new data. Yet this design also provides the platform for important new applications that the long-form sample could not support.
This summary provides the panel’s general guidelines for using the ACS for such applications as fund allocation, program planning by federal, state, and local governments, transportation modeling, private-sector decision making, research on population and housing trends, and general public understanding. It then presents the panel’s recommendations to the Census Bureau for investment in the ACS and in user education and outreach that will be necessary to make the most effective use of the new data.
The panel encourages users to follow the general guidelines below in working with the ACS period estimates.
Always examine margins of error before drawing conclusions from a set of estimates.
Review the available information about nonsampling errors for estimates of interest and use this information in interpreting findings from the ACS.
Carefully consider the pros and cons of alternative strategies for extracting value from ACS 5-year period estimates for very small areas, such as aggregating small-area estimates into estimates for larger, user-defined areas.
When using ACS data to estimate shares of some total, compare estimates among areas or population groups, or assess trends over time, use ACS estimates that pertain to the same time period (1-year, 3-year, or 5-year) for all geographic areas or population groups that are being compared. Do not use a mixture of different period estimates.
When analyzing trends over time for an area or population group, use ACS 1-year period estimates whenever they are available and sufficiently precise for the purpose of interest and be cognizant of changes in geographic area boundaries that may affect comparability. Keep in mind that the sampling error for the estimate of the difference between pairs of 1-year period estimates will be larger than the sampling error of either estimate.
If only 3-year or 5-year period estimates are available or sufficiently precise, use them with care for analyzing trends over time for an area or population group. In general, avoid analyses of changes over time that are based on overlapping period estimates (for example, 5-year period estimates for 2010–2014 and 2011–2015).