Hi,
I am estimating the following FE panel model:
xtreg AverChangeROEadj2 strategy_01 duration_change_t1 ceo_change_t1 ceo_int_t1 tmt_turnover_t1 sizelnempl age prior_slack_avail2 ROEadj_1 external_change_dummy lgcount_strategy performance_crisis_ROEadj strategy_01_change_t1 strategy_ceoint ceoint_change change_ceoint_strategy, fe
However, the interaction between strategy_01 (a dummy variable) and change duration (continuous variable) gets dropped from the model (strategy_01_change_t1).
Also, the interaction between strategy_01 (a dummy variable), change duration (continuous variable) and ceo change (a dummy variable) gets dropped from the model. (change_ceoint_strategy)
Any hints why this could be the case and what to do about it (there is no multicollinearity or missing value problem)?
Thanks, Pat
Here's the STATA output:
Fixed-effects (within) regression Number of obs = 430
Group variable: number Number of groups = 60
R-sq: within = 0.0998 Obs per group: min = 1
between = 0.0009 avg = 7.2
overall = 0.0013 max = 9
F(14,356) = 2.82
corr(u_i, Xb) = -0.9883 Prob > F = 0.0005
AverCh~Eadj2 Coef. Std. Err. t P>t [95% Conf. Interval]
strategy_01 2.161211 2.012137 1.07 0.284 -1.795958 6.11838
duration_c~1 -.475537 .877321 -0.54 0.588 -2.20092 1.249846
ceo_cha~e_t1 .7214819 3.349671 0.22 0.830 -5.866149 7.309113
ceo_int_t1 -2.241493 4.682335 -0.48 0.632 -11.45001 6.967021
tmt_turno~t1 -2.060425 1.605712 -1.28 0.200 -5.218299 1.097448
sizelnempl -4.503579 1.727811 -2.61 0.010 -7.90158 -1.105579
age -.464394 .4892887 -0.95 0.343 -1.426654 .4978657
prior_slac~2 .5187986 .3436538 1.51 0.132 -.1570482 1.194645
ROEadj_1 -.0276773 .0467122 -0.59 0.554 -.1195439 .0641892
external_c~y 1.628413 1.329209 1.23 0.221 -.9856769 4.242503
lgcount_st~y 1.426753 2.201901 0.65 0.517 -2.903616 5.757123
perform~Eadj 5.296512 1.790716 2.96 0.003 1.7748 8.818223
strateg~e_t1 (dropped)
strategy_~nt 15.62659 5.616043 2.78 0.006 4.581794 26.67138
ceoint_cha~e -6.139526 1.89593 -3.24 0.001 -9.868157 -2.410895
c~int_stra~y (dropped)
_cons 69.46962 40.03339 1.74 0.084 -9.262056 148.2013
sigma_u 33.386383
sigma_e 12.392948
rho .87889857 (fraction of variance due to u_i)
F test that all u_i=0: F(59, 356) = 0.86 Prob > F = .7540
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