I'm estimating the wage equation for a selected sample of the self-employed, which contains both males and females, and afterwards which will be decomposed using the Oaxaca command in Stata, by gender.
The wage equation for the Oaxaca-Blinder Decomposition by gender doesn't contain a gender dummy.
However, I am also checking for sample selection bias, and so was wondering if the probit model which will be used to calculate the Inverse Mills Ratio (IMR) should include a gender dummy or not. This is because as mentioned earlier, the main equation doesn't have one.
N.B. The IMR calculation I'm interested in is for participation into the sample for both genders.
Now the problem is, if I include the female dunmy in svy: probit, the mills coefficient is significant in the svy: reg, otherwise not. Any suggestion regarding what is the appropriate approach here?
Thank you in advance.
The wage equation for the Oaxaca-Blinder Decomposition by gender doesn't contain a gender dummy.
However, I am also checking for sample selection bias, and so was wondering if the probit model which will be used to calculate the Inverse Mills Ratio (IMR) should include a gender dummy or not. This is because as mentioned earlier, the main equation doesn't have one.
N.B. The IMR calculation I'm interested in is for participation into the sample for both genders.
Code:
svy: probit selfemp age agesq edu1-edu6 maritalstat1-maritalstat3 head childrenunder6 lnnethhincome hhasset1-hhasset3 landown predict xb if e(sample), xb generate mills=normalden (-xb) / (1-normal (-xb)) svy: reg lnwage age agesq edu1-edu6 occ1-occ9 ind1-ind3 mills oaxaca lnwage age agesq edu1-edu6 occ1-occ9 ind1-ind3 mills, by (female) pooled svy relax adjust (mills) detail
Thank you in advance.
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