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This is a Non-Federal dataset covered by different Terms of Use than See Terms

Housing Market Value Analysis - Allegheny County Economic Development

Metadata Updated: January 24, 2023

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.

Access & Use Information

Public: This dataset is intended for public access and use. Non-Federal: This dataset is covered by different Terms of Use than See Terms License: No license information was provided.

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Metadata Created Date January 24, 2023
Metadata Updated Date January 24, 2023

Metadata Source

Harvested from WPRDC data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date January 24, 2023
Metadata Updated Date January 24, 2023
Publisher Allegheny County
Identifier 9088f03b-8b4f-479e-bbea-38710e6a2c0a
Data Last Modified 2021-12-15T20:31:49.856871
Category Housing & Properties
Public Access Level public
Metadata Context
Schema Version
Catalog Describedby
Harvest Object Id eaa567ce-edd1-414f-b6e8-04b7b629a663
Harvest Source Id 2b953a26-28c2-4190-ad6c-d0fdc8d2786d
Harvest Source Title WPRDC data.json
Source Datajson Identifier True
Source Hash 3e536d99ef2b1a41268c74548a47db8bb74466c0
Source Schema Version 1.1

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