ACS Data Users Group

Hi all,

I'm brand new to the ACS Data Users Group and very excited to be a part of it! What an incredible wealth of resources.

I actually have a challenge that I've been running into while using PUMS. I've been using FactFinder for years, but have only started using PUMS in the last six months, so please forgive my lack of knowledge.

After reading your post, I ran a tabulation for MA on SSMC through Gateway To MAST (2014 data, Android/Kindle app). I suspect that you are calculating correctly, but that the self-reported incomes in the PUMS are high. I too would be interested in any insights the group has on this.

Hi Anise,

I'm happy to take a look. What you propose sounds roughly correct (keeping the householder record, using the household weight, using a weighted average). The most likely problem I can think if is that you're dropping cases with 0 income. Another problem that could have occurred is not adjusting the for number of years of data you use if by chance you combined more than one year of data.

As a new PUMS user, I highly recommend downloading the verification files and attempting to recreate the weighted estimates therein. Even better if you can reproduce the replicate weight standard errors. (See PUMS Estimates for User Verification: www.census.gov/.../documentation.html)

From there, I'd then try to reproduce estimates of mean household income for all households in Massachusetts and compare those against what you see in American FactFinder. This is a good way to benchmark your approach, though your PUMS estimate will differ slightly from the pre-tabulated results because you're using a smaller (public use) sample and, I think, incomes are rounded to protect confidentiality. (See Subject Definitions: www.census.gov/.../code-lists.html)

I'll see what I get when I get a moment, but you can send your code to palacios@cbpp.org as well.

Vincent

I absolutely agree with Vincent in validating your processing with the verification files, weighted estimates, and replicate weights. However, Gateway To MAST is spot on with those, and the incomes still come out high. I would be very interested if you find that your high numbers are a result of a significant error in your processing.

Related... You may want to check to see how your code is handling negative income levels. Reported household income can be negative or positive.

From what I can tell, these numbers are not that unreasonable. For 2016 1-year ACS data, table S1901 shows mean incomes by household type. (See: factfinder.census.gov/.../0400000US25)

From table S1901:
There are 2,579,398 households with a mean household income of $101,911.
There are 1,633,661 family households with a mean HHI of $122,310.
There are 1,194,726 married-couple family households with a mean HHI of $143,966.
There are 945,737 non-family households with a mean HHI of $62,500.

With weighted 2016 1-year ACS PUMS for MA I get:
There are 2,579,453 households with a mean household income of $101,593.
There are 1,634,746 family households with a mean HHI of $124,355.
There are 1,195,011 married-couple family households with a mean HHI of $144,204.
There are 944,707 non-family households with a mean HHI of $62,207.

-And for comparison, with PUMS-
There are 17,396 same-sex couple households with a mean HHI of $181,920.

Stata code:
...load data...
gen hincp_adj = hincp * adjinc/1000000
gen hh = 1
gen fam_hh = inrange(hht, 1, 3)
gen mcfam_hh = hht == 1
gen nonfam_hh = inrange(hht, 4, 7)
gen ssmc_hh = inlist(ssmc, 1, 2)
tab1 hh fam_hh mcfam_hh nonfam_hh ssmc_hh [fw=wgtp], sum(hincp_adj)

Speaking qualitatively, as someone familiar with the situation on the ground in Massachusetts I do not find the results here surprising. We have the fifth highest mean household income in the country and the fourth highest family median income. Two adults in a household who both have professional or union jobs could certainly earn salaries commensurate with these mean values. This is reflected to some extent in our ever soaring real estate values. The issue in Massachusetts lies more with the distribution of incomes rather than a lack of income overall.

Thanks for these recommendations Vincent! I will definitely download the verification files and attempt to recreate the weighted estimates. And I'll try to reproduce the replicate weight standard errors as well.

I'll send on the R script to that email address now--thanks for offering to take a look when you get a moment!

I ran a tabulation that breaks households into state (so you can just look at MA, or compare MA to other states), SSMC, and whether or not the reference person is white. I've tried including it in this post, but it says that .csv files are invalid. So I've put it on google drive here: drive.google.com/open

It's 2014 data, so expect some differences if you are using newer data. Line 135 shows you that in MA with a white reference person, the average household income for a same sex couple is about $164,000. With a non-white reference person (line 132) there is an average household income of $151,000. However, the sample size for line 132 is pretty tiny - there are only 10 (UW_hdrs) actual households in the sample in that category. For non same-sex couples with a white householder my numbers are quite a bit lower than yours ($76,000 for family income, $100,000 for household income, where you had $139,000 for household income). The tabulation has two levels (sections). The upper is household level information. If you want to know a bit about the people who live in those households, scroll down to the person level section (line 438 for MA).

If you have any questions (most people aren't used to working with 2 level MAST tabulations) feel free to ask.

John, this is great. Thanks for taking the time to pull that sheet together. It's interesting to see how MA compares to other states in your tabulation--very useful overview.

You are very welcome.

Curious to see your R script.

Happy to send it along! Where is best to send it? Or is it standard practice to post in groups? Not sure of the protocol...

When I'm working with open data like the ACS PUMS, I create a github repo and then use that to share since it provide a reproducible example. This site also has a messaging feature but I have been unsuccessful in using it. Dropbox etc. work too.