, Volume 54, Issue 1, pp 285–309 | Cite as

Measuring Residential Segregation With the ACS: How the Margin of Error Affects the Dissimilarity Index

  • Jeffrey NapieralaEmail author
  • Nancy Denton


The American Community Survey (ACS) provides valuable, timely population estimates but with increased levels of sampling error. Although the margin of error is included with aggregate estimates, it has not been incorporated into segregation indexes. With the increasing levels of diversity in small and large places throughout the United States comes a need to track accurately and study changes in racial and ethnic segregation between censuses. The 2005–2009 ACS is used to calculate three dissimilarity indexes (D) for all core-based statistical areas (CBSAs) in the United States. We introduce a simulation method for computing segregation indexes and examine them with particular regard to the size of the CBSAs. Additionally, a subset of CBSAs is used to explore how ACS indexes differ from those computed using the 2000 and 2010 censuses. Findings suggest that the precision and accuracy of D from the ACS is influenced by a number of factors, including the number of tracts and minority population size. For smaller areas, point estimates systematically overstate actual levels of segregation, and large confidence intervals lead to limited statistical power.


American Community Survey Residential segregation Dissimilarity index Segregation methodology 



An early version of this article was presented at the 2013 meeting of the Population Association of America. The authors thank Ruby Wang, Hui-Shien Tsao, and Jin-Wook Lee for providing research assistance. We also thank Richard Alba, Glenn Deane, Samantha Friedman, Timothy Gage, and Maria Krysan for their helpful comments and suggestions. The Center for Social and Demographic Analysis of the University at Albany provided technical and administrative support for this research through a grant from the National Institute of Child Health and Human Development (R24-HD044943).


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Copyright information

© Population Association of America 2017

Authors and Affiliations

  1. 1.Department of SociologyUniversity at Albany, State University of New YorkAlbanyUSA
  2. 2.Center for Social and Demographic AnalysisUniversity at Albany, State University of New YorkNew YorkUSA

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