Hello, I am accessing the 5-Yr estimates for 2022 but not seeing that PUMAs are an option in the "Geography" Any ideas how to get this?
2022
2021
Update: IPUMS USA has now added PUMA identifiers to its version of the 2022 5-year sample through a single PUMA variable. Almost all the other geographic variables that we derive from PUMA information…
In New York the names are very long. My guess is they edited the PUMAs, but did not edit all of the names. PUMAs now are almost always a set of tracts. In the distant past they were created by Summary…
Yes, in MDAT, for the 2022 5-year PUMS, you'll find PUMA information through two _variables_, not geographies. The PUMA10 variable identifies 2010 PUMA codes for respondents from 2018 through 2021. PUMA20 identifies 2020 PUMA codes for respondents from 2022. This two-variable system will most likely continue for 5-year PUMS until the 2026 release when, once again, the 5-year PUMS will use only one set of PUMA definitions for the entire 5-year period. (MDAT uses the same setup for the 2012 through 2015 5-year PUMS releases, which also used two sets of PUMA definitions.)For IPUMS USA, we're working on providing PUMA codes for the 2022 5-year sample through a single "PUMA" variable (as we already do for the 2012 through 2015 5-year samples). We aim to release that update sometime in the next couple weeks. We have several other resources related to PUMAs and PUMA changes through our Geographic Tools & Resources page.
Thank you, Jonathan. I found the variable, but there is no detail with it. So, there is no telling which PUMA each row is.
As Jonathan indicate, the 2018-2022 PUMS data is a "mixed geography" file. There are 2 variables that don't exist in the 2017-2021 file, PUMA10 and PUMA20. The file is 4/5ths PUMA10 records and 1/5th PUMA20 records. This makes the 2022 5 year file pretty useless. You are better using the 2022 1-year PUMS data. For the API for the 2018-2022 you can't use the the "&for=public use microdata:PUMAFIPS" construction. You need to use "&for state=STATEFIPS" and the "subset" on PUMA10 or PUMA20 FIPS code records.
From the people at ACSO (American Community Survey Operations) :
Thank you David. I need to use the 5-yr estimate as I want to go down to the PUMA level (I actually want county data). But, this seems to not be an option with this file. Like I've stated, I used the PUMA20 or PUMA10 variable but its pretty useless, with the way I'm using it. The PUMA value does not show on the table.
Any ideas of how to accurately get to the county level for 2022 data?
Thank you,
Lorna
Dear Lorna,
If you look at my post about a Small Area Estimation (SAE) program that I wrote you can use the program to get county data. The problem is that a county may contain several PUMAs, This situation is pretty easy to handle you can just "add up" the tables for the relevant PUMAs. For PUMAs that cross county lines, which may contain parts of several counties, you are stuck. I wrote the SAE program to handle this situation. I start with PUMS data for all the relevant PUMAs (large area) and then I create PUMs like tract level data. Next I "stack" the tracts for the county that I want. There are many potential issues with this approach but it seems reasonable. You can then create any county table that you want using the synthetic data.
The current version of the program does not produce useful MOEs. I'm working on an extension the produces replicate weights. You can produce MOEs using the replicate weights. To do all this you need to be able to use "R" Do you have any experience with R ? If you work for a nonprofit 501(c)(3) or government you can get free support through my foundation dorerfoundation.org
Dave
Thanks again David. I think I will switch over and use the PUMS data with SAS. I need demographics by county/zip for 200% FPL. I'm VERY interested in in using the Supplemental poverty data though. Can you get me started? I work for the state of Washington, DSHS
I haven't used SAS in years and years so I don't recall how transferrable this resource is.... These two links were extremely helpful with using pums data in R.
https://walker-data.com/census-r/introduction-to-census-microdata.html
https://walker-data.com/tidycensus/articles/pums-data.html
Meghan