using data to understand the past, present and future
Data Analysis & Decision Making through the URA Real Estate Department
The URA has partnered with Tolemi's BuildingBlocks analytical tool to aggregate property and market level data from city departments and authorities and guide strategic planning on:
- acquiring land/structure
- identifying nuisance properties
- providing real estate market level analysis
Like the URA, city agencies and authorities across the country use the BuildingBlocks user-friendly interface to identify, vet and prioritize properties for Land Bank activities; to inform strategic demolitions; to identify vacant structures; and to deploy policy and programmatic resources to stabilize property values.
BuildingBlocks allows the URA to:
• Perform quick analysis of tax delinquent/ building permits by geographic area
• Find vacant houses to include in the Treasurer's Sale
• See the market impact from a URA project
• Assist project managers in providing data for grants/proposals
• Work with property owners who have the most code violations and unpaid taxes
• And much more
Tolemi is a Boston-based "smart city" data analytics and web technology company that specializes in delivering mapping, visualizations, and performance/program evaluation solutions to the state and local government departments and agencies that administer urban development and real property. BuildingBlocks is their web-based solution that links city data sources and enterprise systems across departments and agencies to deliver critical analyses/insights that decision-makers use to align and prioritize policies, resources, and investments for property and neighborhood development.
Market Value Analysis
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 the highest-demand markets, areas of greatest distress, plus various markets types in 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 to help define the local real estate market between July, 2013 and June, 2016 including:
• Median sales price
• Variance of sales price
• Percent of owner-occupied households
• Density of residential housing units
• Percent of rentals with subsidies
• 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 of “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, our staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflected the market.
Click here to access the 2016 MVA via the Western Pennsylvania Regional Data Center website.