You do not include state dummies (as fixed-effects) because you included them as random-effects (by stating "|| betnr:"). You can include in this model an overall (fixed) intercept but not all single state dummies.
By including state dummies you take out all the variation between states which you need to calculate the state random effects.
Try it out
use http://www.stata-press.com/data/r12/productivity.dta
egen cyear = std(year)
xtmixed gsp cyear, || region: || state: cyear, cov(indep)
tabulate state, generate(state_dummy)
xtmixed gsp cyear state_dummy*, || region: || state: cyear, cov(indep)
And look at variation of the random effect "state: Independent" -> "sd(_cons)"
xtmixed gsp cyear state_dummy*, || region: || state: cyear, cov(indep)
note: state_dummy48 omitted because of collinearity
Performing EM optimization:
Performing gradient-based optimization:
Iteration 0: log likelihood = 1285.4493
Iteration 1: log likelihood = 1286.9064
Iteration 2: log likelihood = 1286.9508
Iteration 3: log likelihood = 1286.9508
Computing standard errors:
Mixed-effects ML regression Number of obs = 816
-----------------------------------------------------------
| No. of Observations per Group
Group Variable | Groups Minimum Average Maximum
----------------+------------------------------------------
region | 9 51 90.7 136
state | 48 17 17.0 17
-----------------------------------------------------------
Wald chi2(48) = 402947.61
Log likelihood = 1286.9508 Prob > chi2 = 0.0000
-------------------------------------------------------------------------------
gsp | Coef. Std. Err. z P>|z| [95% Conf. Interval]
--------------+----------------------------------------------------------------
cyear | .1347569 .0080845 16.67 0.000 .1189117 .1506022
state_dummy1 | 1.302481 .0155805 83.60 0.000 1.271944 1.333018
[...]
state_dummy47 | 1.711969 .0155805 109.88 0.000 1.681432 1.742506
state_dummy48 | 0 (omitted)
_cons | 9.235048 .0110171 838.25 0.000 9.213455 9.256641
-------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
region: Identity |
sd(_cons) | 1.80e-11 2.67e-10 4.64e-24 70.07652
-----------------------------+------------------------------------------------
state: Independent |
sd(cyear) | .0549153 .0102601 .0380767 .0792005
sd(_cons) | 2.47e-12 . . .
-----------------------------+------------------------------------------------
sd(Residual) | .0454246 .0016555 .0422931 .0487881
------------------------------------------------------------------------------
LR test vs. linear regression: chi2(3) = 578.39 Prob > chi2 = 0.0000
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