While detailed geographic information is an important component of data utility, sample size and privacy concerns can make release of small area statistics (e.g., census tract statistics) challenging. To address these issues, NORC is working to develop estimation methods that generate modeled estimates at lower levels of geography than are available in public use microdata sets, allowing for a much more detailed picture of person and housing characteristics than would have been otherwise possible.
As one example of the use of these methods, the visualization below shows modeled (census) tract-level measures of housing characteristics from the New York City Housing Vacancy Survey (NYCHVS). We also plot how these relate to a measure of gentrification taken from tract-level American Community Survey data so that users can examine how housing characteristics relate to gentrification. This tool won the Joint Statistical Meeting Data Expo 2019 prize in the professional category.
www.community.amstat.org/governmentstatisticssection/awards/dataexpo
NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, NORC has conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with NORC to transform increasingly complex information into useful knowledge.
www.norc.org
For more information please contact:
Eric Young
NORC Senior External Affairs Manager
young-eric@norc.org
(301) 634-9536
Quentin Brummet
Senior Research Methodologist
brummet-quentin@norc.org
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