I am running a fe regression model on US listed companies to study the effect of lagged Relative Geographic Diversification (L1.Relative_GSD) on Firm Performance (ROA.) I am using a linear and quadratic term for L1.Relative_GSD and am interacting it with a dummy variable Crisis (Crisis=0 is the period 2001-06 and Crisis=1 is the period 2010-19.)
1. cL.Relative_GSD#cL.Relative_GSD has a p>|t| = 10.5%, but Crisis#cL.Relative_GSD has a p>|t| = 73.7% (not significant at all.)
2. Crisis#cL.Relative_GSD#cL.Relative_GSD is significant but Crisis#cL.Relative_GSD is not. (In such a situation, would it be correct for me to interpret the interaction results for Crisis#cL.Relative_GSD#cL.Relative_GSD?)
3. Should I be considered the adjusted R-squared before interpreting the results in #2? If so, where can I find the adjusted R-squared for xtreg? Thank you so much.
I am attaching my results screen for your reference.
Code:
. xtreg ROA_win05 l1.LnRev l1.LnLTDTA l1.CoAge l1.RnDIntensity l1.AdvExpIntensity TotalPSD GDPGrowth_Wg
> t GDP_pc_Wgt CPI_Wgt c.l1.Relative_GSD##c.l1.Relative_GSD##i.Crisis if SIC_2Digit_Division=="Manufact
> uring" & l1.Relative_GSD !=0 & l1.Relative_GSD !=. & HeadquartersCountryRegion=="United States" & FST
> S>10, fe cluster(compid)
Fixed-effects (within) regression Number of obs = 6,433
Group variable: compid Number of groups = 805
R-sq: Obs per group:
within = 0.0575 min = 1
between = 0.1898 avg = 8.0
overall = 0.0981 max = 18
F(14,804) = 8.81
corr(u_i, Xb) = -0.1639 Prob > F = 0.0000
(Std. Err. adjusted for 805 clusters in compid)
-------------------------------------------------------------------------------------------------
| Robust
ROA_win05 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
--------------------------------+----------------------------------------------------------------
LnRev |
L1. | -1.407216 .3320157 -4.24 0.000 -2.058935 -.7554957
|
LnLTDTA |
L1. | -.521211 .1351684 -3.86 0.000 -.7865356 -.2558863
|
CoAge |
L1. | .0137111 .0283719 0.48 0.629 -.0419806 .0694027
|
RnDIntensity |
L1. | .0026586 .0026161 1.02 0.310 -.0024766 .0077938
|
AdvExpIntensity |
L1. | -11.87018 9.741451 -1.22 0.223 -30.99186 7.251499
|
TotalPSD | -.2000879 .3119765 -0.64 0.521 -.8124725 .4122966
GDPGrowth_Wgt | .2464468 .040049 6.15 0.000 .1678338 .3250599
GDP_pc_Wgt | .0000154 .0000294 0.53 0.599 -.0000422 .0000731
CPI_Wgt | .1231483 .0824054 1.49 0.135 -.0386069 .2849035
|
Relative_GSD |
L1. | .0011202 .9366034 0.00 0.999 -1.837356 1.839597
|
cL.Relative_GSD#cL.Relative_GSD | 2.913843 1.793011 1.63 0.105 -.6056914 6.433377
|
1.Crisis | .8772725 .2731693 3.21 0.001 .3410634 1.413482
|
Crisis#cL.Relative_GSD |
1 | .3113933 .9286133 0.34 0.737 -1.511399 2.134186
|
Crisis#cL.Relative_GSD#|
cL.Relative_GSD |
1 | -3.953864 1.851397 -2.14 0.033 -7.588007 -.3197211
|
_cons | 16.47904 2.224425 7.41 0.000 12.11268 20.84541
--------------------------------+----------------------------------------------------------------
sigma_u | 8.7188974
sigma_e | 3.7498225
rho | .84390413 (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------------
0 Response to Interaction Effect between a Dummy Variable and Quadratic Term
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