Hello! I am part of a research team that is exploring the use of CPS data as denominator data for industry, occupation, and some demographic variables for a single state (and looking at trends across 5 years; 2019-2023). Despite using the broadest industry and occupations variables available (A_MJIND and A_DTOCC from the March Supplement) we noticed that there are significant fluctuations in population totals from year to year. Is there any guidance on how to manage this issue? Is this a function of the survey design, changes in how industries and occupations are classified from year to year, the process of looking at small units (e.g., a specific industry within a single state), a combination of all of these factors, or something else? It looks like IPUMS provides data harmonization (to address issues of how variables change over time), but we’re really trying to get a handle on the best approach to obtaining denominator data (and whether the ACS might be preferable). Any thoughts or feedback is welcome. Thank you!
It would be helpful to see an example of how large these fluctuations are to determine if they are being caused by specifics in the data or in your analysis. While there will be some fluctuations year-to-year, especially for smaller industries and for those that are more responsive to changing economic conditions, using the major industry and occupation groups for state-level estimates should provide relatively stable results. These large groups should also not be affected by changes in classifications over this period of time.
If you do not require individual-level microdata for your denominator, then you might consider exploring the ACS geographically aggregated summary data on IPUMS NHGIS. These use larger samples from the American Community Survey and estimates often come with margins of error shared by the Census Bureau. Using the IPUMS NHGIS data finder tool, you can filter by topic to Occupation and Industry to find relevant tables for each individual year to add to your data cart (note that the 5-year period data are not for annual estimates). One that you may be interested in is table C24050 (Industry by Occupation for the Civilian Employed Population 16 Years and Over), which reports estimates of the number of workers across 13 major industry groups and five major occupation groups (see screenshot below).
In the following screenshot, I’ve combined results from the 2021, 2022, and 2023 industry by occupation tables and provided the labels from the codebook for a select number of industries in Minnesota. Employment appears to be mostly stable across years, with smaller industries such as Information showing greater volatility.
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