Hello Sadia,
A sketch of the matching is as follows:
For i_youth file, you have different identifiers for parents (i_fnpid: natural father pidp, i_mnpid: natural mother pidp, i_pn1pid: natural parent 1 pidp, i_pn2pid: natural parent 2 pidp, i_pns1pid: nat/step/adopt parent 1 pidp, i_pns2pid: nat/step/adopt parent 2 pidp, i_fnspid: nat/step/adopt father pidp, i_mnspid: nat/step/adopt mother pidp) then you will need to choose one of these variables to match any information from them (not only income variables but also all the information the study has about them, e.g education, employment, etc.). Once you choose which parent variable you want to use (let's say i_fnpid: natural father) you will need to rename it to pidp which is the cross-wave person identifier to match with other files. But first, you will need to rename pidp (cross-wave youth identifier in this case) to, let’s say pidp_y and then i_fnpid to pidp. Then you can merge this file (by pidp) with i_indresp to obtain income variables.
For cf_youth_p you will need first to merge it with _indall ( = a,b,c,d,e,f,g,h,i,j,k,l) files to get the parents identifiers (*_fnpid *_mnpid *_pn1pid *_pn2pid *_pns1pid *_pns2pid *_fnspid *_mnspid) Then repeat the process as in i_youth file.
Attached you will find a Stata syntax code example.
If you need more information about the previous variables you can use the variable search at: https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation
To have more information about income variables please see the derived income variables user guide: https://www.understandingsociety.ac.uk/documentation/mainstage/user-guides/main-survey-user-guide/derived-income-variables
Hope this helps.
Best wishes,
Understanding Society User Support Team
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