- American Housing Survey
- Volume 14 Number 1
- Managing Editor: Mark D. Shroder
- Associate Editor: Michelle P. Matuga
The Importance of Using Layered Data To Analyze Housing: The Case of the Subsidized Housing Information Project
, Michael Williams
, Furman Center for Real Estate and Urban Policy
New York University School of Law and Wagner School of Public Service
Data Shop, a department of Cityscape, presents short articles or notes on the uses of data in housing and urban research. Through this department, PD&R introduces readers to new and overlooked data sources and to improved techniques in using wellknown data. The emphasis is on sources and methods that analysts can use in their own work. Researchers often run into knotty data problems involving data interpretation or manipulation that must be solved before a project can proceed, but they seldom get to focus in detail on the solutions to such problems. If you have an idea for an applied, data-centric note of no more than 3,000 words, please send a one-paragraph abstract to email@example.com for consideration.
Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau or the Bureau of Labor Statistics. The research in this article does not use any confidential Census Bureau information.
The Furman Center for Real Estate and Urban Policy recently developed a new database through its Subsidized Housing Information Project (SHIP). The SHIP database combines more than 50 disparate data sets to catalogue every privately owned, publicly subsidized affordable rental property developed in New York City with financing and insurance from the U.S. Department of Housing and Urban Development (HUD), HUD projectbased rental assistance, New York City or State Mitchell-Lama financing, or the federal Low-Income Housing Tax Credit Program. The pooling and layering of data, as well as combining the data with other local housing and neighborhood information, in databases like the SHIP allow for a clearer understanding of the existing affordable housing stock and enable practitioners to more effectively target resources toward the preservation of affordable housing.
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