An evaluation of the American Community Survey: results from the Oregon test site View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2006-06

AUTHORS

George C. Hough, David A. Swanson

ABSTRACT

The American Community Survey (ACS) is a Census Bureau product designed to provide accurate and timely demographic and economic indicators on an annual basis for both large and small geographic areas within the United States. Operational plans for Census 2010 call for ACS to replace the decennial census long form (Census LF), pending the results of evaluation studies. This plan represents a major change in that variables that traditionally have been collected on a “snapshot” basis once every 10 years would be collected on a “rolling” annual basis. Using a loss function analysis and other tools, this paper reports preliminary findings from a comparison of ACS and Census 2000 results in Multnomah County, Oregon, one of five national “local expert” test sites set up to compare ACS data collected at the time of Census 2000. The preliminary findings suggest that there are notable differences between some of the corresponding variables found in the ACS and Census LF that require more detailed examination. For example, the loss function analysis reveals notable differences for race and disability variables. In other comparisons of corresponding variables between ACS and Census 2000, differences are found within each of the four major areas of interest: (1) demographic characteristics, (2) social characteristics, (3) economic characteristics, and (4) housing characteristics, with housing characteristics showing the least similarity overall. These results also suggest that more detailed examinations are needed to understand differences between corresponding variables collected by ACS and the Census LF. More... »

PAGES

257-273

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11113-006-0007-1

DOI

http://dx.doi.org/10.1007/s11113-006-0007-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047226968


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