- Volume 19, Number 2
- Managing Editor: Mark D. Shroder
- Associate Editor: Michelle P. Matuga
Debra L. Brucker
University of New Hampshire
Veronica E. Helms
U.S. Department of Housing and Urban Development
The views expressed in this article are those of the authors and do not represent the official positions or policies of the U.S. Department of Housing and Urban Development or the U.S. government.
Data Shop, a department of Cityscape, presents short articles or notes on the uses of data in housing and urban research. Through this department, the Office of Policy Development and Research introduces readers to new and overlooked data sources and to improved techniques in using well-known 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 firstname.lastname@example.org for consideration.
Housing policy researchers studying the intersection of housing and disability must understand the relative strengths and limitations of the various types of administrative and survey data that can be used to identify persons with disabilities. This article describes traditional ways that disability has been measured in U.S. Department of Housing and Urban Development (HUD) administrative data and in relevant federally funded household surveys in the United States, while also highlighting newly available linked administrative survey data that can better identify persons with disabilities who participate in HUD-assisted housing programs. The article addresses various methods of measuring disability, including measures that are common across data sources (such as the sequence of six disability questions now included in the American Community Survey, American Housing Survey, and other federally funded surveys) and measures that are unique to specific sources of data (including HUD administrative data linked with population health surveys that include more detail on activity, functional, and social limitations). The article also discusses the strengths and limitations of various measures.
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