I am doing a FE and RE Regression and I am not sure if I should use Time Dummies (i.date) or a linear time trend (c.date).
Code:
xtreg BEVsalesshare2 $varying $invariant i.date, fe vce(cluster county)
Fixed-effects (within) regression Number of obs = 1,296
Group variable: county Number of groups = 18
R-sq: Obs per group:
within = 0.8461 min = 72
between = 0.5139 avg = 72.0
overall = 0.4984 max = 72
F(20,17) = .
corr(u_i, Xb) = -0.8236 Prob > F = .
(Std. Err. adjusted for 18 clusters in county)
------------------------------------------------------------------------------
| Robust
BEVsalessh~2 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
HOVkm | .0035468 .0009032 3.93 0.001 .0016412 .0054524
NTPKM | 1.457356 .5944069 2.45 0.025 .2032672 2.711445
NFPKM | -.0001876 .0002327 -0.81 0.431 -.0006786 .0003034
lCHRoadKm | .0003344 .0001517 2.20 0.042 .0000143 .0006546
DGPrice | 1.457764 1.039166 1.40 0.179 -.7346851 3.650213
EnergyPrice | .0000216 .0000378 0.57 0.575 -.0000582 .0001015
Arbeitslos | .0156132 .0080518 1.94 0.069 -.0013746 .0326009
AVKT | .000037 .0000282 1.31 0.207 -.0000225 .0000966
Einkommen | 7.03e-07 9.98e-07 0.70 0.491 -1.40e-06 2.81e-06
KuestenKm | 0 (omitted)
MuMShare | 0 (omitted)
Temp | 0 (omitted)
|
date |
613 | -.2939739 .2121634 -1.39 0.184 -.7415996 .1536518
614 | -.9261776 .6646269 -1.39 0.181 -2.328418 .4760626
615 | -1.207906 .861059 -1.40 0.179 -3.024582 .6087697
616 | -.9949058 .710164 -1.40 0.179 -2.493221 .5034093
617 | -1.020068 .7257672 -1.41 0.178 -2.551303 .5111668
618 | -1.027555 .7295912 -1.41 0.177 -2.566858 .5117477
619 | -.8171673 .5847958 -1.40 0.180 -2.050979 .4166441
620 | -.6837897 .4917226 -1.39 0.182 -1.721234 .3536543
621 | -.6799051 .4899869 -1.39 0.183 -1.713687 .3538769
622 | -.7046242 .5125549 -1.37 0.187 -1.78602 .3767721
623 | -.6535136 .470383 -1.39 0.183 -1.645935 .3389078
624 | -1.313945 .9263289 -1.42 0.174 -3.268328 .640438
625 | -1.623553 1.146794 -1.42 0.175 -4.043077 .7959706
626 | -1.858993 1.315581 -1.41 0.176 -4.634626 .9166396
627 | -2.22194 1.575141 -1.41 0.176 -5.545197 1.101316
628 | -1.514201 1.070677 -1.41 0.175 -3.773132 .7447305
629 | -1.019642 .7174562 -1.42 0.173 -2.533342 .4940579
630 | -.9345289 .6548755 -1.43 0.172 -2.316195 .4471376
631 | -1.403574 .9984869 -1.41 0.178 -3.510197 .7030493
632 | -1.823847 1.306 -1.40 0.181 -4.579265 .9315715
633 | -1.473502 1.045445 -1.41 0.177 -3.679199 .7321946
634 | -.9520076 .6716685 -1.42 0.174 -2.369104 .465089
635 | -.7893453 .5522139 -1.43 0.171 -1.954415 .3757241
636 | -1.031465 .7057578 -1.46 0.162 -2.520484 .4575538
637 | -1.326484 .9191686 -1.44 0.167 -3.26576 .6127924
638 | -1.241148 .8566794 -1.45 0.166 -3.048584 .5662872
639 | -.8768857 .5970589 -1.47 0.160 -2.13657 .3827985
640 | -1.009364 .690045 -1.46 0.162 -2.465231 .446504
641 | -1.062054 .7318846 -1.45 0.165 -2.606196 .4820875
642 | -1.513326 1.047113 -1.45 0.167 -3.72254 .6958884
643 | -1.677617 1.184271 -1.42 0.175 -4.176211 .8209776
644 | -1.772249 1.263255 -1.40 0.179 -4.437484 .8929865
645 | -1.589766 1.12864 -1.41 0.177 -3.970989 .7914568
646 | -1.313958 .9574884 -1.37 0.188 -3.334082 .706166
647 | -1.38575 1.006986 -1.38 0.187 -3.510305 .7388046
648 | -1.681797 1.192454 -1.41 0.176 -4.197656 .8340617
649 | -1.570769 1.127175 -1.39 0.181 -3.9489 .8073629
650 | -1.249355 .9409421 -1.33 0.202 -3.23457 .7358591
651 | -1.152704 .8185926 -1.41 0.177 -2.879784 .5743752
652 | -1.534667 1.093846 -1.40 0.179 -3.84248 .7731458
653 | -1.360255 .979134 -1.39 0.183 -3.426047 .7055375
654 | -1.759904 1.262651 -1.39 0.181 -4.423864 .9040554
655 | -1.617958 1.178995 -1.37 0.188 -4.105421 .8695047
656 | -1.393409 .9957378 -1.40 0.180 -3.494232 .7074141
657 | -.9588679 .6830983 -1.40 0.178 -2.400079 .4823435
658 | -.9905187 .7153963 -1.38 0.184 -2.499873 .5188354
659 | -.1240522 .0973825 -1.27 0.220 -.3295112 .0814069
660 | -.0512563 .0597748 -0.86 0.403 -.17737 .0748574
661 | .3494894 .2271063 1.54 0.142 -.1296629 .8286418
662 | -.1340338 .1525497 -0.88 0.392 -.4558856 .187818
663 | -.5874017 .4276434 -1.37 0.187 -1.48965 .314847
664 | .0913795 .0551258 1.66 0.116 -.0249259 .2076848
665 | -.8334221 .621054 -1.34 0.197 -2.143732 .4768874
666 | -1.008883 .7212533 -1.40 0.180 -2.530595 .512828
667 | .1646014 .0987002 1.67 0.114 -.0436379 .3728406
668 | .3036344 .1969627 1.54 0.142 -.1119206 .7191894
669 | .4383204 .3030653 1.45 0.166 -.2010915 1.077732
670 | .4428938 .3001054 1.48 0.158 -.1902732 1.076061
671 | .806903 .5671724 1.42 0.173 -.3897263 2.003532
672 | .9135457 .6428917 1.42 0.173 -.4428371 2.269929
673 | 1.648068 1.173547 1.40 0.178 -.8279002 4.124037
674 | .6626571 .4521357 1.47 0.161 -.2912657 1.61658
675 | .8644334 .6236019 1.39 0.184 -.4512516 2.180118
676 | .95344 .708503 1.35 0.196 -.5413708 2.448251
677 | .1065229 .0872987 1.22 0.239 -.0776612 .2907069
678 | .0950838 .1061755 0.90 0.383 -.1289269 .3190944
679 | .630049 .4534669 1.39 0.183 -.3266824 1.58678
680 | .8275755 .573103 1.44 0.167 -.3815662 2.036717
681 | .9732132 .7018173 1.39 0.183 -.5074919 2.453918
682 | .3737313 .2477754 1.51 0.150 -.1490292 .8964918
683 | 0 (omitted)
|
_cons | -19.84632 13.11662 -1.51 0.149 -47.51997 7.827334
-------------+----------------------------------------------------------------
sigma_u | .08053934
sigma_e | .02521736
rho | .91071741 (fraction of variance due to u_i)
------------------------------------------------------------------------------
What does this mean?
Is the joint test result still significant and I should therefore use Time dummies instead of a Time Trend?
Code:
. testparm i.date
( 1) 613.date = 0
( 2) 614.date = 0
( 3) 615.date = 0
( 4) 616.date = 0
( 5) 617.date = 0
( 6) 618.date = 0
( 7) 619.date = 0
( 8) 620.date = 0
( 9) 621.date = 0
(10) 622.date = 0
(11) 623.date = 0
(12) 624.date = 0
(13) 625.date = 0
(14) 626.date = 0
(15) 627.date = 0
(16) 628.date = 0
(17) 629.date = 0
(18) 630.date = 0
(19) 631.date = 0
(20) 632.date = 0
(21) 633.date = 0
(22) 634.date = 0
(23) 635.date = 0
(24) 636.date = 0
(25) 637.date = 0
(26) 638.date = 0
(27) 639.date = 0
(28) 640.date = 0
(29) 641.date = 0
(30) 642.date = 0
(31) 643.date = 0
(32) 644.date = 0
(33) 645.date = 0
(34) 646.date = 0
(35) 647.date = 0
(36) 648.date = 0
(37) 649.date = 0
(38) 650.date = 0
(39) 651.date = 0
(40) 652.date = 0
(41) 653.date = 0
(42) 654.date = 0
(43) 655.date = 0
(44) 656.date = 0
(45) 657.date = 0
(46) 658.date = 0
(47) 659.date = 0
(48) 660.date = 0
(49) 661.date = 0
(50) 662.date = 0
(51) 663.date = 0
(52) 664.date = 0
(53) 665.date = 0
(54) 666.date = 0
(55) 667.date = 0
(56) 668.date = 0
(57) 669.date = 0
(58) 670.date = 0
(59) 671.date = 0
(60) 672.date = 0
(61) 673.date = 0
(62) 674.date = 0
(63) 675.date = 0
(64) 676.date = 0
(65) 677.date = 0
(66) 678.date = 0
(67) 679.date = 0
(68) 680.date = 0
(69) 681.date = 0
(70) 682.date = 0
Constraint 1 dropped
Constraint 2 dropped
Constraint 3 dropped
Constraint 4 dropped
Constraint 5 dropped
Constraint 6 dropped
Constraint 7 dropped
Constraint 8 dropped
Constraint 10 dropped
Constraint 11 dropped
Constraint 12 dropped
Constraint 13 dropped
Constraint 14 dropped
Constraint 16 dropped
Constraint 17 dropped
Constraint 18 dropped
Constraint 19 dropped
Constraint 20 dropped
Constraint 21 dropped
Constraint 22 dropped
Constraint 23 dropped
Constraint 24 dropped
Constraint 25 dropped
Constraint 26 dropped
Constraint 27 dropped
Constraint 28 dropped
Constraint 29 dropped
Constraint 30 dropped
Constraint 31 dropped
Constraint 32 dropped
Constraint 34 dropped
Constraint 35 dropped
Constraint 36 dropped
Constraint 37 dropped
Constraint 39 dropped
Constraint 40 dropped
Constraint 41 dropped
Constraint 45 dropped
Constraint 47 dropped
Constraint 54 dropped
Constraint 55 dropped
Constraint 56 dropped
Constraint 57 dropped
Constraint 58 dropped
Constraint 59 dropped
Constraint 62 dropped
Constraint 63 dropped
Constraint 64 dropped
Constraint 66 dropped
Constraint 69 dropped
F( 20, 17) = 3.5e+06
Prob > F = 0.0000
Thanks a lot for your help
Cheers
Alex
0 Response to Test for significance of Time Dummies
Post a Comment