三阶段DEA第二阶段求出冗余项后如何调整产出值进行三阶段计算 [推广有奖]

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岳瑶 发表于 2012-2-19 16:48:44 |只看作者 |坛友微信交流群|倒序 |AI写论文

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根据多数文献所写，在第一阶段通过DEAP2.1软件求出效率后（产出导向型），第二阶段用第一阶段产出松弛变量作为被解释变量，加入环境变量，用frontier4.1算出如下结果。如题，如何调整产出值，求三阶段效率？虽然悬赏不多，还望热心人多提宝贵意见。
注：决策单位为76，投入指标为6，产出指标为2.
utput from the program FRONTIER (Version 4.1c)

instruction file = eg2.ins
data file =       eg2.dta

Error Components Frontier (see B&C 1992)
The model is a production function
The dependent variable is not logged

the ols estimates are :
               coefficient    standard-error t-ratio
  beta 0       -0.22651321E+02  0.11170162E+02 -0.20278418E+01
  beta 1       -0.16323482E-01  0.19065608E-01 -0.85617419E+00
  beta 2       0.88980281E+01  0.36102020E+01  0.24646898E+01
  sigma-squared  0.30126476E+03
log likelihood function =  -0.32321252E+03
the estimates after the grid search were :
  beta 0       -0.19566867E+02
  beta 1       -0.16323482E-01
  beta 2       0.88980281E+01
  sigma-squared  0.29888659E+03
  gamma       0.50000000E-01
mu is restricted to be zero
eta is restricted to be zero

iteration =    0  func evals =    20  llf = -0.32335455E+03
-0.19566867E+02-0.16323482E-01 0.88980281E+01 0.29888659E+03 0.50000000E-01
gradient step
iteration =    5  func evals =    84  llf = -0.32324758E+03
-0.19753777E+02-0.16432444E-01 0.83909921E+01 0.29888152E+03 0.84745079E-02
iteration = 10  func evals = 195  llf = -0.32323592E+03
-0.20980606E+02-0.17017501E-01 0.85767576E+01 0.29856512E+03 0.17562523E-02
iteration = 15  func evals = 295  llf = -0.32322930E+03
-0.22232721E+02-0.16284515E-01 0.89273223E+01 0.29820233E+03 0.12620267E-02
iteration = 20  func evals = 385  llf = -0.32322887E+03
-0.22442639E+02-0.16367809E-01 0.89032455E+01 0.29806166E+03 0.25182115E-03
pt better than entering pt cannot be found
iteration = 25  func evals = 483  llf = -0.32322748E+03
-0.22829305E+02-0.16274954E-01 0.89497107E+01 0.29760107E+03 0.10000000E-07

the final mle estimates are :
               coefficient    standard-error t-ratio
  beta 0       -0.22829305E+02  0.11038506E+02 -0.20681516E+01
  beta 1       -0.16274954E-01  0.18800725E-01 -0.86565565E+00
  beta 2       0.89497107E+01  0.35328077E+01  0.25333139E+01
  sigma-squared  0.29760107E+03  0.43326239E+01  0.68688415E+02
  gamma       0.10000000E-07  0.50577811E-03  0.19771516E-04
mu is restricted to be zero
eta is restricted to be zero
log likelihood function =  -0.32322748E+03
the likelihood value is less than that obtained
using ols! - try again using different starting values
number of iterations =    25
(maximum number of iterations set at : 100)
number of cross-sections =    76
number of time periods =    1
total number of observations =    76
thus there are:    0  obsns not in the panel

covariance matrix :
  0.12184862E+03 -0.35657528E-01 -0.38670499E+02  0.48235040E+02 -0.35160474E-03
-0.35657528E-01  0.35346727E-03  0.22167863E-02 -0.26098712E-01 -0.12064179E-06
-0.38670499E+02  0.22167863E-02  0.12480730E+02 -0.15633748E+02 -0.32841463E-04
  0.48235040E+02 -0.26098712E-01 -0.15633748E+02  0.18771630E+02 -0.91217044E-03
-0.35160474E-03 -0.12064179E-06 -0.32841463E-04 -0.91217044E-03  0.25581150E-06

technical efficiency estimates :

   firm          eff.-est.
   1          0.10000000E+01
   2          0.10000000E+01
   3          0.10000000E+01
   4          0.10000000E+01
   5          0.10000000E+01
   6          0.99950101E+00
   7          0.99983796E+00
   8          0.99981888E+00
   9          0.99971994E+00
   10          0.99983796E+00
   11          0.99982886E+00
   12          0.99981888E+00
   13          0.99981888E+00
   14          0.99976308E+00
   15          0.99979470E+00
   16          0.99983796E+00
   17          0.99985341E+00
   18          0.99985341E+00
   19          0.99982725E+00
   20          0.99896889E+00
   21          0.99896889E+00
   22          0.99896889E+00
   23          0.99706244E+00
   24          0.99960479E+00
   25          0.99984759E+00
   26          0.99989387E+00
   27          0.99987711E+00
   28          0.99988600E+00
   29          0.99988130E+00
   30          0.99989390E+00
   31          0.99984459E+00
   32          0.99988604E+00
   33          0.99982227E+00
   34          0.99979470E+00
   35          0.99973999E+00
   36          0.99983597E+00
   37          0.99981952E+00
   38          0.99986616E+00
   39          0.10000000E+01
   40          0.99908514E+00
   41          0.10000000E+01
   42          0.99932885E+00
   43          0.10000000E+01
   44          0.99883767E+00
   45          0.10000000E+01
   46          0.99860595E+00
   47          0.10000000E+01
   48          0.99862777E+00
   49          0.10000000E+01
   50          0.99786968E+00
   51          0.10000000E+01
   52          0.99955952E+00
   53          0.99979470E+00
   54          0.99980433E+00
   55          0.99948922E+00
   56          0.99958464E+00
   57          0.99979470E+00
   58          0.99472525E+00
   59          0.10000000E+01
   60          0.10000000E+01
   61          0.99472525E+00
   62          0.97945125E+00
   63          0.10000000E+01
   64          0.10000000E+01
   65          0.99981888E+00
   66          0.10000000E+01
   67          0.10000000E+01
   68          0.99896889E+00
   69          0.10000000E+01
   70          0.99811937E+00
   71          0.10000000E+01
   72          0.10000000E+01
   73          0.10000000E+01
   74          0.10000000E+01
   75          0.10000000E+01
   76          0.10000000E+01

mean efficiency = 0.99927324E+00