xtreg v4 v5 v10 lnv7,fe
Fixed-effects (within) regression Number of obs = 180
Group variable (i): v1 Number of groups = 36
R-sq: within = 0.8536 Obs per group: min = 5
between = 0.9035 avg = 5.0
overall = 0.8965 max = 5
F(3,141) = 274.08
corr(u_i, Xb) = 0.2418 Prob > F = 0.0000
------------------------------------------------------------------------------
v4 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
v5 | 1302.331 144.1842 9.03 0.000 1017.289 1587.374
v10 | .0303081 .0012586 24.08 0.000 .0278199 .0327963
lnv7 | -9144.074 4398.437 -2.08 0.039 -17839.48 -448.6656
_cons | 141985.3 91641.91 1.55 0.124 -39184.47 323155.1
-------------+----------------------------------------------------------------
sigma_u | 26434.241
sigma_e | 13101.292
rho | .80280182 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(35, 141) = 19.09 Prob > F = 0.0000
. xtreg v4 v5 v10 lnv7,re
Random-effects GLS regression Number of obs = 180
Group variable (i): v1 Number of groups = 36
R-sq: within = 0.8535 Obs per group: min = 5
between = 0.9032 avg = 5.0
overall = 0.8965 max = 5
Random effects u_i ~ Gaussian Wald chi2(3) = 1129.69
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
v4 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
v5 | 1369.91 111.8272 12.25 0.000 1150.732 1589.087
v10 | .030744 .0011995 25.63 0.000 .028393 .0330949
lnv7 | -8760.225 3785.156 -2.31 0.021 -16178.99 -1341.456
_cons | 130269.8 78533.4 1.66 0.097 -23652.87 284192.4
-------------+----------------------------------------------------------------
sigma_u | 25907.499
sigma_e | 13101.292
rho | .79635117 (fraction of variance due to u_i)
-----------------------------------------------------------------------------
hausman r1
Note: the rank of the differenced variance matrix (2) does not equal the number of coefficients being tested
(3); be sure this is what you expect, or there may be problems computing the test. Examine the output
of your estimators for anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| r1 r2 Difference S.E.
-------------+----------------------------------------------------------------
v5 | 1302.331 1369.91 -67.57836 91.01519
v10 | .0303081 .030744 -.0004359 .0003813
lnv7 | -9144.074 -8760.225 -383.8485 2240.277
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(2) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 0.57
Prob>chi2 = 0.7534
|