I am researching the effect of Geographic Segment Diversification (GSD) on firm performance (EBIT ROA) for US industrial companies for the period 2000-2019. This period includes the financial crisis (2008, 2009.) Hence, I included an interaction term to see how the crisis impacts the quadratic relationship between GSD and EBIT_ROA and find that the interaction impact is significant (below.)

Code:
. xtreg Ln_EBIT_ROA Ln_Revenue Ln_LTD_to_Sales Ln_Intangible_Assets  CoAge wGDPpc wCPI wDCF wExpgr
>  wGDPgr wCons Ln_PS_RD c.l1.Ln_GSD##c.l1.Ln_GSD##ib2.crisis if  CoAge>=0 & NATION=="UNITED STATE
> S" & NATIONCODE==840 & FSTS>=10 & FSTS <=100 & GENERALINDUSTRYCLASSIFICATION ==1 & Year_<2020 & 
> Year_<YearInactive & Discr_GS_Rev!=1, fe cluster(n_WSID)

Fixed-effects (within) regression               Number of obs     =      1,080
Group variable: n_WSID                          Number of groups  =        215

R-sq:                                           Obs per group:
     within  = 0.1280                                         min =          1
     between = 0.0043                                         avg =        5.0
     overall = 0.0123                                         max =         19

                                                F(17,214)         =          .
corr(u_i, Xb)  = -0.7239                        Prob > F          =          .

                                             (Std. Err. adjusted for 215 clusters in n_WSID)
--------------------------------------------------------------------------------------------
                           |               Robust
               Ln_EBIT_ROA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                Ln_Revenue |   .5231021   .1499161     3.49   0.001     .2276008    .8186035
           Ln_LTD_to_Sales |   -.125481   .0419333    -2.99   0.003    -.2081362   -.0428258
      Ln_Intangible_Assets |  -.1103335   .0615829    -1.79   0.075    -.2317202    .0110532
                     CoAge |  -.0029363   .0166989    -0.18   0.861    -.0358517    .0299791
                    wGDPpc |   .0000298   .0000218     1.37   0.172    -.0000131    .0000727
                      wCPI |   .0060675   .0254869     0.24   0.812      -.04417     .056305
                      wDCF |   1.36e-13   1.27e-13     1.07   0.285    -1.14e-13    3.85e-13
                    wExpgr |   .0126791   .0125128     1.01   0.312    -.0119851    .0373433
                    wGDPgr |   .0115004   .0300052     0.38   0.702    -.0476431     .070644
                     wCons |  -2.27e-14   4.36e-14    -0.52   0.603    -1.09e-13    6.32e-14
                  Ln_PS_RD |    -.04777   .0474308    -1.01   0.315    -.1412614    .0457213
                           |
                    Ln_GSD |
                       L1. |    -.49074   .2583853    -1.90   0.059    -1.000046    .0185662
                           |
       cL.Ln_GSD#cL.Ln_GSD |    .177507   .1103887     1.61   0.109    -.0400813    .3950953
                           |
                    crisis |
                        1  |   .0000289   .1170896     0.00   1.000    -.2307677    .2308255
                        3  |   -.244763   .1386875    -1.76   0.079    -.5181314    .0286055
                           |
          crisis#cL.Ln_GSD |
                        1  |  -.0697625   .1898751    -0.37   0.714    -.4440274    .3045024
                        3  |  -.1822128   .2083067    -0.87   0.383    -.5928084    .2283829
                           |
crisis#cL.Ln_GSD#cL.Ln_GSD |
                        1  |  -.2631727   .1049846    -2.51   0.013    -.4701091   -.0562364
                        3  |  -.2041293   .0970556    -2.10   0.037    -.3954366   -.0128219
                           |
                     _cons |   -13.0135   2.823174    -4.61   0.000    -18.57829   -7.448709
---------------------------+----------------------------------------------------------------
                   sigma_u |  1.1013267
                   sigma_e |  .59130596
                       rho |  .77623771   (fraction of variance due to u_i)
--------------------------------------------------------------------------------------------
However, when I run margins dydx pwcompare, there seems to be no statistical difference in the marginal effects (below). I am not clear how to interpret these two results. Any help would be appreciated. Thanks!
Code:
. margins crisis, dydx(cL.Ln_GSD) pwcompare

Pairwise comparisons of average marginal effects

Model VCE    : Robust                           Number of obs     =      1,080

Expression   : Linear prediction, predict()
dy/dx w.r.t. : L.Ln_GSD

--------------------------------------------------------------
             |   Contrast Delta-method         Unadjusted
             |      dy/dx   Std. Err.     [95% Conf. Interval]
-------------+------------------------------------------------
L.Ln_GSD     |
      crisis |
     2 vs 1  |   -.140872   .1625424     -.4594492    .1777053
     3 vs 1  |  -.1597067   .2006283     -.5529309    .2335176
     3 vs 2  |  -.0188347   .1449543     -.3029399    .2652705
--------------------------------------------------------------