New Connecticut counties, er... regions

This regards those new Connecticut "county equivalents" or "planning regions."
My apologies if this issue has already been covered and I overlooked it.
www.federalregister.gov/.../change-to-county-equivalents-in-the-state-of-connecticut

Some users have helpfully pointed out how data for the new areas can be aggregated from lower-level geographies, such as county subdivisions.
Which is fine, if one has the data at those more detailed geo levels.

But what about the wealth of useful data published at the county levels (such as health indicators)?  How might we convert new data for the "county equivalents" back to the previous CT county structure so it can be used with pre-existing data for analysis, comparison, reporting, trends, etc.  We don't want to leave a big hole for the state of Connecticut until all agencies and companies switch over to the new counties in a year or two.
Or when we switch over to the new CT regions to include in our list of all US counties, how should we convert data for the earlier CT counties to its new CT equivalent geographies?

The only workable solution I can imagine to convert new CT counties to previous counties (and vice versa) is to create an allocation table which shows the percent of each existing CT county in the new regions/equivalents.  The value for allocation would be either area or population.

Anyone have a better idea?  Would this approach give "good enough" estimates of the new counties?

Thanks,
Bert Sperling
bestplaces.net

Parents
  • This is the general approach I use in Geocorr. You can allocate by area or population, but in practice, I almost never use area.

    Here are a couple of tables I just made. One is a list showing (2020) county and (2022) planning region for each block in CT. The smaller file is a list of allocation factors (afacts), based on 2020 block populations, between counties and planning regions.

    Eventually I'll add the new CT regions to Geocorr, but there are a number of unanswered questions. For example, will CT tracts be renumbered? We're used to the assumption that tract numbers are unique within a county, but not between counties. I haven't checked, but there could now be duplicate tract numbers within a planning region. Conversely, if the tract numbers and geoids will remain the same, we won't be able to derive a tract's planning region by looking at the first five digits of the geoid. 

    [hmm, can't seem to attach a file... I'll post to MCDC site]

    Link to block file: https://mcdc.missouri.edu/data/georef/CT_blocks_county_region_equivalency_2022.csv

    Link to allocation factor file: https://mcdc.missouri.edu/data/georef/CT_county20_region22_allocation_factors.csv

    From our "georef" collection: https://mcdc.missouri.edu/cgi-bin/uexplore?/data/georef 

    EDIT: is correct, allocation is far from perfect -- especially because of the assumption of uniformity. Unfortunately it's sometimes the best we've got to work with.

Reply
  • This is the general approach I use in Geocorr. You can allocate by area or population, but in practice, I almost never use area.

    Here are a couple of tables I just made. One is a list showing (2020) county and (2022) planning region for each block in CT. The smaller file is a list of allocation factors (afacts), based on 2020 block populations, between counties and planning regions.

    Eventually I'll add the new CT regions to Geocorr, but there are a number of unanswered questions. For example, will CT tracts be renumbered? We're used to the assumption that tract numbers are unique within a county, but not between counties. I haven't checked, but there could now be duplicate tract numbers within a planning region. Conversely, if the tract numbers and geoids will remain the same, we won't be able to derive a tract's planning region by looking at the first five digits of the geoid. 

    [hmm, can't seem to attach a file... I'll post to MCDC site]

    Link to block file: https://mcdc.missouri.edu/data/georef/CT_blocks_county_region_equivalency_2022.csv

    Link to allocation factor file: https://mcdc.missouri.edu/data/georef/CT_county20_region22_allocation_factors.csv

    From our "georef" collection: https://mcdc.missouri.edu/cgi-bin/uexplore?/data/georef 

    EDIT: is correct, allocation is far from perfect -- especially because of the assumption of uniformity. Unfortunately it's sometimes the best we've got to work with.

Children
No Data