostely produced from statistical returns completed by Local Authorities, although some are from survey data or external sources.

This dataset represents indicators of local housing market strengths and to appropriately match neighborhood strategies to market conditions, for the best use of public and private resources. To leave feedback or ask a question about this dataset, please fill out the following form: 2011 Housing Market Typology feedback form.

A dataset of indicators of the state of the UK housing market

This is a collection of indicators from diverse sources on different aspects of the state of the UK housing market. Some indicators are updated monthly, others quarterly.

Publication of this dataset began in August 2012. The choice of which indicators are included in this dataset may be subject to revision, but the intention is to update the dataset regularly as new data become available.

Historical time series have been added for some (but not yet all) of the indicators.

In 2023, approximately 50 percent of homes sold in Texas, United States fell in the 200,000 to 399,999 U.S. dollar price class. Luxury homes valued at over one million U.S. dollars were almost four percent of all sales. The housing market in Texas grew substantially between 2011 and 2023, with both sales volumes and house prices increasing notably.

The municipality’s assessment of the housing market situation for young people, aged 19-25, in the municipality. Balance, surplus or deficit of housing. Housing deficits do not always mean that there are housing social problems such as overcrowding or extensive subletting as a widespread phenomenon. Housing deficits can mean that there is a dynamic economy in the municipality, where increased income leads to increased demand for housing. The fact that a municipality reports a deficit on housing means in many cases that it is difficult to move to, or within the municipality. surplus of housing means that there are constantly more vacant dwellings, or homes for sale, than is demanded. The existence of unleashed apartments in a single residential area does not necessarily mean that the local housing market is characterised by a surplus. A surplus of housing does not necessarily mean that there are suitable housing in relation to the demand and/or need in the municipality.

The global second-hand housing trading platform market is experiencing robust growth, driven by increasing urbanization, rising disposable incomes, and the growing preference for online real estate transactions. The market's expansion is fueled by technological advancements, such as improved mobile applications and advanced search functionalities, that enhance user experience and streamline the buying and selling process. Furthermore, the integration of virtual tours and 3D modeling provides potential buyers with immersive experiences, reducing the need for physical viewings and accelerating transaction times. Competition is fierce, with established players like Zillow, Rightmove, and Realtor.com vying for market share alongside emerging local and international platforms. The market is segmented geographically, with variations in growth rates influenced by factors such as local regulations, economic conditions, and technological adoption rates. While challenges exist, such as regulatory hurdles and the need for robust fraud prevention measures, the overall market outlook remains positive, projecting substantial growth over the forecast period. The success of individual platforms depends on several factors. These include the effectiveness of their marketing strategies, the breadth and accuracy of their property listings, the quality of their customer service, and the level of trust they build with users. The integration of innovative features, such as AI-powered property valuation tools and advanced data analytics, will be crucial for platforms aiming to gain a competitive edge. The market also shows potential for niche platforms targeting specific demographics or geographic areas. For example, platforms focusing on sustainable housing or catering to specific buyer needs (e.g., first-time homebuyers) could carve out significant market segments. Overall, strategic partnerships, technological innovation, and a strong focus on user experience will be key determinants of success within this dynamic and evolving market.

Graph and download economic data for All-Transactions House Price Index for Wisconsin (WISTHPI) from Q1 1975 to Q2 2025 about WI, appraisers, HPI, housing, price index, indexes, price, and USA.

Median price paid for residential property in England and Wales, by property type and administrative geographies. Annual data.

Affordable Housing Market Outlook

According to our latest research, the affordable housing market size reached USD 69.2 billion globally in 2024, driven by rapid urbanization, supportive government policies, and rising demand for cost-effective housing solutions. The market is projected to expand at a robust CAGR of 6.1% from 2025 to 2033, reaching an estimated USD 117.4 billion by the end of the forecast period. The growth is primarily attributed to increasing urban migration, widening income disparities, and a surge in public and private investments aimed at addressing the global housing deficit. As per our latest research, the affordable housing sector is undergoing significant transformation as stakeholders focus on innovative construction methods, sustainable materials, and digital technologies to streamline project delivery and reduce costs.

One of the primary growth drivers for the affordable housing market is the escalating rate of urbanization, particularly in emerging economies. Urban populations are swelling at an unprecedented pace, with millions migrating to cities in search of better employment opportunities and improved living standards. This mass migration has led to a surge in demand for affordable, quality housing, placing immense pressure on urban infrastructure and local governments. Consequently, both public and private sector players are ramping up investments in affordable housing projects, leveraging innovative financing models and partnerships to bridge the housing gap. Furthermore, the emergence of smart city initiatives and sustainable urban planning is fostering the development of integrated, affordable housing solutions that cater to the diverse needs of low- and middle-income populations.

Another significant factor propelling the affordable housing market is the increasing involvement of governments and international organizations in addressing the global housing crisis. Numerous policy interventions, such as subsidies, tax incentives, and relaxed regulatory frameworks, are being introduced to stimulate the supply of affordable homes. Governments are also collaborating with private developers through public-private partnerships (PPPs) to expedite project execution and ensure long-term sustainability. Additionally, multilateral agencies and non-governmental organizations are providing technical and financial assistance to support large-scale affordable housing initiatives, particularly in regions with acute housing shortages. These concerted efforts are not only enhancing access to affordable housing but also fostering socio-economic development and reducing urban poverty.

Technological advancements in construction methods and materials are further accelerating the growth of the affordable housing market. The adoption of modular and prefabricated construction techniques is enabling developers to deliver high-quality housing units at lower costs and within shorter timeframes. These innovative approaches are also contributing to improved energy efficiency, reduced environmental impact, and enhanced structural durability. Moreover, the integration of digital technologies, such as Building Information Modeling (BIM) and project management software, is streamlining the design, planning, and execution of affordable housing projects. As a result, stakeholders are increasingly embracing technology-driven solutions to optimize resource utilization, minimize risks, and ensure compliance with stringent regulatory standards.

From a regional perspective, Asia Pacific continues to dominate the affordable housing market, accounting for the largest share in 2024, followed by North America and Europe. The region's rapid urbanization, burgeoning population, and proactive government policies are driving significant investments in affordable housing infrastructure. Countries such as China, India, and Indonesia are at the forefront, implementing ambitious housing schemes and leveraging innovative construction technologies to address the growing demand. Meanwhile, developed regions like North America and Europe are witnessing renewed interest in affordable housing, fueled by rising property prices, income inequality, and shifting demographic trends. Latin America and the Middle East & Africa are also emerging as promising markets, supported by favorable regulatory environments and increased foreign direct investments.

This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.

The average monthly asking rent per square foot of shopping center real estate in the leading markets in Texas increased between 2020 and 2024. Although this trend was observed in all four major markets, Austin recorded the highest rent in 2024, at 30.5 U.S. dollars per square foot. This was higher than both the national average and the average for the South region.

The Market Value Analysis (MVA) is a tool to help residents and policymakers identify and understand the elements of their local real estate markets. It is an objective, data-driven tool built on local administrative data and validated with local experts. With an MVA, public officials and private actors can more precisely target intervention strategies in weak markets and support sustainable growth in stronger markets.In 2023, Reinvestment Fund completed an update to the City of Dallas MVA. The first MVA study in the City of Dallas was conducted in 2018 and a new study was needed to update information on current housing market conditions in Dallas neighborhoods.This is a map of the 2023 Housing Market Value Analysis and Displacement Risk Ratio for the City of Dallas. The map displays affordability information related to housing such as household income and house prices within the context of determined market types A-I. The map also includes data variables related to displacement risk ratio, or the likelihood for residents in a housing area to be push out, or displaced. The analysis was completed by a contractor, Reinvestment Fund. The analysis and findings are provided on the 2023 Market Value Analysis storymap.