. xtnbreg Y X1 X2 X4 X5,fe nolog
Conditional FE negative binomial regression Number of obs = 440
Group variable: company Number of groups = 22
Obs per group:
min = 20
avg = 20.0
max = 20
Wald chi2(4) = 445.43
Log likelihood = -2717.0222 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
Y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X1 | .0005598 .0000342 16.39 0.000 .0004928 .0006268
X2 | .0052978 .0016869 3.14 0.002 .0019915 .008604
X4 | 1.61e-06 4.33e-07 3.71 0.000 7.57e-07 2.46e-06
X5 | .0090133 .001977 4.56 0.000 .0051385 .0128882
_cons | .0941248 .162569 0.58 0.563 -.2245046 .4127541
------------------------------------------------------------------------------
. xtnbreg Y X1 X2 X4 X5,re nolog
Random-effects negative binomial regression Number of obs = 440
Group variable: company Number of groups = 22
Random effects u_i ~ Beta Obs per group:
min = 20
avg = 20.0
max = 20
Wald chi2(4) = 475.88
Log likelihood = -2951.2656 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
Y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X1 | .0005695 .0000337 16.90 0.000 .0005035 .0006356
X2 | .0053215 .0016662 3.19 0.001 .0020558 .0085872
X4 | 1.64e-06 4.28e-07 3.84 0.000 8.06e-07 2.48e-06
X5 | .0090954 .0018924 4.81 0.000 .0053864 .0128044
_cons | .0741569 .1568047 0.47 0.636 -.2331746 .3814884
-------------+----------------------------------------------------------------
/ln_r | .0111269 .2753644 -.5285774 .5508313
/ln_s | 4.00352 .3683888 3.281491 4.725549
-------------+----------------------------------------------------------------
r | 1.011189 .2784455 .5894429 1.734694
s | 54.79069 20.18427 26.61544 112.7924
------------------------------------------------------------------------------
LR test vs. pooled: chibar2(01) = 468.69 Prob >= chibar2 = 0.000
. estimates store fe
. estimates store re
. hausman fe re
Note: the rank of the differenced variance matrix (0) does not equal the number of coefficients being tested (4); 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))
| fe re Difference S.E.
-------------+----------------------------------------------------------------
X1 | .0005695 .0005695 0 0
X2 | .0053215 .0053215 0 0
X4 | 1.64e-06 1.64e-06 0 0
X5 | .0090954 .0090954 0 0
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtnbreg
B = inconsistent under Ha, efficient under Ho; obtained from xtnbreg
Test: Ho: difference in coefficients not systematic
chi2(0) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 0.00
Prob>chi2 = .
(V_b-V_B is not positive definite)