Understanding Society User Support

Hi Alita!

Thanks for your fast and very helpful reply, which makes sense. The only follow up question - why is it that I also only have 35.000 observations when restricting unique observations to jbsemp>0? This should include both self-employed and employed, right?

Thanks again!

You're welcome.

jbsemp =1 for in paid employment and =2 for self-employed. So, you need to check for jbsemp=1 and not jbsemp>0

I am interested in employed and self-employed. This should match the number of individuals with a valid occupation code, right? But when I restrict to employed and self-employed (jbsemp=1 and jbsemp=2) I get a much smaller number of unique observations than when I look at valid occupation codes (jbisco88_cc). So I am just puzzled how this can be the case...

Those who have a job in the week before the interview (jbhas=1 OR jboff =1), whether in paid employment or self-employed (jbsemp=1 or jbsemp=2) are asked about their occupation. This is coded to SOC codes (JBSOC00) and then transformed into JBISCO codes using a look-up file. See description here
https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/variable/jbisco88
But for these 10k cases, this translation was not possible and so JBISCO88 is missing even though JBSOC00 is available.

Also note, that _cc versions of these variables are the less disclosive versions and so available in End User License version of the data. If you wanted the complete coding, then you would need to apply for Special License version of the data.

Hi Alita! Sorry to bother you again but just to reiterate: the occupation code actually has more unique observations than the ones who have a job in the week before the interview (jbhas=1 OR jboff =1) - How can that be? If you're saying there is 10k JBISCO88 missing, than if anything there should be less observations in jbisco88 than people in some form of employment, no?

Thanks again for your help!!!

No problem. I have looked at the data again. Over the 18+9 waves of data:

jbhas=1|jboff=1 for 370979 cases
jbocc90_cc or jbsoc00_cc is not -8 (i.e., valid cases either >0 or -1 -2 -9) for 370412 cases
jbisco88_cc is not -8 (i.e., valid cases either >0 or -1 -2 -9) for 360642 cases

Are you using Stata? Then I can share the syntax file which I have used to get these figures.

Thanks so much for looking into this. I think I have figured it now. I was looking at unique observations (i.e. by pidp) so it makes sense that there is more occupation codes than observations of work status if individuals stay employed but switch jobs. My sample is smaller as I have restricted for things.

Thanks for your help in understanding the difference in those variables and best!