Proxy PUMAs

This is a list of 2 data frames giving PUMAs that make reasonable approximations of designated regions, with weights to apply to both population- and household-based measures. The data frame labeled county uses county-based PUMAs and 2021 ACS values; the data frame cog uses the new COG-based PUMAs and 2022 ACS values. When working with PUMS data or other weighted surveys, multiply the weights in the proxy table with the weights from the survey to account for how much of the PUMA overlaps the region. The county-based table includes just non-county regions (e.g. Greater New Haven), but the COG-based table also includes "legacy" counties (e.g. New Haven County), since we assume that even if data isn't released for counties, some organizations might still want estimates based on those geographies. See maps of proxies and their weights here: https://ct-data-haven.github.io/cogs/proxy-geos.html NOTE: There are some PUMAs that are included in more than one region. When joining these tables with survey data, make sure you're allowing for duplicates of PUMAs.

proxy_pumas

Format

A list of 2 data frames, county and cog, with 19 and 54 rows, respectively, and 6 variables:

puma

7-digit PUMA FIPS code

region

Region name

pop

Total population in the overlapping area between the region and the PUMA

hh

Total households in the overlapping area between the region and the PUMA

pop_weight

Population weight: share of the PUMA's population that's included in the region, to be used for population-based survey analysis

hh_weight

Household weight: share of the PUMA's households that are included in the region, to be used for household-based survey analysis

Source

2021 & 2022 5-year ACS

Examples

if (FALSE) {
# proxies made from county-based PUMAs, use for pre-2022 ACS or other datasets
proxy_pumas$county

# proxies made from COG-based PUMAs
proxy_pumas$cog
}