st: Clustered SE & High amount of treatment obs.

[startistiker <diudas1@gmail.com>]

Hi!

I'm facing some problems in my analysis. I want to test a treatment-effect
on various firms. 

Panel data, unbalanced, 50 firms/15 years, about 600 obs, average treatment
years: 4,37.

I'm currently using:
cgmreg Y DTreat SC_INCPT X1 X2 i.year i.firm, noconstant cluster(firm year)

where: DTreat is a treatment dummy, SC_INCPT Y X1 X2 are continuous (scaled)
variables.

------------------------------------------------------------------------------
Y                       Coef.     Std. Err.      z      P>|z|     [95% Conf.
Interval]
-------------+----------------------------------------------------------------
SC_INCPT        -6686.274   7841.345    -0.85   0.394    -22055.03    
8682.48
DTreat           -.0217945   .0085074    -2.56   0.010    -.0384687  
-.0051202
X1                  .0220784   .0250524     0.88   0.378    -.0270234   
.0711801
X2                -.1035717   .0178838    -5.79   0.000    -.1386233  
-.0685201
-------------+----------------------------------------------------------------
(year/firm dummies not reported, all variables scaled, both FE have highly
significant F-Test)

1.) The treatment variable seems to be signifcant, but about 30% of the
whole sample are treatment firm-year observations (4.37 on average). Could
this cause problems? If yes, how can I adress them in Stata?

2.) X1 is unfortunately not significant. It is a change variable (xt-xt_1)
which gets insignificant when clustered standard errors are used (highly
significant without firm-clustered SE). How can I adress this issue?

Thank you!


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