Why not replace ln wages =0 when they are missing. You should also
define a binary variable which takes the value of 1 when the person is
a wage earner and zero otherwise. In your case ilf=1 if there is labor
force participation and ilf=0 if otherwise. Check also other variables
for missing values. To consider the whole sample you should replace
them with zero in case they have missing values.
Goodluck!
-------------------
>Dear Statalist users,
>
>please excuse if this is a basic question, however, I could not find
the
>answer or the right search terms to find it in the archives.
>I have a data set with about 600,000 observations, of which about
90,000
>are wage earners. In it, I would like to run the heckman command to
>correct for sample selectivity bias. My earnings variable is
ln(wages),
>and thus has missing values for all observations that do not have a
>recorded wage. Hence, if I run my heckman with:
>
>Heckman ln_wages varlist1, sel(ilf = varlist1 varlist2),
>
>where varlist2 are my exclusion restrictions and ilf is a
participation
>dummy, the number of observations comes down to 90,000 (ilf does not
>only take the value of 1, since I failed to clean the data
completely,
>yet).
>My aim is to run the selection function on the whole sample (of
600,000
>obs), and to get stata to run the wage function without the missing
>observations. The only solution I found was to replace all missing
>values with -9999 in ln_wages.
>
>Is there some better way to tell stata to use the whole sample for
the
>selection function, even if ln_wages is missing?
>
>Thank you very much in advance for your help.
>
>Nicolas
>
>*
>* For searches and help try:
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>* http://www.ats.ucla.edu/stat/stata/
>
Fatma Bircan
Middle East Technical University
Department of Economics
210-2032
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*
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