Rationale for making comparisons using non-overlapping periods

Hi ACS friends, 

I'm trying to explain to some brilliant but non-ACS-knowledgeable coworkers and others why the recommended approach is to use *non-overlapping* periods when making comparisons over time.  I've looked at the Census doc (https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html) and all I can find is the guidance that says Do use non-overlapping datasets, Do not use overlapping datasets.  I'm having a hard time finding the why.  All I can come up with is this:

4-5ths of the sample is the same in adjacent datasets, e.g., 2014-2018 vs. 2015-2019. You can think of Census removing respondents from 2014, and adding respondents from 2019, but the respondents from 2015, 2016, 2017, and 2018 are the same. We should compare two completely different datasets, which means two non-overlapping periods.

I'm curious how others answer this question as well!  -Diana

Top Replies

Parents
  • There are the following statements in the document https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf:

    "TIP: As shown in Figure 3.1, consecutive 5-year estimates
    contain 4 years of overlapping coverage (for
    example, the 2010–2014 ACS 5-year estimates share
    sample data from 2011 through 2014 with the 2011–
    2015 ACS 5-year estimates). Because of this overlap,
    users should use extreme caution in making comparisons
    with consecutive years of multiyear estimates."

    "TIP: In general, ACS 1-year data are more likely to
    show year-to-year fluctuations, while consecutive
    5-year estimates are more likely to show a smooth
    trend, because 4 of the 5 years in the series overlap
    from one year to the next.".

    "When using ACS 1-year data, these comparisons are
    generally straightforward. Using multiyear estimates to
    look at trends for small populations can be challenging
    because they rely on pooled data for 5 years. For
    example, comparisons of 5-year estimates from 2010
    to 2014 and 2011 to 2015 are unlikely to show much difference
    because four of the years overlap; both sets of
    estimates include the same data collected from 2011
    through 2014. The Census Bureau suggests comparing 5-year estimates that do not overlap—for example, comparing
    2006–2010 ACS 5-year estimates with 2011–2015
    ACS 5-year estimates."

Reply
  • There are the following statements in the document https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf:

    "TIP: As shown in Figure 3.1, consecutive 5-year estimates
    contain 4 years of overlapping coverage (for
    example, the 2010–2014 ACS 5-year estimates share
    sample data from 2011 through 2014 with the 2011–
    2015 ACS 5-year estimates). Because of this overlap,
    users should use extreme caution in making comparisons
    with consecutive years of multiyear estimates."

    "TIP: In general, ACS 1-year data are more likely to
    show year-to-year fluctuations, while consecutive
    5-year estimates are more likely to show a smooth
    trend, because 4 of the 5 years in the series overlap
    from one year to the next.".

    "When using ACS 1-year data, these comparisons are
    generally straightforward. Using multiyear estimates to
    look at trends for small populations can be challenging
    because they rely on pooled data for 5 years. For
    example, comparisons of 5-year estimates from 2010
    to 2014 and 2011 to 2015 are unlikely to show much difference
    because four of the years overlap; both sets of
    estimates include the same data collected from 2011
    through 2014. The Census Bureau suggests comparing 5-year estimates that do not overlap—for example, comparing
    2006–2010 ACS 5-year estimates with 2011–2015
    ACS 5-year estimates."

Children
No Data