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Activity Number: 18
Type: Topic Contributed
Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
Sponsor: Survey Research Methods Section
Abstract #311312 View Presentation
Title: Improving the American Community Survey Margins of Error Through Data-Driven Regionalization
Author(s): Seth Spielman*+ and David Folch
Companies: University of Colorado and University of Colorado
Keywords: American Community Survey ; GIS ; Spatial

This talk describes a method to improve the efficiency of small area demographic and economic estimates from the American Community Survey (ACS). Small area estimates from the ACS are terribly imprecise however it is possible to improve the precision of estimates via spatial (or temporal) aggregation. However, geographic aggregation of tracts can lead to significant information loss and a dilution of spatial patterns. The method presented here is a novel spatial optimization algorithm that improves small area estimates by intelligently grouping small areas while minimizing information loss and preserving spatial patterns. The algorithm allows the post-processing of public use data to to a user specified level of precision.

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