Hi,

I am using panel data for US manufacturing companies for the period 2000-19. I am focusing on the impact of international diversification (or GeoGraphic Segment Diversification ie GSD) on Performance (or EBIT_ROA). I have divided my data into 3 eras i.e. pre-crisis period 2001-06 (era=1), crisis period 2007-09 (era=2) and post-crisis period (era=3). Based on my analysis, the margins impact of GSD on performance does not differ significantly in the 3 eras.

I would like to now check whether the level of GSD itself varies in the 3 areas. I did this analysis using xtreg as shown below. My interpretation is that GSD varies significantly across the 3 eras. I would like to check if there is any way to do this analysis for panel data using ANOVA. Thank you.

Code:
. xtreg Ln_GSD l1.era2 l1.era3 if  CoAge>=0 & NATION=="UNITED STATES" & NATIONCODE==840 & FSTS>=1
> 0 & GENERALINDUSTRYCLASSIFICATION ==1 & Year_<2020 & Year_<YearInactive & Discr_GS_Rev!=1, fe c
> luster(n_CUSIP)

Fixed-effects (within) regression               Number of obs     =     26,796
Group variable: n_CUSIP                         Number of groups  =      3,563

R-sq:                                           Obs per group:
     within  = 0.0203                                         min =          1
     between = 0.0000                                         avg =        7.5
     overall = 0.0022                                         max =         19

                                                F(2,3562)         =      54.03
corr(u_i, Xb)  = -0.0417                        Prob > F          =     0.0000

                            (Std. Err. adjusted for 3,563 clusters in n_CUSIP)
------------------------------------------------------------------------------
             |               Robust
      Ln_GSD |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        era2 |
         L1. |   .0624621   .0080676     7.74   0.000     .0466444    .0782798
             |
        era3 |
         L1. |   .0999507    .009785    10.21   0.000     .0807659    .1191355
             |
       _cons |  -.4679418    .004862   -96.24   0.000    -.4774745   -.4584091
-------------+----------------------------------------------------------------
     sigma_u |  .60796916
     sigma_e |  .26823125
         rho |  .83706486   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. test l1.era2 l1.era3

 ( 1)  L.era2 = 0
 ( 2)  L.era3 = 0

       F(  2,  3562) =   54.03
            Prob > F =    0.0000