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Support #2033

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Derived variable on income / earnings of each benefit unit

Added by Thomas Stephens 11 months ago. Updated 9 months ago.

Status:
Resolved
Priority:
Normal
Assignee:
-
Category:
Income
Start date:
01/18/2024
% Done:

100%


Description

Hi,

I notice that Understanding Society has a useful derived variable which splits households by their benefit unit (buno_dv); https://www.understandingsociety.ac.uk/documentation/mainstage/variables/buno_dv/. This appears to be aligned to how the DWP and Family Resources Survey define a benefit unit.

Is there a derived variable on income strictly for those in each benefit unit? This would ideally include several additional variables, distinguishing between income from all sources, earnings, investments, benefit income, pension, e.t.c. I am aware of household income derived variables and individual income derived variables, and have used them in my other analysis,, but I can't seem to see a set of the same derived variables for the benefit unit. Perhaps this exists and I have missed it.

If it hasn't been created, any advice / code on how it has been constructed in other cases would be very welcome of course.

Thanks in anticipation and let me know if any questions or ambiguities.

Best wishes,

Tom

Actions #1

Updated by Understanding Society User Support Team 11 months ago

  • Category set to Income
  • Status changed from New to In Progress
  • % Done changed from 0 to 10

Many thanks for your enquiry. The Understanding Society team is looking into it and we will get back to you as soon as we can. We aim to respond to simple queries within 48 hours and more complex issues within 7 working days.

Best wishes,
Understanding Society User Support Team

Actions #2

Updated by Understanding Society User Support Team 10 months ago

  • Status changed from In Progress to Feedback
  • % Done changed from 10 to 80
  • Private changed from Yes to No

Sorry for the delay in getting back to you. Here is the response from our income team.

For complete households you can sum the individual incomes in the benefit unit to get the benefit unit total. The Stata code for this is something like this:
use pidp l_hidp l_buno_dv using l_indall, clear
merge 1:1 pidp using l_indresp, nogen keep(3) keepus(l_fimngrs_dv)
mvdecode _all, mv(-9/-1)
bys l_hidp l_buno_dv: egen l_fimngrs_dv_bu=sum(l_fimngrs_dv)
bys l_hidp l_buno_dv: keep if _n==1
drop l_fimngrs_dv pidp
isid l_hidp l_buno_dv
su

Similarly, you can do this for subcomponents of income that are provided like total benefit income or total earnings. Note, you will not be able to recreate benefit unit totals of individual benefits (eg. benefit unit child benefit income or universal credit income) as these amounts are not on the released datasets (at least not in a cleaned up form with imputed values. Only the raw survey reports are available on the benefit.dta file). Also note that you will also be ignoring council tax deductions which occur at the household level and not deducted from individual incomes (and are deducted in the variable fihhmnnet3_dv measured at the household level).

One thing to consider is that there can be joint reporting of benefits and unearned sources (eg. both partners report child benefit, we identify and give it only to one) which possibly could introduce an issue. When summing at the household level it doesnt matter – the household total will be correct. But at the benefit unit level it will only work if both of the joint recipients are in the same benefit unit – or if not it will be slightly random which benefit unit gets the amount. [In principle this should not be an issue as both recipients should always be in the same benefit unit. But there MAYBE small violations where there are reporting errors and respondents in different benefit units but in the same household report the same benefit (and so it will be a bit random which benefit unit gets assigned the amount). That should really be checked.]

For incomplete households (ie. households where not all members completed an interview) things are more tricky. See variable hhresp_dv. You will not observe the imputed income amounts for non-respondents as these are not available in the data. And so you will have to drop such households which is a kind of selection which they might want to create some weights to adjust depending on their research question.

Hope this helps. If you have further questions please let us know.

Actions #3

Updated by Understanding Society User Support Team 9 months ago

  • Status changed from Feedback to Resolved
  • % Done changed from 80 to 100
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