The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Using the American Community Survey: Benefits and Challenges
TABLE 3-2 Example of Simple Method to Update ACS 5-Year Period Estimates for 2010–2014 to Latest Year (2014), Four Small Counties (A, B, C, D) in State X, Using Data for Two Public Use Microdata Areas (PUMAs)
Total Population (20% are school-age children)
Estimated Number of Poor School-Age Children
1. 5-year period ACS estimate, 2010–2014
2. 1-year period ACS estimate, 2014
Change in School-Age Poverty
3. Ratio of 2014 PUMA estimate to 2010–2014 PUMA estimate (line 2/line 1)
Estimated Number of Poor School-Age Children, 2014
4. For PUMAs: ACS 1-year period estimate (line 2) For counties: Simple method, using county ACS 5-year Period estimate and PUMA change ratio (line 1 × line 3)
How well does the simple method to update a 5-year average estimate of poor school-agechildren to the latest year work?
Assume that the actual number of poor school-age children for the four counties in 2014 is 2,100 for County A, 2,900 for County B, 800 for County C, and 1,300 for County D.
For Counties A and B in PUMA 1, which both experienced an increase in school-age poor children from the average 5-year estimate to the latest year (1,500 to 2,100 and 2,500 to 2,900, respectively), the simple updating method makes their 5-year period estimates more current.
For Counties C and D in PUMA 2, the simple method is less satisfactory. Because County C bucked the overall trend and had a decrease in school-age poor children (from 1,000 to 800), the PUMA 2 change ratio between the 2014 estimate and the 2010–2014 estimate is very small. Consequently, the simple updating method does not capture either the substantial decrease in school-age poor children in County C or the substantial increase in school-age poor children (1,000 to 1,300) in County D.
NOTE: See text on the need to understand and evaluate the assumptions that underlie any modeling procedure, even the simplest, before using a particular procedure to update ACS 5-year (or 3-year) period estimates to 1-year period estimates. The method illustrated assumes that the numbers of poor school-age children grew at the same rate for each county in a PUMA, or, alternatively, that each county’s share of poor school-age children in a PUMA remained the same over time.