I am writing my Master's thesis, where I am doing an FE estimation on the probability of default of a panel data set from 2008-2018. I have been made aware that it could be a good idea to include time dummies to control for any aggregate time effect (i.e. changes in the economic environment).
The variable I am interested in is the first one "WOMEN", as this is the fraction of female directors in the firms.
When I run my regression without time dummies, I get significant results, but when I include them, the results turn insignificant. (See code)
First my estimation with time dummies
Code:
. xtreg $ylist $xlist i.Time, fe vce(robust)
Fixed-effects (within) regression Number of obs = 76,710
Group variable: ID Number of groups = 12,895
R-sq: Obs per group:
within = 0.2433 min = 1
between = 0.2360 avg = 5.9
overall = 0.2757 max = 46
F(36,12894) = 42.19
corr(u_i, Xb) = 0.0226 Prob > F = 0.0000
(Std. Err. adjusted for 12,895 clusters in ID)
----------------------------------------------------------------------------------
| Robust
PD | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
Women | -.0011513 .001198 -0.96 0.337 -.0034996 .001197
ROA | -.102301 .0060319 -16.96 0.000 -.1141244 -.0904776
MTBt | .0001097 .0000167 6.57 0.000 .000077 .0001424
LIQUID | -.0002312 .0000897 -2.58 0.010 -.0004069 -.0000554
SOLV | .007016 .0006786 10.34 0.000 .0056859 .0083461
RISK1 | .0176122 .000926 19.02 0.000 .0157971 .0194274
MktCap | -5.00e-09 6.51e-10 -7.69 0.000 -6.28e-09 -3.73e-09
Inde | .0022668 .000858 2.64 0.008 .000585 .0039486
OtherBoards | .0001514 .0001023 1.48 0.139 -.0000491 .0003519
Bsize | -.0004402 .0000529 -8.33 0.000 -.0005439 -.0003366
dGov | .0011423 .0004785 2.39 0.017 .0002044 .0020802
dAudit | .0000593 .0002138 0.28 0.782 -.0003599 .0004784
dComp | .000157 .0001896 0.83 0.408 -.0002146 .0005286
dNom | -.0012808 .000506 -2.53 0.011 -.0022726 -.0002889
InstOwn | -.0212428 .0022082 -9.62 0.000 -.0255713 -.0169144
FCF | -3.85e-08 9.35e-09 -4.12 0.000 -5.68e-08 -2.02e-08
dEnergy | -.0017655 .0007583 -2.33 0.020 -.0032519 -.0002792
dMaterials | -.000624 .0005299 -1.18 0.239 -.0016627 .0004146
dConsumerDisc | .0023597 .0005535 4.26 0.000 .0012748 .0034447
dConsumerSta | .0001703 .0007431 0.23 0.819 -.0012863 .0016268
dHealthCare | .0027769 .0007045 3.94 0.000 .001396 .0041578
dFinancials | -.0004171 .0037388 -0.11 0.911 -.0077456 .0069114
dInformationTech | .0030258 .0007783 3.89 0.000 .0015002 .0045514
dComms | .0002314 .0009373 0.25 0.805 -.0016059 .0020686
dUtilities | -.0050889 .0007094 -7.17 0.000 -.0064794 -.0036985
dRealEstate | -.0060983 .0020713 -2.94 0.003 -.0101584 -.0020381
|
Time |
2 | -.0041194 .0003411 -12.08 0.000 -.004788 -.0034509
3 | -.0039076 .000284 -13.76 0.000 -.0044642 -.003351
4 | -.0017163 .0001891 -9.08 0.000 -.002087 -.0013457
5 | -.0023712 .0002102 -11.28 0.000 -.0027832 -.0019593
6 | -.0010996 .0001915 -5.74 0.000 -.001475 -.0007242
7 | -.0013153 .0002051 -6.41 0.000 -.0017172 -.0009133
8 | -.001092 .0002049 -5.33 0.000 -.0014935 -.0006904
9 | -.0015867 .000247 -6.42 0.000 -.0020708 -.0011026
10 | -.0032568 .0002524 -12.90 0.000 -.0037515 -.002762
11 | -.001924 .0002559 -7.52 0.000 -.0024257 -.0014223
|
_cons | .0269272 .0023039 11.69 0.000 .0224112 .0314433
-----------------+----------------------------------------------------------------
sigma_u | .01838454
sigma_e | .00901617
rho | .80611808 (fraction of variance due to u_i)
----------------------------------------------------------------------------------Code:
. xtreg $ylist $xlist , fe vce(robust)
Fixed-effects (within) regression Number of obs = 76,710
Group variable: ID Number of groups = 12,895
R-sq: Obs per group:
within = 0.2338 min = 1
between = 0.2244 avg = 5.9
overall = 0.2638 max = 46
F(26,12894) = 52.71
corr(u_i, Xb) = 0.0224 Prob > F = 0.0000
(Std. Err. adjusted for 12,895 clusters in ID)
----------------------------------------------------------------------------------
| Robust
PD | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
Women | -.0021433 .0010889 -1.97 0.049 -.0042777 -8.82e-06
ROA | -.1033834 .0059445 -17.39 0.000 -.1150355 -.0917312
MTBt | .0001104 .0000167 6.63 0.000 .0000777 .0001431
LIQUID | -.0002607 .0000901 -2.89 0.004 -.0004373 -.0000842
SOLV | .0068866 .0006663 10.34 0.000 .0055805 .0081926
RISK1 | .012754 .0005728 22.27 0.000 .0116312 .0138768
MktCap | -5.18e-09 6.75e-10 -7.68 0.000 -6.51e-09 -3.86e-09
Inde | .0017683 .0008672 2.04 0.041 .0000684 .0034682
OtherBoards | .0001932 .0001038 1.86 0.063 -.0000103 .0003966
Bsize | -.0004775 .000053 -9.01 0.000 -.0005814 -.0003736
dGov | .0012372 .0005022 2.46 0.014 .0002527 .0022217
dAudit | -1.80e-06 .0002154 -0.01 0.993 -.0004241 .0004205
dComp | .0000934 .0001928 0.48 0.628 -.0002845 .0004712
dNom | -.0014574 .0005306 -2.75 0.006 -.0024975 -.0004174
InstOwn | -.0213736 .0022335 -9.57 0.000 -.0257516 -.0169956
FCF | -4.17e-08 9.68e-09 -4.31 0.000 -6.06e-08 -2.27e-08
dEnergy | -.00168 .0007594 -2.21 0.027 -.0031685 -.0001915
dMaterials | -.0005221 .0005387 -0.97 0.332 -.001578 .0005337
dConsumerDisc | .0025209 .000564 4.47 0.000 .0014154 .0036265
dConsumerSta | -.0001026 .0007424 -0.14 0.890 -.0015579 .0013527
dHealthCare | .0026983 .0007112 3.79 0.000 .0013042 .0040924
dFinancials | -.0000391 .003853 -0.01 0.992 -.0075915 .0075133
dInformationTech | .0030545 .0007851 3.89 0.000 .0015156 .0045933
dComms | .0003357 .0009567 0.35 0.726 -.0015396 .002211
dUtilities | -.0057208 .0007085 -8.07 0.000 -.0071095 -.004332
dRealEstate | -.0062761 .0021122 -2.97 0.003 -.0104163 -.002136
_cons | .0278123 .0023418 11.88 0.000 .023222 .0324026
-----------------+----------------------------------------------------------------
sigma_u | .01851273
sigma_e | .00907152
rho | .80637699 (fraction of variance due to u_i)
----------------------------------------------------------------------------------Code:
testparm i.Time
( 1) 2.Time = 0
( 2) 3.Time = 0
( 3) 4.Time = 0
( 4) 5.Time = 0
( 5) 6.Time = 0
( 6) 7.Time = 0
( 7) 8.Time = 0
( 8) 9.Time = 0
( 9) 10.Time = 0
(10) 11.Time = 0
F( 10, 12894) = 38.22
Prob > F = 0.0000What are your experiences with time dummies in panel data? Should they be included or not?
Thanks in advance
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