Oaxaca-RIF decomposition

Hi all,
I'm having a puzzle trying to decompose the change in log-wage over percentiles between 2007 and 2017. Specifically, I'm focusing on P10, P50 and P90 and I have that the unexplained component always dominates and it is significant along all percentiles. However, it is mostly the case that none of the coefficient in the detailed unexplained is significant. As an example:

Code:

  oaxaca_rif log_gross occupation sector isced emp_status pl200 region contract_type [pw=rb050] if gender==1, by(overall) rif(q(10)) relax wgt(0) rwlogit(occupation sector isced emp_status pl200 region contract_type) 

Model  : Blinder-Oaxaca RIF-decomposition
Type   : Reweighted
RIF    : q(10)
Scale  : 1
Group 1: overall = 0                             N of obs 1      = 7462
Group c: X2~>rw~>X1 or x1*b2                     N of obs C      = 7786
Group 2: overall = 1                             N of obs 2      = 7786

----------------------------------------------------------------------------------
       log_gross |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
Overall          |
         Group_1 |   9.281226   .0297112   312.38   0.000     9.222993    9.339459
         Group_c |   9.479692   .0231539   409.42   0.000     9.434311    9.525073
         Group_2 |   9.531197   .0181483   525.18   0.000     9.495627    9.566767
     Tdifference |   -.249971   .0348155    -7.18   0.000     -.318208   -.1817339
   ToT_Explained |  -.0515046   .0117615    -4.38   0.000    -.0745567   -.0284526
 ToT_Unexplained |  -.1984663   .0370411    -5.36   0.000    -.2710656   -.1258671
-----------------+----------------------------------------------------------------
Explained        |
           Total |  -.0515046   .0117615    -4.38   0.000    -.0745567   -.0284526
  Pure_explained |  -.0522429   .0086994    -6.01   0.000    -.0692934   -.0351923
      Specif_err |   .0007382   .0072891     0.10   0.919    -.0135481    .0150245
-----------------+----------------------------------------------------------------
Pure_explained   |
      occupation |    .004348   .0015658     2.78   0.005     .0012791     .007417
          sector |  -.0003758   .0006203    -0.61   0.545    -.0015916      .00084
           isced |   .0186843   .0033935     5.51   0.000     .0120331    .0253355
      emp_status |  -.0384481   .0047426    -8.11   0.000    -.0477433   -.0291528
           pl200 |   .0206592   .0023426     8.82   0.000     .0160678    .0252506
          region |  -4.69e-07    .000039    -0.01   0.990    -.0000769     .000076
   contract_type |    -.05711    .005093   -11.21   0.000    -.0670921    -.047128
-----------------+----------------------------------------------------------------
Specif_err       |
      occupation |   .0026133   .0292909     0.09   0.929    -.0547958    .0600224
          sector |   .0220972   .0177351     1.25   0.213     -.012663    .0568574
           isced |   .0202463   .0352649     0.57   0.566    -.0488716    .0893642
      emp_status |   -.104401   .0804261    -1.30   0.194    -.2620333    .0532314
           pl200 |  -.0564017    .020493    -2.75   0.006    -.0965672   -.0162362
          region |  -.0075232   .0208354    -0.36   0.718    -.0483597    .0333134
   contract_type |   .0152354   .0353048     0.43   0.666    -.0539608    .0844317
           _cons |   .1088717   .1135587     0.96   0.338    -.1136992    .3314426
-----------------+----------------------------------------------------------------
Unexplained      |
           Total |  -.1984663   .0370411    -5.36   0.000    -.2710656   -.1258671
    Reweight_err |   .0078208   .0162171     0.48   0.630    -.0239641    .0396057
Pure_Unexplained |  -.2062871   .0335048    -6.16   0.000    -.2719553   -.1406189
-----------------+----------------------------------------------------------------
Pure_Unexplained |
      occupation |  -.1129848    .102314    -1.10   0.269    -.3135167     .087547
          sector |  -.0740689   .0565395    -1.31   0.190    -.1848843    .0367465
           isced |  -.0262418    .121197    -0.22   0.829    -.2637835       .2113
      emp_status |   .2850504    .267775     1.06   0.287     -.239779    .8098799
           pl200 |   .0325169   .0640682     0.51   0.612    -.0930545    .1580884
          region |   .0836086   .0650197     1.29   0.198    -.0438277    .2110449
   contract_type |  -.1249659   .1243426    -1.01   0.315    -.3686729    .1187411
           _cons |  -.2692016   .3899048    -0.69   0.490    -1.033401    .4949978
-----------------+----------------------------------------------------------------
Reweight_err     |
      occupation |  -.0003377   .0011815    -0.29   0.775    -.0026534    .0019781
          sector |  -.0000911   .0005099    -0.18   0.858    -.0010904    .0009083
           isced |   -.002396   .0026608    -0.90   0.368    -.0076111    .0028191
      emp_status |   .0062846   .0094418     0.67   0.506    -.0122211    .0247903
           pl200 |   .0009365   .0029674     0.32   0.752    -.0048795    .0067525
          region |  -9.14e-06    .000083    -0.11   0.912    -.0001718    .0001535
   contract_type |   .0034335   .0092499     0.37   0.710     -.014696    .0215631
----------------------------------------------------------------------------------

What could be the reason for this result? Indeed, the effects of the characteristics makes perfectly sense to me, but I don't know how to conjugate with the fact that the unexplained part is dominant.
Furthermore, once doing on the Gini coefficient, the characteristics effects are dominant, what's the reason for the reverse in magnitude of coefficient vs characteristics effect?

thanks for the support