Dear listusers,
I am using STATA 10 to try to perform Blinder Oaxaca decomposition. I
have problem with interpreting the unexplained part for detailed variables.
How do I interpret e.g. the variable edu (education) in the unexplained
part. (see below)
How do I consider the intercept (which is positive for women) when
interpreting the variables? (see below)
I'm really new to all this and hope you guys don't feel annoyed if
myquestions are too basic.
Best regards,
Lotta
.oaxaca lnwage edu exp exp2 requieedu trained authority autonomy intern
public, by (women) pooled detail
Blinder-Oaxaca decomposition Number of obs =
2844
1: women = 0
2: women = 1
------------------------------------------------------------------------------
| Robust
lnwage | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
Differential |
Prediction_1 | 4.788947 .0086897 551.11 0.000 4.771915
4.805978
Prediction_2 | 4.615645 .0067895 679.82 0.000 4.602338
4.628953
Difference | .1733014 .0110276 15.72 0.000 .1516876
.1949151
-------------+----------------------------------------------------------------
Explained |
edu | -.0034005 .0024698 -1.38 0.169 -.0082412
.0014402
exp | .0125292 .0065196 1.92 0.055 -.0002489 .0253073
exp2 | -.0154632 .0045769 -3.38 0.001 -.0244337
-.0064927
requireedu | .0064778 .0029525 2.19 0.028 .000691
.0122646
trained | .0195371 .0029021 6.73 0.000 .0138491
.025225
authority | .0186862 .0029988 6.23 0.000 .0128086
.0245638
autonomy | .0047546 .0012853 3.70 0.000 .0022355
.0072737
intern | .0006255 .00053 1.18 0.238 -.0004133
.0016644
public| .0414331 .0038519 10.76 0.000 .0338835
.0489828
Total | .0851799 .0085466 9.97 0.000 .0684288
.1019309
-------------+----------------------------------------------------------------
Unexplained |
edu | .1854117 .056676 3.27 0.001 .0743288
.2964945
exp | .0473325 .0463625 1.02 0.307 -.0435363 .1382013
exp2 | .0054573 .0276459 0.20 0.844 -.0487276
.0596423
requireedu | -.0016687 .0148152 -0.11 0.910 -.0307059
.0273686
trained | -.0197569 .0311631 -0.63 0.526 -.0808354
.0413216
authority | .0059023 .0051046 1.16 0.248 -.0041025
.0159072
autonomy | .069515 .0237158 2.93 0.003 .0230329
.1159971
intern | -.0061785 .004479 -1.38 0.168 -.0149571
.0026001
public | -.0153003 .008253 -1.85 0.064 -.0314759
.0008753
_cons | -.182593 .0659775 -2.77 0.006 -.3119065
-.0532795
Total | .0881215 .0093661 9.41 0.000 .0697642
.1064787
------------------------------------------------------------------------------
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