President, Population Association of America
Regents Professor, University of Minnesota
Director, Minnesota Population Center
The U.S. Census Bureau plans to discontinue the 3-year American Community Survey (ACS) data products as a cost-saving maneuver. Although the Census Bureau will continue to provide 1-year and 5-year ACS products, significant data will be lost.
The 3-year data provide a unique combination of spatial, temporal, and statistical precision, enabling a range of high-value analyses that the other ACS products cannot support. With a sample three times larger than 1-year ACS data, 3-year estimates have considerably smaller margins of error and are made available for nearly twice as many areas. Compared to 5-year data, 3-year data provide a degree of specificity that is crucial for some time series comparisons
The 3-year estimates may be used to analyze pre-recession (2005-2007), recession (2008-2010), and post-recession (2011-2013) characteristics of population and housing, summarizing shorter time periods than 5-year data and smaller areas (with at least 20,000 people) than 1-year data (with at least 65,000 people).
If you believe this change would significantly harm the nation's statistical infrastructure, you should make your feelings known by email:
Email James Treat, Chief of the American Community Survey Office, at firstname.lastname@example.org, and tell him how this elimination will negatively impact your research. Please be as specific as possible!
Email Katherine K. Wallman, Chief Statistician of the US Office of Management and Budget (OMB) at Katherine_K._Wallman@omb.eop.gov, and tell her how this cut will negatively impact your research. The OMB must approve the spending plan proposed by the Census Bureau.
For more details on the proposed discontinuation and how it would impact research, please see these posts:
The ACS 3-year Demographic Estimates Are History
Opportunities to Provide Input Regarding the Proposed Elimination of ACS 3-year Data Products
Census to Eliminate 3-year Estimates
If policy-makers, academics, and students explain why these data are important, we may save this critical element of the nation's statistical infrastructure. I urge you to send your comments to email@example.com and Katherine_K_Wallman@omb.eop.gov and copy us at firstname.lastname@example.org.