请教达人帮我看一下这个使用frontier运算得出来的结果

janet_910

5586

收藏 2008-05-07

命令文件：

1               1=ERROR COMPONENTS MODEL, 2=TE EFFECTS MODEL
eg1-dta.txt         DATA FILE NAME
eg1-out.txt         OUTPUT FILE NAME
2               1=PRODUCTION FUNCTION, 2=COST FUNCTION
y               LOGGED DEPENDENT VARIABLE (Y/N)
14              NUMBER OF CROSS-SECTIONS
1               NUMBER OF TIME PERIODS
14              NUMBER OF OBSERVATIONS IN TOTAL
4               NUMBER OF REGRESSOR VARIABLES (Xs)
n               MU (Y/N) [OR DELTA0 (Y/N) IF USING TE EFFECTS MODEL]
y               ETA (Y/N) [OR NUMBER OF TE EFFECTS REGRESSORS (Zs)]
n               STARTING VALUES (Y/N)
                IF YES THEN     BETA0
                                BETA1 TO
                                BETAK
                                SIGMA SQUARED
                                GAMMA
                                MU              [OR DELTA0
                                ETA                 DELTA1 TO
                                                      DELTAP]

                                NOTE: IF YOU ARE SUPPLYING STARTING VALUES
                                AND YOU HAVE RESTRICTED MU [OR DELTA0] TO BE
                                ZERO THEN YOU SHOULD NOT SUPPLY A STARTING
                                VALUE FOR THIS PARAMETER.

结果：

Output from the program FRONTIER (Version 4.1c)

instruction file = eg1-ins.txt
data file = eg1-dta.txt

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

the ols estimates are :

coefficient standard-error t-ratio

beta 0         0.15868004E+01 0.10229348E+00 0.15512235E+02
beta 1         0.77195591E+00 0.46159293E-01 0.16723738E+02
beta 2         0.17857996E+00 0.55482126E-01 0.32186936E+01
beta 3         0.29137648E-01 0.35593624E-01 0.81861989E+00
beta 4         0.71574949E+00 0.91406919E-01 0.78303645E+01
sigma-squared 0.81583486E-02

log likelihood function = 0.16888685E+02

the estimates after the grid search were :

beta 0         0.15029154E+01
beta 1         0.77195591E+00
beta 2         0.17857996E+00
beta 3         0.29137648E-01
beta 4         0.71574949E+00
sigma-squared 0.12281346E-01
gamma          0.90000000E+00
mu             0.00000000E+00
eta            0.00000000E+00

iteration =     0 func evals =     20 llf = 0.17740423E+02
     0.15029154E+01 0.77195591E+00 0.17857996E+00 0.29137648E-01 0.71574949E+00
     0.12281346E-01 0.90000000E+00 0.00000000E+00 0.00000000E+00
gradient step
iteration =     5 func evals =     43 llf = 0.18537696E+02
     0.14782516E+01 0.76607540E+00 0.18967181E+00 0.16599516E-01 0.77918427E+00
     0.12836356E-01 0.94547837E+00-0.42494927E-01 0.00000000E+00
pt better than entering pt cannot be found
iteration =     6 func evals =     51 llf = 0.18537696E+02
     0.14782516E+01 0.76607540E+00 0.18967181E+00 0.16599516E-01 0.77918427E+00
     0.12836356E-01 0.94547837E+00-0.42494927E-01 0.00000000E+00

the final mle estimates are :

coefficient standard-error t-ratio

beta 0         0.14782516E+01 0.94418554E+00 0.15656367E+01
beta 1         0.76607540E+00 0.26980054E+00 0.28394139E+01
beta 2         0.18967181E+00 0.23788038E+00 0.79734116E+00
beta 3         0.16599516E-01 0.16464679E+00 0.10081895E+00
beta 4         0.77918427E+00 0.58751887E+00 0.13262285E+01
sigma-squared 0.12836356E-01 0.52194196E-01 0.24593455E+00
gamma          0.94547837E+00 0.89460588E+00 0.10568658E+01
mu            -0.42494927E-01 0.90528012E+00 -0.46941191E-01
eta            0.00000000E+00 0.10000000E+01 0.00000000E+00

log likelihood function = 0.18537696E+02

LR test of the one-sided error = 0.32980226E+01
with number of restrictions = 3
[note that this statistic has a mixed chi-square distribution]

number of iterations = 6

(maximum number of iterations set at : 100)

number of cross-sections = 14

number of time periods = 1

total number of observations = 14

thus there are: 0 obsns not in the panel

covariance matrix :

0.89148634E+00 -0.24873643E+00 0.71297626E-01 0.11804169E+00 0.10653548E+00
-0.35462090E-02 -0.61843214E-01 -0.31227745E-01 0.00000000E+00
-0.24873643E+00 0.72792333E-01 -0.29214176E-01 -0.28177050E-01 -0.24275469E-01
-0.16879185E-02 -0.81125271E-02 0.52668803E-01 0.00000000E+00
0.71297626E-01 -0.29214176E-01 0.56587074E-01 -0.12912427E-01 -0.94381124E-01
0.87348349E-02 -0.37688373E-01 -0.18873383E+00 0.00000000E+00
0.11804169E+00 -0.28177050E-01 -0.12912427E-01 0.27108565E-01 0.49119047E-01
-0.54623990E-02 -0.20969837E-01 0.88923675E-01 0.00000000E+00
0.10653548E+00 -0.24275469E-01 -0.94381124E-01 0.49119047E-01 0.34517842E+00
-0.80871274E-02 0.36314972E+00 0.26521384E+00 0.00000000E+00
-0.35462090E-02 -0.16879185E-02 0.87348349E-02 -0.54623990E-02 -0.80871274E-02
0.27242341E-02 0.22459146E-01 -0.44901130E-01 0.00000000E+00
-0.61843214E-01 -0.81125271E-02 -0.37688373E-01 -0.20969837E-01 0.36314972E+00
0.22459146E-01 0.80031968E+00 -0.17077245E+00 0.00000000E+00
-0.31227745E-01 0.52668803E-01 -0.18873383E+00 0.88923675E-01 0.26521384E+00
-0.44901130E-01 -0.17077245E+00 0.81953210E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.10000000E+01

cost efficiency estimates :

efficiency estimates for year 1 :

firm eff.-est.

       1           0.10282716E+01
       2           0.10352434E+01
       3           0.11527963E+01
       4           0.10595196E+01
       5           0.10772122E+01
       6           0.10331596E+01
       7           0.10232192E+01
       8           0.13175927E+01
       9           0.10769889E+01
      10           0.10962023E+01
      11           0.10368850E+01
      12           0.10161276E+01
      13           0.11000742E+01
      14           0.10170084E+01

mean eff. in year 1 = 0.10764501E+01

我想测成本效率，可是计算出来的结果都小于1，不应该大于1吗，+01，+00都代表什么呀，而且我得出来的结果差异不大，因为论文急用，请各位达人多多帮忙！谢谢！

还有如何使用shazam进行数据转换呀，跪求详细操作方法！！