Hello. I have a question regarding the stata commands "xtreg" and "xtivreg2" using the "fe"-option. The regression-outputs below show the same coefficients but slightly different standard-errors. Even if these differences are very small in my case I wonder about the reason. Does it have to do with the missing constant? Very much thanks for your help.
Florian
. xtreg logED_K Bev_m Ausl Bev_0_14 Bev_15_30 Bev_ab65 time_3 time_4 Flukt Ssterb Bev_Dichte BIP_KopfR ALQ, fe cluste
> r(code_d)
Fixed-effects (within) regression Number of obs = 1531
Group variable: code_d Number of groups = 411
R-sq: within = 0.1270 Obs per group: min = 2
between = 0.2297 avg = 3.7
overall = 0.2404 max = 4
F(12,410) = 9.67
corr(u_i, Xb) = -0.6284 Prob > F = 0.0000
(Std. Err. adjusted for 411 clusters in code_d)
------------------------------------------------------------------------------
| Robust
logED_K | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Bev_m | -5.055154 4.770304 -1.06 0.290 -14.43246 4.322152
Ausl | -.2978585 .3102666 -0.96 0.338 -.9077703 .3120534
Bev_0_14 | 3.413796 2.240333 1.52 0.128 -.9901764 7.817768
Bev_15_30 | 1.47096 1.104769 1.33 0.184 -.7007582 3.642679
Bev_ab65 | -1.343489 2.623084 -0.51 0.609 -6.49986 3.812882
time_3 | -.0051302 .0074063 -0.69 0.489 -.0196893 .0094289
time_4 | -.0258546 .0146786 -1.76 0.079 -.0547092 .003
Flukt | -.0305269 .1025177 -0.30 0.766 -.2320528 .170999
Ssterb | .0011562 .0010933 1.06 0.291 -.0009929 .0033054
Bev_Dichte | -.0000805 .0001198 -0.67 0.502 -.000316 .0001551
BIP_KopfR | -1.74e-09 2.97e-09 -0.58 0.559 -7.57e-09 4.10e-09
ALQ | .0034246 .0040251 0.85 0.395 -.0044878 .0113371
_cons | 10.16893 2.795267 3.64 0.000 4.674089 15.66378
-------------+----------------------------------------------------------------
sigma_u | .59185905
sigma_e | .07465149
rho | .98434022 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xtivreg2 logED_K Bev_m Ausl Bev_0_14 Bev_15_30 Bev_ab65 time_3 time_4 Flukt Ssterb Bev_Dichte BIP_KopfR ALQ, fe clu
> ster(code_d)
FIXED EFFECTS ESTIMATION
------------------------
Number of groups = 411 Obs per group: min = 2
avg = 3.7
max = 4
OLS estimation
--------------
Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on code_d
Number of clusters (code_d) = 411 Number of obs = 1531
F( 12, 410) = 9.68
Prob > F = 0.0000
Total (centered) SS = 7.072739806 Centered R2 = 0.1270
Total (uncentered) SS = 7.072739806 Uncentered R2 = 0.1270
Residual SS = 6.174712943 Root MSE = .07425
------------------------------------------------------------------------------
| Robust
logED_K | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Bev_m | -5.055154 4.745777 -1.07 0.287 -14.35671 4.246397
Ausl | -.2978585 .3086713 -0.96 0.335 -.9028431 .3071262
Bev_0_14 | 3.413796 2.228814 1.53 0.126 -.9545986 7.782191
Bev_15_30 | 1.47096 1.099089 1.34 0.181 -.6832138 3.625135
Bev_ab65 | -1.343489 2.609596 -0.51 0.607 -6.458204 3.771226
time_3 | -.0051302 .0073682 -0.70 0.486 -.0195717 .0093112
time_4 | -.0258546 .0146031 -1.77 0.077 -.0544761 .0027669
Flukt | -.0305269 .1019906 -0.30 0.765 -.2304247 .169371
Ssterb | .0011562 .0010877 1.06 0.288 -.0009755 .003288
Bev_Dichte | -.0000805 .0001192 -0.67 0.500 -.0003141 .0001532
BIP_KopfR | -1.74e-09 2.95e-09 -0.59 0.557 -7.53e-09 4.05e-09
ALQ | .0034246 .0040044 0.86 0.392 -.0044239 .0112731
------------------------------------------------------------------------------
Included instruments: Bev_m Ausl Bev_0_14 Bev_15_30 Bev_ab65 time_3 time_4 Flukt
Ssterb Bev_Dichte BIP_KopfR ALQ
------------------------------------------------------------------------------
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