Closed rhrabino closed 10 months ago
We created the dummy variable for being a nepobaby, i.e. being in the same industry as at least one parent. We do have one significant issue with this, however, which is that we have a number of false positives. This is because whenever a respondent did not respond to the question asking their industry and they did not respond to the question asking their mother of father's industry, the GSS marked it as iap
. So we will need to back and correct for these false positives.
This was the line of code we used: gen nepobaby = ((indus10 == paind10)|(indus10 == maind10))
nepobaby
variable for false positives.iap
means "inapplicable"
@ecn310/nepobabies This is a big step! Yay!
Let us know if you need help figuring out how to deal with the iap
issue.
Where is your do-file with this work? NEVERMIND. I just found it at the bottom of the main do file in your repo.
We must create this new variable, that splits respondents into two groups of whether or not they have the same college major as the industry their parent's are in.
We are no longer going in the direction of matching respondent college major to respondent parent industry as a label of being a nepobaby. As reflected in the new variable we have created but are still editing, nepobaby
, we are now measuring nepotism in and out of recessions as being in the same industry as a parent.
These are the following responses that might need to be recoded for nepobaby
:
iap
no answer
uncodeable
And can be creating false positives for parent industry. We should use the replace
function as recommended by Dylan to replace any responses that include those options with 1 or 0 for only indus10
.
I added two new variables panepobaby
and manepobaby
, which are dummy variables for matching father's industry or mother's industry, respectively.
We should use the
replace
function as recommended by Dylan to replace any responses that include those options with 1 or 0 for onlyindus10
.
@eldreddyl Thank you! I used the following line of code to ensure that no false positives are created from two matching responses that are missing!
replace indus10 = 1 if missing(indus10)
And with that we can close this issue!
We must create this new variable, that splits respondents into two groups of whether or not they have the same college major as the industry their parent's are in. Maybe it could include three groups, the third being they have a similar major to their parent's industry, e.g. respondent majors in human development, parent is a psychologist. Our issue is that we do not know how to match up major to industry and make it a new variable. I assume there is also a time issue to this. It might have to be only respondents who are currently in college.