I'm wondering if anyone is familiar with the CHAS data set (a special tabulation of ACS data for HUD).
I'd prefer to use ACS data directly to calculate the CHAS estimate of housing problems (defined as a housing unit experiencing 1 of 4 housing problems including overcrowding, cost burden, lack of plumbing, or kitchen facilities). However it seems like CHAS is the only way to do so because it offers a unique count of the units experiencing at least 1 of 4 housing problems, where with ACS data there's potential overlap in the count of households (since they're separate questions). For example tabulating from ACS, if a unit had lack of plumbing, crowding and was cost burdened, it would appear that 3 units had problems whereas it should be counted as a single unit, having at least 1 of the 4 problems.
My conclusion was that CHAS avoids this and therefore I shouldn't/cannot use ACS, but I'm wondering if there's a way around it? Anyone else have experience with CHAS and know if I'm on the right track?
If the housing problem tabulation is your variable of interest, then yes, CHAS makes compiling that data very elegant because it filters out the overlapping responses. It can be done manually using a microdata…
Matt: The 2013-2017 data are out now: https://www.huduser.gov/portal/datasets/cp.html.
Elise: Interesting question. I don't know the answer, so I'll have to punt and say that if it's appropriate to do that…
Adding documentation about calculation of the CHAS income limits would be a great help to data users.
If the housing problem tabulation is your variable of interest, then yes, CHAS makes compiling that data very elegant because it filters out the overlapping responses. It can be done manually using a microdata file, but then you're unable to assess any areas smaller than a PUMA. It all really depends on your exact research question. Happy to discuss further.
Thanks Bryan! I'm only looking at state and US estimates for the general population as well as by race and ethnicity, so perhaps I could use a microdata file.