Dear Stata experts,

I am trying to test the influence of my dummy moderator (high tech industry =1, not high tech =0) on the relationship between R&D (lagged with 1 year, lagrd) and Return on Sales (ros100) with panel data ranging from 2005 to 2010. As controls I included a dummy for the company being from the US or not being from the US, year dummies, and a dummy for marketing intensity. Hausman test argues a Fixed effect model.

So far so good. Hereafter I get some difficulties. I am not sure about:

1. which model to use. Using the fixed effects model will omit my US dummy, is it justified to just use random effects model instead?
2. if my input to see the results is correct: xtreg ros100 i.du_high_tech##c.lagrd, re

And when it is correct; what should be interpreted as the overall results.

Code:
. xtreg ros100  i.du_high_tech##c.lagrd, re

Random-effects GLS regression                   Number of obs     =      1,620
Group variable: company_id                      Number of groups  =        324

R-sq:                                           Obs per group:
     within  = 0.6199                                         min =          5
     between = 0.9172                                         avg =        5.0
     overall = 0.7350                                         max =          5

                                                Wald chi2(3)      =    4482.85
corr(u_i, X)   = 0 (assumed)                    Prob > chi2       =     0.0000

--------------------------------------------------------------------------------------
              ros100 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      1.du_high_tech |   .5100225   .0539294     9.46   0.000     .4043229    .6157222
               lagrd |   .0323437   .8364303     0.04   0.969     -1.60703    1.671717
                     |
du_high_tech#c.lagrd |
                  1  |  -3.476529   .8380226    -4.15   0.000    -5.119023   -1.834035
                     |
               _cons |   .0004879   .0430304     0.01   0.991    -.0838501     .084826
---------------------+----------------------------------------------------------------
             sigma_u |          0
             sigma_e |  .84690728
                 rho |          0   (fraction of variance due to u_i)
--------------------------------------------------------------------------------------
Thanks in advance for your help, it would be greatly appreciated!

Sjors