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

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  • The general ACS handbook does say that "these comparisons can be made with caution" (footnote 19 on p. 17 of https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020.pdf). I vaguely recall someone mentioning once that what you're basically getting is the difference between the last year of the more recent dataset and the first year of the earlier dataset (so 2014 vs 2019, in your example).

    As Todd G noted, the usual significance tests don't work, but the Census Bureau used to provide a modification, which is multiplying the standard error of the difference by a factor that depends on the proportion of years that overlap. (Specifically, you subtract that proportion -- 4/5 = 0.8 in your example -- from 1 and take the square root.) I don't know if the Census Bureau is still publishing that guidance, but it does appear in the 2013-vintage ACS documentation (https://www2.census.gov/programs-surveys/acs/tech_docs/statistical_testing/2013StatisticalTesting3and5.pdf).

    So it's doable, but I don't know whether it's desirable. You could easily imagine this being used as a "magic" way to make single-year comparisons for geographies without one-year estimates, but keep in mind:

    • That modification to the usual significance tests is an approximation of an approximation (as I understand it). So there's more room for things to go awry.
    • On average, the ACS samples about 2% of households each year. In a census tract with 2,000 total households, that's only ~40 households. So: even if a change over time were statistically significant, I would hesitate to draw any firm conclusions about change between two years, especially if I'm looking at subgroups (for example, renter households, or households with Black householders).

    I'm looking forward to seeing other responses as well!

    --Matt

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  • The general ACS handbook does say that "these comparisons can be made with caution" (footnote 19 on p. 17 of https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020.pdf). I vaguely recall someone mentioning once that what you're basically getting is the difference between the last year of the more recent dataset and the first year of the earlier dataset (so 2014 vs 2019, in your example).

    As Todd G noted, the usual significance tests don't work, but the Census Bureau used to provide a modification, which is multiplying the standard error of the difference by a factor that depends on the proportion of years that overlap. (Specifically, you subtract that proportion -- 4/5 = 0.8 in your example -- from 1 and take the square root.) I don't know if the Census Bureau is still publishing that guidance, but it does appear in the 2013-vintage ACS documentation (https://www2.census.gov/programs-surveys/acs/tech_docs/statistical_testing/2013StatisticalTesting3and5.pdf).

    So it's doable, but I don't know whether it's desirable. You could easily imagine this being used as a "magic" way to make single-year comparisons for geographies without one-year estimates, but keep in mind:

    • That modification to the usual significance tests is an approximation of an approximation (as I understand it). So there's more room for things to go awry.
    • On average, the ACS samples about 2% of households each year. In a census tract with 2,000 total households, that's only ~40 households. So: even if a change over time were statistically significant, I would hesitate to draw any firm conclusions about change between two years, especially if I'm looking at subgroups (for example, renter households, or households with Black householders).

    I'm looking forward to seeing other responses as well!

    --Matt

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