Dear all, I am struggling with a selection problem and I would like to know your feedback about it: I want to explore in a multivariate OLS framework the association between my X (media_use) and Y, but I suspect that the observations may be selected in X by some socio-demographic, and thus I would like to check the eventual selection.

Thus i decided to run an Oaxaca-Blinder threefold decomposition, and the results are the following:

Code:
oaxaca creativity age edu city sex  openness, by(media_use)  noisily

Model for group 1

      Source |       SS       df       MS              Number of obs =    1099
-------------+------------------------------           F(  5,  1093) =   11.27
       Model |  139.229392     5  27.8458784           Prob > F      =  0.0000
    Residual |  2701.30382  1093  2.47145821           R-squared     =  0.0490
-------------+------------------------------           Adj R-squared =  0.0447
       Total |  2840.53321  1098  2.58700657           Root MSE      =  1.5721

------------------------------------------------------------------------------
  creativity |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |  -.0220914   .0062677    -3.52   0.000    -.0343895   -.0097934
         edu |   .0171041   .0744698     0.23   0.818    -.1290158     .163224
        city |   .0119995   .0059058     2.03   0.042     .0004116    .0235875
         sex |   .2500307   .0954181     2.62   0.009     .0628074    .4372541
    openness |   .1069547   .0172714     6.19   0.000     .0730659    .1408435
       _cons |   7.766424   .3895031    19.94   0.000     7.002166    8.530683
------------------------------------------------------------------------------

Model for group 2

      Source |       SS       df       MS              Number of obs =     268
-------------+------------------------------           F(  5,   262) =    3.70
       Model |  29.3619807     5  5.87239615           Prob > F      =  0.0030
    Residual |  415.455183   262  1.58570681           R-squared     =  0.0660
-------------+------------------------------           Adj R-squared =  0.0482
       Total |  444.817164   267  1.66598189           Root MSE      =  1.2592

------------------------------------------------------------------------------
  creativity |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |  -.0269685   .0100983    -2.67   0.008    -.0468526   -.0070843
         edu |   .0075992   .1059643     0.07   0.943    -.2010508    .2162492
        city |   .0014394   .0100752     0.14   0.887    -.0183993     .021278
         sex |   .3840037   .1559485     2.46   0.014     .0769317    .6910757
    openness |   .0512226   .0284962     1.80   0.073    -.0048881    .1073332
       _cons |   9.151029   .6641105    13.78   0.000     7.843356     10.4587
------------------------------------------------------------------------------

Blinder-Oaxaca decomposition                      Number of obs   =       1367
                                                  Model           =     linear
Group 1: media_use = 0                            N of obs 1      =       1099
Group 2: media_use = 1                            N of obs 2      =        268

------------------------------------------------------------------------------
  creativity |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
overall      |
     group_1 |   8.621474   .0486231   177.31   0.000     8.526175    8.716774
     group_2 |   9.026119   .0795434   113.47   0.000     8.870217    9.182022
  difference |  -.4046453   .0932274    -4.34   0.000    -.5873678   -.2219229
  endowments |  -.0504749   .0403209    -1.25   0.211    -.1295025    .0285526
coefficients |  -.3243429   .0939862    -3.45   0.001    -.5085525   -.1401334
 interaction |  -.0298274   .0427209    -0.70   0.485    -.1135589    .0539041
-------------+----------------------------------------------------------------
endowments   |
         age |   .0049286   .0142001     0.35   0.729    -.0229031    .0327603
         edu |   .0018419   .0256868     0.07   0.943    -.0485033    .0521871
        city |   .0015615   .0109589     0.14   0.887    -.0199176    .0230406
         sex |  -.0148148   .0144081    -1.03   0.304    -.0430542    .0134246
    openness |  -.0439922   .0263984    -1.67   0.096    -.0957321    .0077477
-------------+----------------------------------------------------------------
coefficients |
         age |   .1840348   .4484962     0.41   0.682    -.6950016    1.063071
         edu |   .0199319   .2715956     0.07   0.941    -.5123857    .5522495
        city |   .2067904   .2287483     0.90   0.366     -.241548    .6551288
         sex |  -.0664866   .0908223    -0.73   0.464     -.244495    .1115219
    openness |   .7159911   .4281922     1.67   0.094    -.1232501    1.555232
       _cons |  -1.384605   .7699061    -1.80   0.072    -2.893593    .1243836
-------------+----------------------------------------------------------------
interaction  |
         age |  -.0008913   .0033468    -0.27   0.790    -.0074509    .0056683
         edu |   .0023038   .0313959     0.07   0.942    -.0592311    .0638387
        city |   .0114565   .0139335     0.82   0.411    -.0158525    .0387656
         sex |   .0051687   .0084031     0.62   0.538    -.0113011    .0216384
    openness |  -.0478652   .0305762    -1.57   0.117    -.1077934    .0120631
------------------------------------------------------------------------------
I would like to know from you how to interpret this result. I went through the literature (particularly the Benn Jann paper), but I am not entirely sure.
Specifically, by looking at the estimation associated to 'endowments' and 'coefficients' (in bold), may I assume that the differences arising from media_use are entirely attributable to the way people interact with media, instead of a different distribution of endowment by media_use? Should this suggest that I do not incur in any selection bias in considering the association between my X and Y?

thanks a lot in advance for your tips.

Best, G