[此贴子已经被作者于2008-3-25 9:19:33编辑过]

应该不是啊，我算20个都能出结果，就是结果不对，我也在发愁呢。

提一个弱智的意见，是不是你的数据中间没隔开，计算机不认可啊

hi，解决了，你的原因是数据的小数点后的位数不一致。我改了一下，没有四舍五入，只是简单地留了小数点后三位，不够的补了0.结果如下。

我不会用附件，只好贴在这里。

Output from the program FRONTIER (Version 4.1c)

instruction file = 121.txt    
data file =        eg-dat.txt 

 Error Components Frontier (see B&C 1992)
 The model is a production function
 The dependent variable is logged

the ols estimates are :

                 coefficient     standard-error    t-ratio

  beta 0         0.36500000E+03-NaN            -NaN           
  beta 1        -0.12600000E+03-NaN            -NaN           
  beta 2        -0.93750000E+00  0.28713909E+07 -0.32649682E-06
  beta 3         0.29250000E+02-NaN            -NaN           
  beta 4        -0.26812500E+02-NaN            -NaN           
  beta 5         0.91875000E+01-NaN            -NaN           
  beta 6        -0.13046875E+01  0.21727945E+06 -0.60046522E-05
  beta 7        -0.71875000E+00  0.25273937E+06 -0.28438387E-05
  beta 8         0.22343750E+01  0.54978497E+06  0.40640889E-05
  beta 9        -0.14921875E+01-NaN            -NaN           
  beta10        -0.50854492E+00  0.61625503E+06 -0.82521829E-06
  beta11         0.64238281E+01-NaN            -NaN           
  beta12         0.37226563E+01  0.75646367E+06  0.49211303E-05
  beta13        -0.15625000E-01-NaN            -NaN           
  beta14        -0.67031250E+01-NaN            -NaN           
  sigma-squared -0.29093119E+01

log likelihood function =  -0.12933776E+02

the estimates after the grid search were :

  beta 0         0.36537878E+03
  beta 1        -0.12600000E+03
  beta 2        -0.93750000E+00
  beta 3         0.29250000E+02
  beta 4        -0.26812500E+02
  beta 5         0.91875000E+01
  beta 6        -0.13046875E+01
  beta 7        -0.71875000E+00
  beta 8         0.22343750E+01
  beta 9        -0.14921875E+01
  beta10        -0.50854492E+00
  beta11         0.64238281E+01
  beta12         0.37226563E+01
  beta13        -0.15625000E-01
  beta14        -0.67031250E+01
  sigma-squared  0.45074442E+01
  gamma          0.50000000E-01
  mu             0.00000000E+00
   eta is restricted to be zero
 
 
 iteration =     0  func evals =     20  llf = -0.12939005E+02
     0.36537878E+03-0.12600000E+03-0.93750000E+00 0.29250000E+02-0.26812500E+02
     0.91875000E+01-0.13046875E+01-0.71875000E+00 0.22343750E+01-0.14921875E+01
    -0.50854492E+00 0.64238281E+01 0.37226563E+01-0.15625000E-01-0.67031250E+01
     0.45074442E+01 0.50000000E-01 0.00000000E+00
 gradient step
 iteration =     5  func evals =     82  llf = -0.55221744E+01
     0.36537419E+03-0.12600482E+03-0.96094921E+00 0.29242502E+02-0.26838989E+02
     0.92747406E+01-0.14068303E+01-0.57259334E+00 0.20835379E+01-0.14603361E+01
    -0.38469443E+00 0.64081063E+01 0.37406729E+01-0.14571409E+00-0.67305157E+01
     0.18316870E+01 0.99999999E+00-0.86000711E+00
 iteration =    10  func evals =    213  llf = -0.52734440E+01
     0.36537428E+03-0.12600796E+03-0.96526395E+00 0.29247984E+02-0.26836098E+02
     0.92368887E+01-0.14804082E+01-0.49560166E+00 0.21158752E+01-0.15178883E+01
    -0.38646428E+00 0.64003097E+01 0.37410454E+01-0.15580684E+00-0.66762319E+01
     0.15031350E+01 0.99999999E+00-0.91907293E+00
 iteration =    15  func evals =    253  llf = -0.31222903E+01
     0.36537308E+03-0.12601830E+03-0.97829017E+00 0.29231897E+02-0.26833932E+02
     0.92650843E+01-0.12725231E+01-0.62679450E+00 0.22274641E+01-0.15412402E+01
    -0.40874233E+00 0.64642899E+01 0.37101664E+01-0.14679857E+00-0.68460285E+01
     0.34004034E+00 0.99999998E+00 0.61870990E+00
 iteration =    20  func evals =    314  llf = -0.24835580E+01
     0.36537622E+03-0.12601164E+03-0.96637807E+00 0.29243293E+02-0.26822943E+02
     0.92412914E+01-0.12662610E+01-0.64522229E+00 0.22428341E+01-0.15321413E+01
    -0.40474859E+00 0.64605293E+01 0.37025158E+01-0.13478714E+00-0.68463319E+01
     0.14787755E+00 0.99999997E+00 0.76909700E+00

the final mle estimates are :

                 coefficient     standard-error    t-ratio

  beta 0         0.36537622E+03  0.99988702E+00  0.36541750E+03
  beta 1        -0.12601164E+03  0.99712691E+00 -0.12637473E+03
  beta 2        -0.96637807E+00  0.99650364E+00 -0.96976873E+00
  beta 3         0.29243293E+02  0.99762719E+00  0.29312847E+02
  beta 4        -0.26822943E+02  0.99425004E+00 -0.26978066E+02
  beta 5         0.92412914E+01  0.76075071E+00  0.12147595E+02
  beta 6        -0.12662610E+01  0.57417180E+00 -0.22053695E+01
  beta 7        -0.64522229E+00  0.57600436E+00 -0.11201691E+01
  beta 8         0.22428341E+01  0.67955757E+00  0.33004328E+01
  beta 9        -0.15321413E+01  0.83404881E+00 -0.18369924E+01
  beta10        -0.40474859E+00  0.83828147E+00 -0.48283136E+00
  beta11         0.64605293E+01  0.87699110E+00  0.73666988E+01
  beta12         0.37025158E+01  0.84007919E+00  0.44073414E+01
  beta13        -0.13478714E+00  0.85175449E+00 -0.15824647E+00
  beta14        -0.68463319E+01  0.84027229E+00 -0.81477539E+01
  sigma-squared  0.14787755E+00  0.16814812E+00  0.87944814E+00
  gamma          0.99999997E+00  0.16352265E-06  0.61153605E+07
  mu             0.76909700E+00  0.24766265E+00  0.31054219E+01
   eta is restricted to be zero

log likelihood function =  -0.24835581E+01

LR test of the one-sided error =   0.20900436E+02
with number of restrictions = 2
 [note that this statistic has a mixed chi-square distribution]

number of iterations =     20

(maximum number of iterations set at :   100)

number of cross-sections =      6

number of time periods =      1

total number of observations =      6

thus there are:      0  obsns not in the panel

covariance matrix :

  0.99977405E+00 -0.70477299E-03 -0.92427711E-03 -0.66310922E-03 -0.16442902E-02
 -0.41694597E-03  0.53256173E-03  0.28126465E-02 -0.11533645E-01  0.32233523E-03
  0.18671549E-02 -0.52210466E-02  0.12231368E-02 -0.73580040E-02 -0.66485587E-02
 -0.12239536E-02 -0.38065373E-10  0.19000896E-03
 -0.70477299E-03  0.99426207E+00 -0.27211225E-02 -0.18367878E-02 -0.45456347E-02
 -0.39259515E-01  0.76747683E-02  0.13654641E-01 -0.28421803E-01 -0.26986382E-01
 -0.21562630E-01 -0.34995116E-01  0.88277559E-02 -0.17300805E-01 -0.15533414E-01
 -0.19264281E-02  0.96851448E-10  0.30622090E-02
 -0.92427711E-03 -0.27211225E-02  0.99301950E+00 -0.24144395E-02 -0.59746427E-02
  0.21972694E-02 -0.39614141E-01  0.16347580E-01 -0.36969803E-01 -0.14490180E-01
  0.12032805E-01 -0.14640934E-01 -0.15524452E-01 -0.44311431E-01 -0.22178967E-01
 -0.31541763E-02  0.25919828E-09  0.57360598E-02
 -0.66310922E-03 -0.18367878E-02 -0.24144395E-02  0.99526000E+00 -0.52443749E-02
  0.17943103E-02  0.79858207E-02 -0.33728971E-01 -0.38915313E-01  0.57732664E-02
 -0.71932884E-02 -0.15721170E-01 -0.14006761E-01 -0.22756380E-01 -0.41515974E-01
 -0.48221436E-02 -0.16735543E-09 -0.15846627E-03
 -0.16442902E-02 -0.45456347E-02 -0.59746427E-02 -0.52443749E-02  0.98853314E+00
  0.81662132E-03  0.61410994E-02  0.14148779E-01 -0.78729015E-01  0.66906252E-02
  0.11009165E-01 -0.33759345E-01  0.90498691E-02 -0.45781048E-01 -0.43225884E-01
 -0.43625521E-02 -0.13686733E-09 -0.51556828E-03
 -0.41694597E-03 -0.39259515E-01  0.21972694E-02  0.17943103E-02  0.81662132E-03
  0.57874165E+00  0.55856660E-01  0.59120805E-01  0.25067629E-01 -0.29360771E+00
 -0.29595197E+00 -0.23263291E+00  0.60816071E-01  0.40739612E-01  0.45852822E-01
  0.92349097E-02 -0.17022927E-09  0.25581171E-02
  0.53256173E-03  0.76747683E-02 -0.39614141E-01  0.79858207E-02  0.61410994E-02
  0.55856660E-01  0.32967326E+00  0.72421362E-01  0.53142978E-01 -0.19011968E+00
  0.77202988E-01  0.57461292E-01 -0.30103936E+00 -0.23026716E+00  0.88807516E-01
 -0.37221370E-02 -0.18605261E-08 -0.59294946E-02
  0.28126465E-02  0.13654641E-01  0.16347580E-01 -0.33728971E-01  0.14148779E-01
  0.59120805E-01  0.72421362E-01  0.33178103E+00  0.64614211E-01  0.74862551E-01
 -0.21043288E+00  0.62617212E-01 -0.28481018E+00  0.74810025E-01 -0.23852575E+00
 -0.12792087E-03 -0.80379613E-09 -0.21160252E-01
 -0.11533645E-01 -0.28421803E-01 -0.36969803E-01 -0.38915313E-01 -0.78729015E-01
  0.25067629E-01  0.53142978E-01  0.64614211E-01  0.46179850E+00  0.75867678E-01
  0.63629612E-01 -0.22070107E+00  0.66164579E-01 -0.28177830E+00 -0.27588028E+00
 -0.98423684E-02 -0.11474256E-08 -0.23195419E-01
  0.32233523E-03 -0.26986382E-01 -0.14490180E-01  0.57732664E-02  0.66906252E-02
 -0.29360771E+00 -0.19011968E+00  0.74862551E-01  0.75867678E-01  0.69563741E+00
 -0.18747608E+00 -0.13578470E+00 -0.69376830E-01 -0.52499690E-01  0.58054543E-01
  0.16217571E-02  0.88894061E-09  0.25283382E-01
  0.18671549E-02 -0.21562630E-01  0.12032805E-01 -0.71932884E-02  0.11009165E-01
 -0.29595197E+00  0.77202988E-01 -0.21043288E+00  0.63629612E-01 -0.18747608E+00
  0.70271582E+00 -0.14244666E+00 -0.60918739E-01  0.71570348E-01 -0.48393074E-01
 -0.81843978E-02 -0.18837463E-08 -0.12353344E-01
 -0.52210466E-02 -0.34995116E-01 -0.14640934E-01 -0.15721170E-01 -0.33759345E-01
 -0.23263291E+00  0.57461292E-01  0.62617212E-01 -0.22070107E+00 -0.13578470E+00
 -0.14244666E+00  0.76911339E+00  0.64782686E-01 -0.99432107E-01 -0.94845358E-01
 -0.53792306E-03 -0.71718883E-09 -0.89445549E-02
  0.12231368E-02  0.88277559E-02 -0.15524452E-01 -0.14006761E-01  0.90498691E-02
  0.60816071E-01 -0.30103936E+00 -0.28481018E+00  0.66164579E-01 -0.69376830E-01
 -0.60918739E-01  0.64782686E-01  0.70573305E+00 -0.87809704E-01 -0.81372606E-01
  0.42562664E-02  0.44867678E-09  0.48153568E-02
 -0.73580040E-02 -0.17300805E-01 -0.44311431E-01 -0.22756380E-01 -0.45781048E-01
  0.40739612E-01 -0.23026716E+00  0.74810025E-01 -0.28177830E+00 -0.52499690E-01
  0.71570348E-01 -0.99432107E-01 -0.87809704E-01  0.72548571E+00 -0.14878560E+00
  0.24710897E-02  0.18704452E-08  0.18466137E-01
 -0.66485587E-02 -0.15533414E-01 -0.22178967E-01 -0.41515974E-01 -0.43225884E-01
  0.45852822E-01  0.88807516E-01 -0.23852575E+00 -0.27588028E+00  0.58054543E-01
 -0.48393074E-01 -0.94845358E-01 -0.81372606E-01 -0.14878560E+00  0.70605753E+00
  0.75797307E-02  0.32264003E-08  0.20715400E-01
 -0.12239536E-02 -0.19264281E-02 -0.31541763E-02 -0.48221436E-02 -0.43625521E-02
  0.92349097E-02 -0.37221370E-02 -0.12792087E-03 -0.98423684E-02  0.16217571E-02
 -0.81843978E-02 -0.53792306E-03  0.42562664E-02  0.24710897E-02  0.75797307E-02
  0.28273791E-01  0.47396375E-09 -0.78871720E-02
 -0.38065373E-10  0.96851448E-10  0.25919828E-09 -0.16735543E-09 -0.13686733E-09
 -0.17022927E-09 -0.18605261E-08 -0.80379613E-09 -0.11474256E-08  0.88894061E-09
 -0.18837463E-08 -0.71718883E-09  0.44867678E-09  0.18704452E-08  0.32264003E-08
  0.47396375E-09  0.26739658E-13 -0.37864711E-08
  0.19000896E-03  0.30622090E-02  0.57360598E-02 -0.15846627E-03 -0.51556828E-03
  0.25581171E-02 -0.59294946E-02 -0.21160252E-01 -0.23195419E-01  0.25283382E-01
 -0.12353344E-01 -0.89445549E-02  0.48153568E-02  0.18466137E-01  0.20715400E-01
 -0.78871720E-02 -0.37864711E-08  0.61336787E-01

technical efficiency estimates :

     firm             eff.-est.

       1           0.33638665E+00
       2           0.35870563E+00
       3           0.99964393E+00
       4           0.38523719E+00
       5           0.43143388E+00
       6           0.37749316E+00

 mean efficiency =   0.48148341E+00