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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:
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.
Note:- Only publicly available data can be worked upon
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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.
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CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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.
Context This dataset is a record of every building or building unit (apartment, etc.) sold in the California property market along with the customer data.
Content Real estate is property consisting of land and the buildings on it, along with its natural resources such as crops, minerals or water; immovable property of this nature; an interest vested in this (also) an item of real property, (more generally) buildings or housing in general.
Inspiration
What can you discover about California real estate by looking at a year's worth of raw transaction records? Can you spot trends in the market, or build a model that predicts sale value in the future?
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Existing Home Sales in the United States increased to 4010 Thousand in July from 3930 Thousand in June of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Gain a complete view of the real estate market with our Zillow datasets. Track price trends, rental/sale status, and price per square foot with the Zillow Price History dataset and explore detailed listings with prices, locations, and features using the Zillow Properties Listing dataset. Over 134M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:
Zpid
City
State
Home Status
Street Address
Zipcode
Home Type
Living Area Value
Bedrooms
Bathrooms
Price
Property Type
Date Sold
Annual Homeowners Insurance
Price Per Square Foot
Rent Zestimate
Tax Assessed Value
Zestimate
Home Values
Lot Area
Lot Area Unit
Living Area
Living Area Units
Property Tax Rate
Page View Count
Favorite Count
Time On Zillow
Time Zone
Abbreviated Address
Brokerage Name
And much more
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Single Family Home Prices in the United States decreased to 422400 USD in July from 432700 USD in June of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Silencio’s Street Noise-Level Dataset provides unmatched value for the real estate industry, delivering highly granular noise data to property professionals, developers, and investors. Built from over 35 billion datapoints collected globally via our mobile app and refined through AI-driven interpolation, this dataset offers hyper-local average noise levels (dBA) covering streets, neighborhoods, and venues across more than 200 countries.
Our data helps assess the environmental quality of any location, supporting residential and commercial property valuations, site selection, and urban development. By integrating real-world noise measurements with AI-powered models, we enable real estate professionals to evaluate how noise exposure impacts property value, livability, and buyer perception — factors often overlooked by traditional market analyses.
Silencio also operates the largest global database of noise complaints, providing additional context for understanding neighborhood soundscapes from both objective measurements and subjective community feedback.
We offer on-demand visual delivery for mapped cities, regions, or even specific streets and districts, allowing clients to access exactly the data they need. Data is available both as historical and up-to-date records, ready to be integrated into valuation models, investment reports, and location intelligence platforms. Delivery options include CSV exports, S3 buckets, PDF, PNG, JPEG, and we are currently developing a full-featured API, with flexibility to adapt to client needs. We are open to discussion for API early access, custom projects, or unique delivery formats.
Fully anonymized and fully GDPR-compliant, Silencio’s data ensures ethical sourcing while providing real estate professionals with actionable insights for smarter, more transparent valuations.
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This dataset provides a comprehensive record of property listing price changes over time, including detailed property attributes, location information, and event types for each price change. It enables in-depth analysis of real estate market dynamics, pricing strategies, and property value trends across regions and property types.
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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.
The Market Value Analysis (MVA) is a tool designed to assist the private market and government officials to identify and comprehend the various elements of local real estate markets. It is based fundamentally on local administrative data sources. By using an MVA, public sector officials and private market actors can more precisely craft intervention strategies in weak markets and support sustainable growth in stronger market segments.
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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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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.
The Market Value Analysis (MVA) is a tool designed to assist the private market and government officials to identify and comprehend the various elements of local real estate markets. It is based fundamentally on local administrative data sources. By using an MVA, public sector officials and private market actors can more precisely craft intervention strategies in weak markets and support sustainable growth in stronger market segments.
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License information was derived automatically
Housing Index in Saudi Arabia increased to 105 points in the second quarter of 2025 from 104.90 points in the first quarter of 2025. This dataset provides - Saudi Arabia Housing Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Multiple advantages with Home Owner Data Set: Increase campaign ROI with personalized and targeted engagements. Utilize predictive real estate data attributes such as home value, purchase date, property descriptors, and mortgage information. Focus resources on high-value prospects and their preferences Maximize conversions with personalized marketing campaigns featuring relevant real estate intelligence. Engage your target audience with messaging tailored to their interests and needs.
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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.
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Graph and download economic data for Households; Owner-Occupied Real Estate Including Vacant Land and Mobile Homes at Market Value, Market Value Levels (HOOREVLMHMV) from Q4 1945 to Q1 2025 about , and USA.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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:
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.