关于frontier4.01软件！讨论者有奖励！问题时刻更新！

step2.利用wordpad編輯eg1.pro(記住eg1.pro與eg1.dat與eg1.out 要在同一子目錄)

1 1=ERROR COMPONENTS MODEL, 2=TE EFFECTS MODEL
eg1.dat DATA FILE NAME
eg1.out OUTPUT FILE NAME
1 1=PRODUCTION FUNCTION, 2=COST FUNCTION
y LOGGED DEPENDENT VARIABLE (Y/N)
60 NUMBER OF CROSS-SECTIONS
1 NUMBER OF TIME PERIODS
60 NUMBER OF OBSERVATIONS IN TOTAL
2 NUMBER OF REGRESSOR VARIABLES (Xs)
n MU (Y/N) [OR DELTA0 (Y/N) IF USING TE EFFECTS MODEL]
n 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.

step3. 在sfa(目錄可以變更)按執行檔二下

1.因為你有eg1.pro程式檔所以先按 f

2.再輸入 eg1.pro

3.sfa目錄會產生 eg1.out 可利用wordpad 打開

Output from the program FRONTIER (Version 4.1)

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

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 0.24489834E+00 0.21360307E+00 0.11465114E+01
beta 1 0.28049246E+00 0.48066617E-01 0.58354940E+01
beta 2 0.53330637E+00 0.51498586E-01 0.10355748E+02
sigma-squared 0.11398496E+00

log likelihood function = -0.18446849E+02

the estimates after the grid search were :

beta 0 0.58014216E+00
beta 1 0.28049246E+00
beta 2 0.53330637E+00
sigma-squared 0.22067413E+00
gamma 0.80000000E+00
mu is restricted to be zero
eta is restricted to be zero

iteration = 0 func evals = 19 llf = -0.17034854E+02
0.58014216E+00 0.28049246E+00 0.53330637E+00 0.22067413E+00 0.80000000E+00
gradient step
iteration = 5 func evals = 41 llf = -0.17027230E+02
0.56160697E+00 0.28108701E+00 0.53647803E+00 0.21694170E+00 0.79718731E+00
iteration = 7 func evals = 63 llf = -0.17027229E+02
0.56161963E+00 0.28110205E+00 0.53647981E+00 0.21700046E+00 0.79720730E+00

the final mle estimates are :

coefficient standard-error t-ratio

beta 0 0.56161963E+00 0.20261668E+00 0.27718331E+01
beta 1 0.28110205E+00 0.47643365E-01 0.59001301E+01
beta 2 0.53647981E+00 0.45251553E-01 0.11855501E+02
sigma-squared 0.21700046E+00 0.63909106E-01 0.33954545E+01
gamma 0.79720730E+00 0.13642399E+00 0.58436004E+01
mu is restricted to be zero
eta is restricted to be zero

log likelihood function = -0.17027229E+02

LR test of the one-sided error = 0.28392402E+01
with number of restrictions = 1
[note that this statistic has a mixed chi-square distribution]

number of iterations = 7

(maximum number of iterations set at : 100)

number of cross-sections = 60

number of time periods = 1

total number of observations = 60

thus there are: 0 obsns not in the panel

covariance matrix :

0.41053521E-01 -0.31446721E-02 -0.80030279E-02 0.40456494E-02 0.92519362E-02
-0.31446721E-02 0.22698902E-02 0.40106205E-04 -0.29528845E-04 -0.91550467E-04
-0.80030279E-02 0.40106205E-04 0.20477030E-02 -0.47190308E-04 -0.16404645E-03
0.40456494E-02 -0.29528845E-04 -0.47190308E-04 0.40843738E-02 0.67450773E-02
0.92519362E-02 -0.91550467E-04 -0.16404645E-03 0.67450773E-02 0.18611506E-01

technical efficiency estimates :

firm eff.-est.

1 0.65068880E+00
2 0.82889151E+00
3 0.72642592E+00
4 0.74785113E+00
5 0.69133584E+00
6 0.77654637E+00
7 0.56516787E+00
8 0.73768185E+00
9 0.84388964E+00
10 0.75784167E+00
11 0.54558432E+00
12 0.93739520E+00
13 0.44809682E+00
14 0.61831027E+00
15 0.87384359E+00
16 0.54952777E+00
17 0.71262499E+00
18 0.75907226E+00
19 0.85727198E+00
20 0.80651927E+00
21 0.72458613E+00
22 0.87223606E+00
23 0.83681369E+00
24 0.75225715E+00
25 0.52974774E+00
26 0.89731683E+00
27 0.81013415E+00
28 0.78179413E+00
29 0.85610585E+00
30 0.62097885E+00
31 0.57938181E+00
32 0.74934194E+00
33 0.88192581E+00
34 0.42082174E+00
35 0.35126244E+00
36 0.88908382E+00
37 0.84118609E+00
38 0.67868899E+00
39 0.67291047E+00
40 0.83853427E+00
41 0.75964587E+00
42 0.68189614E+00
43 0.80438742E+00
44 0.88652992E+00
45 0.74299265E+00
46 0.72610191E+00
47 0.85341515E+00
48 0.78519185E+00
49 0.67207111E+00
50 0.51430249E+00
51 0.84238134E+00
52 0.85098581E+00
53 0.85963850E+00
54 0.75508293E+00
55 0.81649829E+00
56 0.75991250E+00
57 0.87350729E+00
58 0.66471456E+00
59 0.85670448E+00
60 0.70842786E+00

mean efficiency = 0.74056772E+00

dta、ins和out都用.txt就可以运算出了，不用上述的那么麻烦的。

嗬嗬，一年多了，这个帖子又热闹了。

回答一个简单问题，Frontier的结果拷到EXcel或Spss是文本格式，可以先考到Word里边，然后将文本转化成表格，再拷到EXcel或Spss就可以了。

其他的问题慢慢来，可能需要把原理整明白，否则照猫画虎，总是很容易出问题。嗬嗬，语气有点过分，但这是我的经验教训，不能有侥幸心理啊。

各位对SFA感兴趣的朋友:

大家过年好!谢谢楼主开辟此讨论空间,关于SFA的使用我还有很多地方不明白,自己找了一些文献拿出来与大家分享,同时也希望哪位大侠有SFA的经典文献和重要文献,能否挂出来或发给在下,感谢万分! forddong@126.com

太大了，只能分两次上传拉

参数就是final项上的值,重要的是一个截断正态分布的mu值要算一下

还有就是各个项的加减处理

我也是刚学 太感谢了

新手上路： 请问“先在Excel中录入原始数据，生成对数数据，再复制对数数据到*.DTA中即可”得出的分析结果与用“ *.SHA转换原始数据”得出的分析结果是否一致 ？是否会出现125楼所说的对数两次的问题？另外，请问哪位有“SHAZAM9.0、10.0专业版”，谢谢

这个帖子好！学到很多东西，谢谢楼上各位！