I am looking to calculate how many households in each state are under 200% of the poverty level. I am doing this by recoding HHINCOME into new variables for every household size based on poverty guideline income ranges that involve the number of household members (ex. 2 member households are under 200% of poverty level if their income is <31,860). I am using NUMPREC to determine household size and PERNUM=1 to represent the household. I put on the HHWT before I run crosstabs. However, whenever I weight the data, the amount of households becomes extremely high. For example, Alaska weighted has 556,440 households but in reality census says it’s only 250,185. Should the weighted number reflect reality? I am wondering if my use of weights is incorrect because I am looking at state-level data within a sample for the whole US?
How do I account for HHWT when looking at data about number of households in a state from sample w/ all states?
Calculating weighted state-level statistics shouldn’t be a problem for the household sample weight variable. I suspect the issue is that for household-level analysis you need to ensure that you have only one observation per household in your dataset. The easiest way to do this, with IPUMS USA data, is to simply keep any record with PERNUM==1. Once you do this, you should calculate population household counts much closer to the official published US Census counts.
I hope this helps. Let me know if you have any additional questions.