Hi, all.
I'm using US 2000 Census data (IPUMS version, with my edits). I've hit upon an issue I don't find much <help> on: how to preserve missing values when these are qualitatively different from zero values when using an <egen> function.
I have individual-level income income data (inctot2) that I want to aggregate within families (famunt2) in a household (serial):
egen ftoty=sum(inctot2), by(serial famunt2)
The issue: ftoty is zero, even when all family members have inctot2==. (i.e., not reported, for example, due to age). In my application (determining family income relative to a poverty threshold) zero family income is very different from nonreported family income.
One work-around is to use the !missing(varname) construction, which sets ftoty to missing for any person with missing inctot2:
egen ftoty=sum(inctot2) if !missing(inctot2), by(serial famunt2)
The drawback to this approach is that I must go back and assign non-missing values of ftoty to individuals for whom ftoty is missing, but who live in a family where other individuals report a valid income value.
Is there a better way to approach this problem?
Best, Deborah Garvey
******************************
Deborah Garvey, Ph.D.
Department of Economics
Kenna Hall
Santa Clara University
Santa Clara, CA 95053
408/554-5580
408/554-2331 (FAX)
[email protected]
http://lsb.scu.edu/~dgarvey
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