Good day,

I am using decomposing analysis to run the following command on individual level data in Stata version 15.1.

HTML Code:
oaxaca move normalize(b.age1624 age2534 age3544 age4554 age55over) normalize(b.male female) normalize(b.ausborn migrant ) normalize(b.married divorced nvmarried widowsep) normalize(b.degree nodegree ) normalize(b.ownerbuyer renters ) normalize(b.notinLF inLF ) normalize(b.noduoinc duoinc), by( svyear) pooled logit
I have created dummies for all my variables. The summary statistics are OK and as excepted. So are the odds ratios. But the coefficient for the explained component are a bit confusing as you can see. It seems the effects are duplicates for each of the vars that are paired eg, male and female ausborn and foreign, degree and no degree, inLf and noiinLF, and duoinc noduoinc. But not for the variables that are more than 2 categories such as age categories and married, divorced, nvmaried an widowsep.
explained Coef. Std. Err z P>z [95% Conf. Interval]
age1624 -0.00011 1.55E-05 -7.14 0 -0.00014 -8E-05
age2534 -0.00011 1.67E-05 -6.67 0 -0.00014 -7.9E-05
age3544 -1.3E-05 1.31E-05 -1 0.317 -3.9E-05 1.26E-05
age4554 -3.21E-07 5.38E-06 -0.06 0.952 -1.1E-05 1.02E-05
age55over -0.00043 7.22E-05 -5.93 0 -0.00057 -0.00029
male -4.49E-07 7.25E-07 -0.62 0.536 -1.87E-06 9.73E-07
female -4.49E-07 7.25E-07 -0.62 0.536 -1.87E-06 9.73E-07
ausborn -3.2E-05 9.34E-06 -3.44 0.001 -5E-05 -1.4E-05
migrant -3.2E-05 9.34E-06 -3.44 0.001 -5E-05 -1.4E-05
married -3.8E-05 2.21E-05 -1.69 0.091 -8.1E-05 5.92E-06
divorced 1.27E-05 1.26E-05 1.01 0.314 -1.2E-05 3.74E-05
nvmarried -4E-05 1.74E-05 -2.31 0.021 -7.5E-05 -6.15E-06
widowsep 3.75E-06 6.95E-06 0.54 0.59 -9.88E-06 1.74E-05
degree 0.000385 6.17E-05 6.23 0 0.000264 0.000506
nodegree 0.000385 6.17E-05 6.23 0 0.000264 0.000506
ownerbuyer 0.000175 0.000026 6.75 0 0.000124 0.000226
renters 0.000175 0.000026 6.75 0 0.000124 0.000226
notinLF 1.64E-05 5.91E-06 2.78 0.005 4.86E-06 0.000028
inLF 1.64E-05 5.91E-06 2.78 0.005 4.86E-06 0.000028
noduoinc -5.7E-05 9.51E-06 -5.98 0 -7.6E-05 -3.8E-05
duoinc -5.7E-05 9.51E-06 -5.98 0 -7.6E-05 -3.8E-05

This doesn't repeat in the unexplained component as you can see
unexplained Coef. Std. Err z P>z [95% Conf. Interval]
age1624 -0.00052 0.000567 -0.92 0.356 -0.00164 0.000588
age2534 -2.7E-05 0.000438 -0.06 0.952 -0.00088 0.000831
age3544 -0.00016 0.000514 -0.31 0.76 -0.00116 0.00085
age4554 -0.00075 0.000647 -1.16 0.248 -0.00202 0.00052
age55over 0.002367 0.001627 1.46 0.146 -0.00082 0.005555
male -0.00057 0.000667 -0.86 0.389 -0.00188 0.000734
female 0.000609 0.000707 0.86 0.389 -0.00078 0.001995
ausborn 6.73E-05 0.001059 0.06 0.949 -0.00201 0.002143
migrant -1.9E-05 0.000422 -0.04 0.964 -0.00085 0.000808
married -0.00069 0.001442 -0.48 0.633 -0.00351 0.002137
divorced -1.42E-06 0.000283 -0.01 0.996 -0.00056 0.000553
nvmarried -0.00031 0.000854 -0.36 0.72 -0.00198 0.001368
widowsep 0.000175 0.000335 0.52 0.601 -0.00048 0.000832
degree 0.000247 0.000263 0.94 0.348 -0.00027 0.000761
nodegree -0.00143 0.001386 -1.03 0.304 -0.00414 0.001291
ownerbuyer 0.00335 0.002312 1.45 0.147 -0.00118 0.007881
renters -0.00131 0.000906 -1.45 0.147 -0.00309 0.000461
notinLF 0.000959 0.000727 1.32 0.187 -0.00047 0.002383
inLF -0.00184 0.00139 -1.33 0.185 -0.00457 0.000883
noduoinc -0.00111 0.001449 -0.76 0.445 -0.00395 0.001733
duoinc 0.000456 0.000595 0.77 0.443 -0.00071 0.001622



I have tried using an alternative command
HTML Code:
mvdcmp svyear, reverse normal(age1624 age2534 age3544 age4554 age55over| male female| ausborn migrant| divorced married nvmarried widowsep | non_student students| degree nodegree| ownerbuyer renters| inLF notinLF| noduoinc duoinc ): logit move age2534 age3544 age4554 age55over female migrant divorced nvmarried widowsep students degree renters inLF duoinc
and as you can see, i get similar results.
inters Coef. Std.err z P>z [95% Conf. Interval] Pct.
age1624 -0.00011 2.08E-05 -5.48 0 -0.00015 -7.3316E-05 4.279
age2534 -0.00011 2.25E-05 -4.83 0 -0.00015 -6.4537E-05 4.07
age3544 -9.52E-06 1.71E-05 -0.56 0.577 -4.3E-05 0.000023915 0.35701
age4554 -3.64E-07 7.43E-08 -4.9 0 -5.10E-07 -2.19E-07 0.013652
age55over -0.00038 8.75E-05 -4.33 0 -0.00055 -0.00020723 14.2
male 3.08E-07 9.05E-07 0.34 0.733 -1.47E-06 2.08E-06 -0.01156
female 3.08E-07 9.05E-07 0.34 0.733 -1.47E-06 2.08E-06 -0.01156
ausborn -2.5E-05 1.18E-05 -2.14 0.032 -4.9E-05 -2.15E-06 0.95013
migrant -2.5E-05 1.18E-05 -2.14 0.032 -4.9E-05 -2.15E-06 0.95013
divorced 9.71E-06 1.63E-05 0.6 0.551 -2.2E-05 0.000041621 -0.36401
married -2.3E-05 2.73E-05 -0.83 0.405 -7.6E-05 0.000030706 0.85185
nvmarried -3.9E-05 2.26E-05 -1.71 0.086 -8.3E-05 5.55E-06 1.4551
widowsep -4.74E-07 9.15E-06 -0.05 0.959 -1.8E-05 0.000017458 0.01776
non_student -9.14E-06 2.69E-06 -3.4 0.001 -1.4E-05 -3.88E-06 0.3428
students -9.14E-06 2.69E-06 -3.4 0.001 -1.4E-05 -3.88E-06 0.3428
degree 0.000385 9.4E-05 4.09 0 0.0002 0.00056893 -14.423
nodegree 0.000385 9.4E-05 4.09 0 0.0002 0.00056893 -14.423
ownerbuyer 0.000152 2.9E-05 5.25 0 9.54E-05 0.00020929 -5.7122
renters 0.000152 2.9E-05 5.25 0 9.54E-05 0.00020929 -5.7122
inLF 1.62E-06 7.81E-06 0.21 0.835 -1.4E-05 0.000016934 -0.06089
notinLF 1.62E-06 7.81E-06 0.21 0.835 -1.4E-05 0.000016934 -0.06089
noduoinc -5E-05 1.08E-05 -4.6 0 -7.1E-05 -2.8506E-05 1.8609
duoinc -5E-05 1.08E-05 -4.6 0 -7.1E-05 -2.8506E-05 1.8609
I have tried separating out the variables to including more categories but then the model becomes insignificant.

What could i possibly be doing wrong?

Please help.