to undertake an analysis of this nature. The example below assumes that the year is 2016.


Strategies for Using the ACS An initial strategy for BIG CITY’s planners to consider, assuming that Area X is contained within a single PUMA and hence represents a large proportion of the PUMA’s population, is to use the ACS 3-year period estimates for the PUMA as a proxy to track population growth and changes in socioeconomic composition of Area X. In fall 2016, 3-year period estimates for the PUMA could be compared for, say, 2007–2009, 2010–2012, and 2013–2015. While 1-year period estimates would also be available for the PUMA, they might not be sufficiently precise for the purpose—see Table 2-7a. A variant of this strategy would be to average two years of 1-year period estimates for the PUMA and compare the 2-year averages for, say, 2006–2007, 2008–2009, 2010–2011, 2012–2013, and 2014–2015.

The analysts would need to consider three potential problems that could affect the results. First, the head count and age, race, and sex composition of the population would likely differ for the PUMA before and after the 2010 census because of inaccuracies in the pre-2010 population controls (see Section G). Second, because the PUMA in this example is a subcity area and not a county, the sampling error of its estimates would likely be higher than if it had benefited from PUMA-level population controls rather than the county-level controls used in the ACS. Third, the PUMA in this example is somewhat larger than Area X, and it is possible that the PUMA population outside Area X differs from the Area X population in ways that could affect the results.

A second strategy would be for the planners to use the ACS 5-year period estimates for an aggregation of the census tracts or block groups making up Area X. The combined 5-year period estimates could then be compared for, say, 2006–2010 and 2011–2015. Again, corrections to the population controls from the 2010 census could distort the precensus and postcensus comparisons.

A combined strategy could make good use of all of the available data. In such a strategy, comparing the 5-year period estimates for the census tracts making up Area X to the 5-year period estimates for the larger PUMA could help assess the validity of using 3-year (or 2- or 1-year) period estimates for the entire PUMA as a proxy for Area X. The advantage of being able to use 2-year or 3-year period estimates is that they will better capture trends than the 5-year period estimates that average the data over a longer time span.

Whichever strategy the planners ultimately select, the availability of ACS estimates would be a vast improvement over the current situation in which indirect or partial measures of change had to suffice. The ACS data



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