From: Measuring links between labor monopsony and the gender pay gap in Brazil
Endowments | Coefficients | |
---|---|---|
ln(wage) | −.001 | −.075 |
(.00006) ∗∗ | (.02) ∗∗ | |
Age 30–39 | −.00003 | −.0009 |
(7.50e −06) ∗∗ | (.001) | |
Age 40–49 | .0003 | .0004 |
(.00006) ∗∗ | (.002) | |
Education: middle | −.00002 | .0007 |
(.00003) | (.0004) | |
Education: high school | .00004 | .003 |
(.0001) | (.001) ∗ | |
Education: college | −.001 | .004 |
(.0002) ∗∗ | (.001) ∗∗ | |
Sector dummies | .001 | .002 |
(.0002) ∗∗ | (.0008) ∗ | |
Region dummies | .0002 | .0002 |
(.00002) ∗∗ | (.0007) | |
Occupation dummies | .001 | .002 |
(.0002) ∗∗ | (.0009) ∗ | |
Potential experience | −.0007 | .025 |
(.0003) ∗ | (.012) ∗ | |
Potential experience-squared | .0006 | −.006 |
(.0002) ∗∗ | (.004) | |
Firm variables | ||
ln(Employees) | .0003 | .001 |
(.00004) ∗∗ | (.001) | |
% primary educated | .003 | −.006 |
(.0002) ∗∗ | (.002) ∗∗ | |
% high school educated | −.0009 | −.006 |
(.00008) ∗∗ | (.002) ∗∗ | |
% white collar | .0002 | .001 |
(.0001) | (.001) | |
Constant | . | .054 |
. | (.016) ∗∗ |