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.

Local housing market statistics for Portland, Tennessee

This Data Set presents an in-depth analysis of property sales data in Vanderburgh County, Indiana, focusing on the dynamic real estate trends observed during the year 2013. The analysis provides valuable insights into the local real estate market, encompassing property types, values, conditions, buyer demographics, and critical trends Stakeholders can leverage these insights to make informed decisions and navigate the market effectively

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.

Local housing market statistics for Greensboro, North Carolina

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.

Local housing market statistics for Fort Campbell North, Kentucky

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 180 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.

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.

Graph and download economic data for Housing Inventory: Median Listing Price in Fairbanks, AK (CBSA) (MEDLISPRI21820) from Jul 2016 to Feb 2026 about Fairbanks, AK, listing, median, price, and USA.

The Office of the Assessor compiles property sales data to perform an annual property sales study to adjust calculated costs of property values based on local market conditions. This dataset includes property sales data obtained for annual sales studies from 2018 to the present. While only Valid Arm's Length transactions that occurred in the two years prior to when a given sales study is finalized are included in each study, this dataset includes all sales transactions obtained to perform the sales studies, whether or not the sales transactions met inclusion criteria for a study. More information about the Sales Study is available from the Office of the Assessor.Values in categorical fields such as 'Sales Instrument' are recorded based on State of Michigan CAMA standards at the time the value was recorded. Some variation in field value codes occurs over time as a related CAMA standard is updated. CAMA standards are available from the State of Michigan Department of Treasury State Tax Commission.Click here for the Analytics Hub visualization of Property Sales.

Local housing market statistics for San Francisco, California

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.

If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you

From the perspective of local market participants, local public and private investment prospects for real estate in the United States in 2023 were highest (****) in Nashville. Other areas with similarly high prospects for local investment in real estate were Dallas-Fort Worth and Raleigh-Durham. These cities also had some of the highest development prospects for real estate in the United States.

ATTOM’s Neighborhood & Subdivision Boundaries dataset delivers a nationwide, proprietary framework of hyperlocal Residential Real Estate Data, defining neighborhood and residential subdivision boundaries that reflect the consensus view of local residents. These boundaries are purpose-built for real estate search, analysis, and visualization use cases where traditional geographies such as ZIP Codes or cities lack sufficient precision.

Neighborhood and Residential Subdivision Boundaries represent socially recognized communities with familiar names and clearly defined extents. Research shows consumers strongly prefer hyperlocal search experiences, making these boundaries essential for modern real estate platforms, analytics, and market insights.

The dataset organizes neighborhoods into a four-level hierarchy, allowing properties to be associated with intuitive and locally meaningful geographies: - Macro Neighborhoods: Large areas covering major portions of a city - Neighborhoods: Core, commonly recognized city neighborhoods - Sub-Neighborhoods: Smaller, locally known areas within neighborhoods - Residential Subdivisions: Distinct housing developments such as condominiums or planned communities

Each boundary is meticulously researched and hand-digitized by ATTOM’s GIS Analysts using authoritative and local sources, including official city and county maps, MLS and Realtor websites, HOA materials, developer site plans, assessor subdivision data, satellite imagery, and direct visual verification through Google Street View. Boundaries are traced using reference layers such as streets, hydrography, administrative limits, and parcel boundaries to ensure accuracy and non-overlapping geometry.

This dataset provides the most precise and consumer-aligned geographic layer available for neighborhood-level property search, mapping, and analysis. Additional demographic, socioeconomic, crime, climate, and risk attributes can be linked through ATTOM’s Community Info product to enrich neighborhood and subdivision insights.

Real estate sales refer to the transactions in which properties, such as houses, apartments, land, or commercial buildings, are bought or sold. These transactions involve transferring the ownership of real estate from one party to another in exchange for a mutually agreed-upon price.

The real estate sales process typically involves several steps, including:

Listing: The property is listed for sale, usually by a real estate agent or broker. The listing includes details about the property, such as its location, size, features, and asking price.

Marketing: The property is marketed to potential buyers through various channels, such as online listings, advertising, open houses, and real estate agents' networks.

Offer and negotiation: Interested buyers make offers on the property, and negotiations take place to determine the final sale price and any additional terms and conditions.

Acceptance and contract signing: Once the buyer's offer is accepted, a purchase agreement or contract is drafted, outlining the terms of the sale. Both parties review and sign the contract.

Due diligence and inspections: The buyer conducts inspections, surveys, and other necessary investigations to ensure the property's condition and suitability meet their requirements. This may also include reviewing documents related to the property, such as title reports and property disclosures.

**Financing and appraisal: **If the buyer requires financing, they apply for a mortgage and the property may need to be appraised to determine its value for lending purposes.

Closing: The closing is the final stage where all parties involved, including the buyer, seller, real estate agents, attorneys, and lenders, meet to complete the transaction. The buyer pays the agreed-upon amount, and the seller transfers ownership of the property to the buyer.

It's important to note that real estate sales data can vary significantly based on location, property type, market conditions, and other factors. If you're looking for specific real estate sales data for a particular area or time period, it's best to consult local real estate market reports, government agencies, or real estate professionals who can provide you with accurate and up-to-date information.

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.

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.

Local housing market statistics for Chillicothe, Missouri

Unlock the Potential of U.S. National MLS Real Estate Data

Discover the wealth of information encapsulated in licensing bulk MLS (Multiple Listing Service) data, a cornerstone of the real estate realm. From property particulars to market trends, delve into the significance and multifaceted utility of MLS data across diverse industries.

MLS Real Estate Data includes:

• Property Information: Address, size, layout, condition, amenities, and more.
• Price History: Historical price changes, listing dates, and sales dates.
• Geographic Insights: Location, neighborhood information, school districts, and proximity to amenities.
• Property Photos: MLS images of properties (see the condition of a property inside and out.)
• Agent/Broker Information: Certain details about the listing agent or broker as well as their notes on properties.
• Market Dynamics: Data on local real estate market conditions, including inventory levels, price trends, and days on the market.