Comprehensive Housing Affordability Strategy (CHAS) data documenting the extent of housing problems and housing needs, particularly for low income households, at the Place level. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income).

2016-2020 ACS 5-Year estimates of housing characteristics compiled at the Tract level. These characteristics include Occupancy Status, Tenure By Household Size, Median Number Of Rooms By Tenure, Units In Structure, Tenure by Units In Structure, Tenure By Year Structure Built, Median Year Structure Built By Tenure, Bedrooms, Tenure By Bedrooms, Contract Rent, Median Contract Rent, Bedrooms By Gross Rent, Median Value, Mortgage Status By Median Value (Dollars), and Tenure By Selected Physical And Financial Conditions.

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.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled at the County level. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

Comprehensive Housing Affordability Strategy (CHAS) data documenting the extent of housing problems and housing needs, particularly for low income households, at the State level. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income).

2016-2020 ACS 5-Year estimates of housing characteristics compiled at the County level. These characteristics include Occupancy Status, Tenure By Household Size, Median Number Of Rooms By Tenure, Units In Structure, Tenure by Units In Structure, Tenure By Year Structure Built, Median Year Structure Built By Tenure, Bedrooms, Tenure By Bedrooms, Contract Rent, Median Contract Rent, Bedrooms By Gross Rent, Median Value, Mortgage Status By Median Value (Dollars), and Tenure By Selected Physical And Financial Conditions.

Comprehensive Housing Affordability Strategy (CHAS) data documenting the extent of housing problems and housing needs, particularly for low income households, at the County level. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income).

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