Combining the ACS and the PRCS



I am researcher interested in combining the PRCS with the ACS, as I am interested in learning how nativity differences among Puerto Ricans are associated with different outcomes. I learned that the PRCS, as downloaded from the IPUMS USA website, does not have cluster and strata variables. So, I am wondering how to best account for the complex sample design of both surveys when doing my analysis.

Would you recommend me to create a value for the cluster and strata that identify respondents from the PRCS, so I can use the cluster and strata in my analysis? That is, to give the strata and cluster variables a random value for those interviewed by the PRCS. OR Would you recommend me to use the replicate weights instead?

I used the replicate weights for the mean estimations and regression analysis, which works fine. However, I am having problems running post-estimation commands after using the replicate weights because the STATA post-estimation commands are based on the assumption that the standard errors are linearized NOT brr.

I would appreciate your help about how to best account for the complex survey design of a sample from a dataset that combines the PRCS with the ACS.

Thanks in advance for your help,




In order to create cluster and strata for the PRCS samples, you can follow the same method as used to create them for ACS samples. For strata, you will need to concatenate STATEFIP and PUMA. For cluster, it can be generated like so: 1000000000*year+(serial*10)+datanum. Since datanum is unique across samples, this will allow you to create unique clusters after combining the ACS and PRCS samples.

I hope this helps.