请问,front做的SFA模型分析,怎样进行数据调整啊?????代入第三阶段计算的数据调整。output from the program FRONTIER (Version 4.1c)
instruction file = wz-i.txt
data file = wz-d.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 0.10849233E-01 0.70935104E-01 0.15294590E+00
beta 1 0.24150237E-02 0.10325328E-01 0.23389317E+00
beta 2 0.42958419E-02 0.16447183E-01 0.26119013E+00
beta 3 -0.59856400E-02 0.76770081E-02 -0.77968395E+00
sigma-squared 0.70460577E-03
log likelihood function = 0.11258442E+03
the estimates after the grid search were :
beta 0 0.41929618E-01
beta 1 0.24150237E-02
beta 2 0.42958419E-02
beta 3 -0.59856400E-02
sigma-squared 0.16142276E-02
gamma 0.94000000E+00
mu is restricted to be zero
eta is restricted to be zero
iteration = 0 func evals = 20 llf = 0.12347442E+03
0.41929618E-01 0.24150237E-02 0.42958419E-02-0.59856400E-02 0.16142276E-02
0.94000000E+00
gradient step
pt better than entering pt cannot be found
iteration = 1 func evals = 28 llf = 0.12347442E+03
0.41929618E-01 0.24150237E-02 0.42958419E-02-0.59856400E-02 0.16142276E-02
0.94000000E+00
the final mle estimates are :
coefficient standard-error t-ratio
beta 0 0.41929618E-01 0.10000000E+01 0.41929618E-01
beta 1 0.24150237E-02 0.10000000E+01 0.24150237E-02
beta 2 0.42958419E-02 0.10000000E+01 0.42958419E-02
beta 3 -0.59856400E-02 0.10000000E+01 -0.59856400E-02
sigma-squared 0.16142276E-02 0.10000000E+01 0.16142276E-02
gamma 0.94000000E+00 0.10000000E+01 0.94000000E+00
mu is restricted to be zero
eta is restricted to be zero
log likelihood function = 0.12347442E+03
LR test of the one-sided error = 0.21780008E+02
with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]
number of iterations = 1
(maximum number of iterations set at : 100)
number of cross-sections = 50
number of time periods = 1
total number of observations = 50
thus there are: 0 obsns not in the panel
covariance matrix :
0.10000000E+01 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00
0.00000000E+00 0.10000000E+01 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00
0.00000000E+00 0.00000000E+00 0.10000000E+01 0.00000000E+00 0.00000000E+00
0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.10000000E+01 0.00000000E+00
0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.10000000E+01
0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.10000000E+01
technical efficiency estimates :
firm eff.-est.
1 0.96879287E+00
2 0.98015994E+00
3 0.97704575E+00
4 0.97967720E+00
5 0.97895340E+00
6 0.95854298E+00
7 0.87599583E+00
8 0.98063824E+00
9 0.97678012E+00
10 0.97831312E+00
11 0.96656892E+00
12 0.96652269E+00
13 0.98287831E+00
14 0.98005454E+00
15 0.97812532E+00
16 0.97538370E+00
17 0.98276748E+00
18 0.98312426E+00
19 0.92384853E+00
20 0.95294709E+00
21 0.97885329E+00
22 0.98349100E+00
23 0.96520522E+00
24 0.98250329E+00
25 0.97527795E+00
26 0.95796900E+00
27 0.98228602E+00
28 0.98325913E+00
29 0.97999471E+00
30 0.94436558E+00
31 0.98091905E+00
32 0.87883852E+00
33 0.98340416E+00
34 0.98211061E+00
35 0.97605345E+00
36 0.98312426E+00
37 0.98236476E+00
38 0.98299789E+00
39 0.97960875E+00
40 0.98391945E+00
41 0.98356095E+00
42 0.98009223E+00
43 0.96546121E+00
44 0.98189801E+00
45 0.97572159E+00
46 0.97982596E+00
47 0.97751468E+00
48 0.97415577E+00
49 0.97751468E+00
50 0.96605916E+00