5-Yr PUMA Geography

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.

Jonathan, thanks for your note. Will there be an announcement when IPUMS releases the single PUMA geography? 

We will announce to registered IPUMS users by email, but sometimes there's a week or two delay between release and the email. You can also occasionally check the Revision History page on the site for current status.

Some insider info: we're on track for a release this Thursday or Friday. It's fully prepped but there are some technical hold-ups on the deployment. I'm not sure, but it sounds like our IT team will get those worked out soon.

That's great to hear, I'm excited to use the new PUMAs in the 2022 5yr survey for the older data for a question I'm working on. I have a tangential question.

In my work I've been using the tidycensus, survey, and srvyr packages in R and calling the data through ACS API. I'm using it because of the resources available on how to use these to get margins of error as recommended by the census bureau (primarily: https://walker-data.com/tidycensus/articles/pums-data.html and https://walker-data.com/census-r/introduction-to-census-microdata.html).

My question is, do you know of similar resources that walk a novice R user on how to do similar manipulations and summarizations of IPUMS microdata that include error estimates? Or perhaps a crosswalk of how IPUMS should be handled differently than the data extracted from ACS to get the margin of error using replicate weights (since the survey and srvyr packages do that automatically).

Thank you,

Meghan

That's great to hear, I'm excited to use the new PUMAs in the 2022 5yr survey for the older data for a question I'm working on. I have a tangential question.

In my work I've been using the tidycensus, survey, and srvyr packages in R and calling the data through ACS API. I'm using it because of the resources available on how to use these to get margins of error as recommended by the census bureau (primarily: https://walker-data.com/tidycensus/articles/pums-data.html and https://walker-data.com/census-r/introduction-to-census-microdata.html).

My question is, do you know of similar resources that walk a novice R user on how to do similar manipulations and summarizations of IPUMS microdata that include error estimates? Or perhaps a crosswalk of how IPUMS should be handled differently than the data extracted from ACS to get the margin of error using replicate weights (since the survey and srvyr packages do that automatically).

Thank you,

Meghan

If I am understanding your question correctly, you are interested in sample code for applying replicate weights to the ACS PUMS available from IPUMS USA to generate empirically derived standard errors for your estimates. IPUMS USA offers both the household (REPWT) and the person (REPWTP) replicate weights through their data access system. This IPUMS USA replicate weights summary page provides a bit of background information as well as sample code for applying replicate weights in R with the srvyr package.