Status:Closed    Asked:Jul 31, 2017 - 12:54 PM

Why doesn't IPUMS have all the variables needed to analyze people who are not in the labor force?

We are interested in dis aggregating people not in the labor force by the following categories. All of these categories can be computed using exclusively NBER CPS basic (not asec) variables.
Don't want job - Fam Don't want job - School Don't want job - Retired
Don't want job - Dsiabled, ill
Don't want job - Othe r Variables needed for the above can be found in the BASIC NBER data set: PEMLR PENLFACT PRWNTJOB
Wan't job - did not search Variable needed for the above can be found in the BASIC NBER data set: PEDWLKO
Wan't job -Searched - not available Variable needed for the above can be found in the BASIC NBER data set: PEDWAVL
Want job - searched - Available (Marginally attached) Variable needed for the above can be found in the BASIC NBER data set: PEDWRSN Using the above categories/coding we hope to arrive at broad reasons for NILF (regardless of desire for job). NILF - School NILF - Family Duty NILF - Disabled/ ill NILF - Retired NILF -Other

  1. The only available variable in the IPUMS data set which is congruent with the above variables is WNLOOK. WNLOOK (similar to PEDWRSN in basic NBER), allows us to code the branch for marginally attached workers.
  2. However, the variables needed to code people who don't want a job (by the various reason) is not in the IPUMS data base (PENLFACT in the basic NBER). EMPSTAT is limited into three NILF categories (unable to work, other, retired) ; we would like to analyze those who are NILF by the additional reasons of school, ill. family duty.
  3. Variables such as A_WANTJOB/ NWLOOK/WHYNWLY are in the IPUMS ASEC data base. Although we could link the ASEC and basic to get at some of the categories we want, they are limiting. b) For instance, WHYNWLY and NWLOOKWK has a universe of people who 'did not work at all last year'. The universe we need is 'people who currently do not hold a job (and have not searched for one int the previous 4 weeks).

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Staff Answer


Jeff Bloem


Note that IPUMS CPS prioritizes making improvements to the already-available CPS data. The IPUMS CPS team is always adding new variables to the IPUMS database, however, and so we appreciate suggestions for new integrated variables that would be useful to users. Regarding the variables you are looking for, you are correct that WNLOOK is the IPUMS CPS variable relating to PEDWRSN. The other variables you have mentioned are currently not available. I've noted your interest and will notify the IPUMS CPS team so that they work on adding these variables in the future. In the meantime, you can merge NBER data with IPUMS CPS data in order to take advantage of all of the available capabilities.
Here are a few helpful notes regarding merging IPUMS CPS data with NBER CPS data. (1) NBER data includes non-response households. So, if you drop the non-interviewed households from the NBER file, the record counts should align with the record counts in IPUMS CPS files. (2) If you are merging ASEC samples, a sequential merge will work as the sort order is the same in IPUMS and NBER. (3) If you are merging basic monthly samples a 1:1 merge is possible using HRHHID, HRHHID2, and LINENO as linking keys. Also note that in the NBER file, you'll need to rename the PULINENO to LINENO to allow the merge to work properly.

I hope this is helpful.


Jul 31, 2017 - 01:23 PM

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