我在处理数据后，结果是
Obtaining starting values for full model:


Iteration 0:   log likelihood = -20645.866
Iteration 1:   log likelihood = -20456.948
Iteration 2:   log likelihood =  -20419.46
Iteration 3:   log likelihood =  -20418.53
Iteration 4:   log likelihood = -20418.529

Fitting full model:

initial values not feasible
r(1400);

end of do-file

r(1400);
       Keywords:  r(1400)
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[P]     error . . . . . . . . . . . . . . . . . . . . . . . . Return code 1400
        numerical overflow;
        You have attempted something that, in the midst of the necessary
        calculations, has resulted in something too large for Stata to
        deal with accurately.  Most commonly, this is an attempt to
        estimate a model (say with regress) with more than 2,147,483,647
        effective observations.  This effective number could be reached
        with far fewer observations if you were running a frequency-weighted
        model.

但是我的数据只有6万多个，离2,147,483,647还远着了，之前用类似的程序处理过其他数据，就没有问题,难道不能用自变量的滞后一阶？
程序是xttobit gdp  L1.a  L1.b  L1.c  L1.d   L1.e  L1.f
           predict rgdp
希望高手指教一下。谢谢了。