I'm confused by xttest0 result and wondering about this result inference. My data consist of 74 observation for 3 years (2016-2018).
Before i explain my confusion let me show my result of F test (chow) over my time dummies (time effect) in my FE model.
Code:
. xtreg Y X1 X2 i.year, vce(robust)
Random-effects GLS regression Number of obs = 222
Group variable: id Number of groups = 74
R-sq: Obs per group:
within = 0.5808 min = 3
between = 0.7509 avg = 3.0
overall = 0.6921 max = 3
Wald chi2(4) = 224.45
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. Err. adjusted for 74 clusters in id)
------------------------------------------------------------------------------
| Robust
Y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X1 | .7108377 .1066756 6.66 0.000 .5017573 .9199181
X2 | 28.54182 3.993661 7.15 0.000 20.71438 36.36925
|
id |
2017 | -.6259327 .3506201 -1.79 0.074 -1.313136 .0612702
2018 | -2.147511 .5524324 -3.89 0.000 -3.230259 -1.064763
|
_cons | -.8966768 .5696678 -1.57 0.115 -2.013205 .2198515
-------------+----------------------------------------------------------------
sigma_u | 1.8382725
sigma_e | 2.7763652
rho | .30478115 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. testparm i.year
( 1) 2017.year = 0
( 2) 2018.year = 0
chi2( 2) = 15.13
Prob > chi2 = 0.0005But the question came when i'm trying to test Breusch-Pagan LM for my re model.
Because i include time dummies in my model,
1. how to test variance for my dummies using xttest0?
2. because i assumed that breusch pagan only test H0; σ2μi = 0 (individual effect variance), how about time dummies that i include in model? does it mean that i also test H0; σ2δt = 0 (time effect variance)?
and this is how i do xttest0, feel free to correct:
Code:
. xtreg Y X1 X2 i.year, re vce (robust)
Random-effects GLS regression Number of obs = 222
Group variable: id Number of groups = 74
R-sq: Obs per group:
within = 0.5808 min = 3
between = 0.7509 avg = 3.0
overall = 0.6921 max = 3
Wald chi2(4) = 224.45
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. Err. adjusted for 74 clusters in Kode)
------------------------------------------------------------------------------
| Robust
Y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X1 | .7108377 .1066756 6.66 0.000 .5017573 .9199181
X2 | 28.54182 3.993661 7.15 0.000 20.71438 36.36925
|
year |
2017 | -.6259327 .3506201 -1.79 0.074 -1.313136 .0612702
2018 | -2.147511 .5524324 -3.89 0.000 -3.230259 -1.064763
|
_cons | -.8966768 .5696678 -1.57 0.115 -2.013205 .2198515
-------------+----------------------------------------------------------------
sigma_u | 1.8382725
sigma_e | 2.7763652
rho | .30478115 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xttest0
Breusch and Pagan Lagrangian multiplier test for random effects
Y[Kode,t] = Xb + u[Kode] + e[Kode,t]
Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
Y | 35.59679 5.966304
e | 7.708204 2.776365
u | 3.379246 1.838272
Test: Var(u) = 0
chibar2(01) = 18.54
Prob > chibar2 = 0.0000
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