stata做sfa分析的详细命令语句

各位群友你们好，就是我在用stata计算sfa的时候，无论是使用frontier+变量，xtfrontier+变量，还是sfcross,sfpanel计算的时候，计算出了的效率值怎么是大于1的，我的一组数据是这样的

lnoutput	lnlabour	lncapital
15.70039162	9.579003174	12.74458941
15.31221415	9.549238236	12.51381099
12.89867818	7.383989458	10.71062391
12.92488172	8.009363077	10.96025997
15.03537952	8.976135873	12.14255227
13.93401911	8.685246776	11.58193927
13.02042633	7.568895663	10.89511208
13.38595366	7.845807503	10.90834761
12.19263983	6.439350371	9.454524999

命令如下：
sfcross  lnoutput lnlabour lncapital
initial:       Log likelihood = -13.449518
Iteration 0:   Log likelihood = -13.449518  (not concave)
Iteration 1:   Log likelihood = -7.0344072  (not concave)
Iteration 2:   Log likelihood = -4.0625023  
Iteration 3:   Log likelihood =  -3.208996  (not concave)
Iteration 4:   Log likelihood = -2.4905345  (not concave)
Iteration 5:   Log likelihood = -2.3886018  (not concave)
Iteration 6:   Log likelihood = -2.3765454  
Iteration 7:   Log likelihood = -2.1444908  
Iteration 8:   Log likelihood =  -2.008752  
Iteration 9:   Log likelihood = -1.9937579  
Iteration 10:  Log likelihood =  -1.986255  
Iteration 11:  Log likelihood = -1.9849598  
Iteration 12:  Log likelihood = -1.9840791  
Iteration 13:  Log likelihood = -1.9839049  
Iteration 14:  Log likelihood = -1.9837359  
Iteration 15:  Log likelihood = -1.9837269  
Iteration 16:  Log likelihood = -1.9836615  
Iteration 17:  Log likelihood = -1.9836566  
Iteration 18:  Log likelihood = -1.9836439  
Iteration 19:  Log likelihood = -1.9836424  
Iteration 20:  Log likelihood = -1.9836418  
Iteration 21:  Log likelihood = -1.9836416  

Stoc. frontier normal/exponential model              Number of obs =         9
                                                     Wald chi2(2)  =    127.03
                                                     Prob > chi2   =    0.0000

Log likelihood =    -1.9836
------------------------------------------------------------------------------
         lno |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Frontier     |
         lnl |    .185529   .6727565     0.28   0.783    -1.133049    1.504107
         lnk |   .9766153   .6863974     1.42   0.155    -.3686988    2.321929
       _cons |    1.24623   2.708034     0.46   0.645    -4.061419    6.553879
-------------+----------------------------------------------------------------
Usigma       |
       _cons |  -9.548672    264.708    -0.04   0.971    -528.3668    509.2694
-------------+----------------------------------------------------------------
Vsigma       |
       _cons |   -2.39786   .5146479    -4.66   0.000    -3.406551   -1.389169
-------------+----------------------------------------------------------------
     sigma_u |   .0084437   1.117556     0.01   0.994     1.8e-115    3.9e+110
     sigma_v |   .3015167   .0775875     3.89   0.000     .1820861     .499282
      lambda |    .028004   1.150761     0.02   0.981    -2.227445    2.283453
------------------------------------------------------------------------------


. predict te1
(option xb assumed; fitted values)

. list te1

     +----------+
     |      te1 |
     |----------|
  1. | 15.46997 |
  2. | 15.23907 |
  3. | 13.07633 |
  4. | 13.43616 |
  5. | 14.77017 |
     |----------|
  6. | 14.16869 |
  7. | 13.29081 |
  8. | 13.35511 |
  9. | 11.67435 |
     +----------+

我想问一下这个te是效率值吗？如果是的话为什么都这么大，还有就是哪些回归系数的显著性判断的那个“*”都是自己查表标上去的，还是说软件会自动输出来，急求懂的人帮忙解释一下  麻烦给一下详细的命令好吗？急求 谢谢