Hi all,
I am using the blinder Oaxaca decomposition method to study spousal decision making outcomes by different groups (wives with children versus wives with no children). My dataset is a repeated cross section with two survey rounds. I ran a threefold decomposition using the below code (My outcome variable is a decision making score, independent variables are various demographic predictors and the groups I’m comparing are women who have children with women who have no children):
Which returned the below output:
From my understanding I have interpreted as:
The mean of the decisions score is -0.24 for women with no children and 0.02 for women with children, yielding a gap in women’s contribution to decisions of -0.26. The decrease of -0.16 indicates that differences in endowments account for just over half of the gap. The total for endowments is the total explained portion by my predictors and the total for coefficients is total unexplained portion.
My question is threefold:
I have used the following literature to help aid my understanding of Oaxaca:
Jann, B., 2008. The Blinder-Oaxaca decomposition for linear regression models. The Stata Journal, 8(4), pp.453-479.
O’Donnell, O., Van Doorslaer, E., Wagstaff, A. and Lindelow, M., 2008. Explaining differences between groups: Oaxaca decomposition. Analysing health equity using household survey data. Inst Learn Resourc Ser, pp.147-157.
Thank you.
I am using the blinder Oaxaca decomposition method to study spousal decision making outcomes by different groups (wives with children versus wives with no children). My dataset is a repeated cross section with two survey rounds. I ran a threefold decomposition using the below code (My outcome variable is a decision making score, independent variables are various demographic predictors and the groups I’m comparing are women who have children with women who have no children):
Code:
oaxaca M1 deduc2 deduc3 deduc4 dreleduc2 dreleduc3 dses1 dses2 dses3 dses4 dsondum1, by (birthstat) detail
Which returned the below output:
Code:
Blinder-Oaxaca decomposition Number of obs = 4,560 1: birthstat = 0 2: birthstat = 1 ------------------------------------------------------------------------------ M1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Differential | Prediction_1 | -.2463795 .0761519 -3.24 0.001 -.3956345 -.0971245 Prediction_2 | .0185322 .0219223 0.85 0.398 -.0244347 .0614991 Difference | -.2649117 .0792446 -3.34 0.001 -.4202281 -.1095952 -------------+---------------------------------------------------------------- Endowments | deduc2 | .0002665 .005405 0.05 0.961 -.0103271 .0108602 deduc3 | .0004218 .0014309 0.29 0.768 -.0023828 .0032263 deduc4 | .0011656 .0084264 0.14 0.890 -.0153499 .017681 dreleduc2 | .0015314 .0021107 0.73 0.468 -.0026055 .0056683 dreleduc3 | .0047169 .0035385 1.33 0.183 -.0022185 .0116522 dses1 | .0070985 .0068327 1.04 0.299 -.0062932 .0204903 dses2 | .0101704 .0062187 1.64 0.102 -.0020181 .0223589 dses3 | -.0097885 .0058672 -1.67 0.095 -.0212881 .001711 dses4 | -.001965 .0026364 -0.75 0.456 -.0071323 .0032022 dsondum1 | -.1796086 .0486933 -3.69 0.000 -.2750457 -.0841715 Total | -.1659911 .0495968 -3.35 0.001 -.2631991 -.0687831 -------------+---------------------------------------------------------------- Coefficients | deduc2 | -.1537282 .1858926 -0.83 0.408 -.5180711 .2106147 deduc3 | -.0243597 .0096307 -2.53 0.011 -.0432357 -.0054838 deduc4 | .0247731 .0669242 0.37 0.711 -.1063959 .1559421 dreleduc2 | .08938 .0493094 1.81 0.070 -.0072647 .1860247 dreleduc3 | .072015 .0559359 1.29 0.198 -.0376173 .1816474 dses1 | -.0126002 .0334791 -0.38 0.707 -.0782179 .0530176 dses2 | .0858618 .0497683 1.73 0.084 -.0116823 .1834059 dses3 | .0455632 .0556434 0.82 0.413 -.0634959 .1546222 dses4 | .0754199 .0555338 1.36 0.174 -.0334242 .1842641 dsondum1 | -.1796086 .0486933 -3.69 0.000 -.2750457 -.0841715 _cons | -.3289041 .3380435 -0.97 0.331 -.9914571 .333649 Total | -.3061878 .080242 -3.82 0.000 -.4634593 -.1489163 -------------+---------------------------------------------------------------- Interaction | deduc2 | .016801 .0213559 0.79 0.431 -.0250558 .0586578 deduc3 | -.0040486 .0131121 -0.31 0.757 -.0297478 .0216507 deduc4 | .0108323 .0294287 0.37 0.713 -.0468469 .0685115 dreleduc2 | .0081574 .0099035 0.82 0.410 -.0112531 .0275678 dreleduc3 | -.0117695 .0111562 -1.05 0.291 -.0336352 .0100963 dses1 | .0021806 .006144 0.35 0.723 -.0098614 .0142225 dses2 | -.0179886 .0143918 -1.25 0.211 -.046196 .0102189 dses3 | .0128592 .0165353 0.78 0.437 -.0195494 .0452677 dses4 | .0106348 .0112055 0.95 0.343 -.0113276 .0325973 dsondum1 | .1796086 .0486933 3.69 0.000 .0841715 .2750457 Total | .2072672 .0580637 3.57 0.000 .0934645 .3210699 ------------------------------------------------------------------------------ .
From my understanding I have interpreted as:
The mean of the decisions score is -0.24 for women with no children and 0.02 for women with children, yielding a gap in women’s contribution to decisions of -0.26. The decrease of -0.16 indicates that differences in endowments account for just over half of the gap. The total for endowments is the total explained portion by my predictors and the total for coefficients is total unexplained portion.
My question is threefold:
- If the unexplained portion (-0.30) is smaller than the difference (-0.26) does that mean that the unexplained portion is explaining less than the total observed gap (in spousal decision making)?
- What does it mean if the unexplained portion is larger than the explained portion?
- How would one interpret the results below “endowments” and “coefficients”, for instance how are the results for deduc4 (having a university degree where reference group is no education at all) under endowments different from the results under coefficients?
I have used the following literature to help aid my understanding of Oaxaca:
Jann, B., 2008. The Blinder-Oaxaca decomposition for linear regression models. The Stata Journal, 8(4), pp.453-479.
O’Donnell, O., Van Doorslaer, E., Wagstaff, A. and Lindelow, M., 2008. Explaining differences between groups: Oaxaca decomposition. Analysing health equity using household survey data. Inst Learn Resourc Ser, pp.147-157.
Thank you.
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