Below I have calculated the share of respondents in each ATUS sample whose EARNWEEK value was top coded at 2884.61. Generally, this represents the share of respondents whose exact EARNWEEK value is not known due to the top code imposed in the original data, but who earned weekly income of at least $2884.61. In all cases, I have restricted the dataset to only those who are in-universe for EARNWEEK. I did this by excluding respondents with EARNWEEK=99999.99 (see codes tab).
This first table is weighted using WT06 (for all samples except 2020) and WT20 (for 2020). I created a variable *topcoded—*a binary variable equal to one if EARNWEEK=2884.61. There are no values of EARNWEEK above this threshold in IPUMS ATUS data, with the exception of 2024, which we discussed in an earlier forum thread. I have used the svyset [pweight=weight] command to declare weights for the survey data and produce a weighted cross tabulation of year and the topcoded variable.
This represents the share of the population that had weekly earnings at or above 2884.61 each year. You can see that in the 2023 sample, 8.17 percent of individuals had weekly earnings at or above 2884.61. In Ivan’s post, he wrote that 8.2 percent of respondents had top-coded EARNWEEK values in 2023; it would be more accurate to say that about 8.2 percent of the U.S. population had weekly earnings of 2884.61 or more in 2023, as estimated using the ATUS data.
This second table is an unweighted cross tabulation of the topcoded variable and year. This represents the unweighted share of the sample that had weekly earnings at or above 2884.61 each year. This tells you how many individuals in the dataset are affected by topcoding.
