fweight or pweight for IPUMS analysis in Stata?

I’m currently doing some analysis with the IPUMS-USA ACS data and am looking for some advice on which weights are appropriate to use in Stata. I’m looking to do individual-level analysis, so I am working with the PERWT variable. As this variable reflects the population represented by each individual in the sample, it at first seemed to me like frequency weights (fweight) were appropriate, and simple tabulations in Stata seemed to support this.

However, after searching around the web for more documentation, the consensus (while sparse) seems to be that probability weights (pweight) should be used instead, and that I should first svyset the data before performing any analysis. My principal reference is from Stack Overflow, here: http://stackoverflow.com/questions/5446078/frequency-weighting-in-r-comparing-results-with-stata

So, here’s what I’m gathering from the online discussions and my readings of Stata:

  1. For simple tabulations that represent the US population, use frequency weights (fweight).

  2. For any statistical calculation (mean, regression, etc.), use the probability weights (pweight).

Am I understanding this correctly? Thanks for your advice.

In general, you will want to use the probability weight (pweight). However, fweight can be used to generate simple counts and frequencies. The counts should be identical under either specification, and fweight can sometimes be faster.

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