leihengzhishang 发表于 2012-3-8 16:23 
把结果发上来吧
Vector Error Correction Estimates
Date: 03/07/12 Time: 19:21
Sample (adjusted): 1989 2009
Included observations: 21 after adjustments
Standard errors in ( ) & t-statistics in [ ]
Cointegrating Eq: CointEq1 CointEq2 CointEq3
LNPTX(-1) 1.000000 0.000000 0.000000
LNKL(-1) 0.000000 1.000000 0.000000
LNFDI(-1) 0.000000 0.000000 1.000000
LNPATENT(-1) -30.09744 27.99924 64.43317
(4.50133) (4.39062) (9.79054)
[-6.68634] [ 6.37705] [ 6.58117]
LNSCALE(-1) 64.19291 -61.52855 -141.2088
(10.7683) (10.5035) (23.4214)
[ 5.96129] [-5.85794] [-6.02905]
LNER(-1) -31.85917 29.20344 68.22184
(6.44293) (6.28447) (14.0136)
[-4.94482] [ 4.64692] [ 4.86827]
C -206.3919 191.1462 446.7495
Error Correction: D(LNPTX) D(LNKL) D(LNFDI) D(LNPATENT) D(LNSCALE) D(LNER)
CointEq1 -1.066974 0.111583 -1.377465 -0.792915 0.067620 -0.643999
(0.41773) (0.35722) (1.09310) (0.53184) (0.42087) (0.55200)
[-2.55421] [ 0.31237] [-1.26014] [-1.49088] [ 0.16067] [-1.16666]
CointEq2 -0.473864 -0.639881 -1.924305 -0.115189 -0.644618 -0.837519
(0.42349) (0.36214) (1.10817) (0.53917) (0.42667) (0.55961)
[-1.11895] [-1.76692] [-1.73647] [-0.21364] [-1.51082] [-1.49660]
CointEq3 -0.279167 0.330591 0.228706 -0.313986 0.322319 0.075441
(0.19072) (0.16309) (0.49907) (0.24282) (0.19215) (0.25202)
[-1.46375] [ 2.02701] [ 0.45827] [-1.29309] [ 1.67742] [ 0.29934]
D(LNPTX(-1)) 0.148130 -0.780596 -1.521930 0.051391 -0.053955 -0.512616
(0.36431) (0.31154) (0.95331) (0.46383) (0.36704) (0.48141)
[ 0.40660] [-2.50563] [-1.59646] [ 0.11080] [-0.14700] [-1.06482]
D(LNKL(-1)) 0.210891 -0.193291 0.738866 0.574469 0.014847 0.297262
(0.24419) (0.20881) (0.63898) (0.31089) (0.24602) (0.32268)
[ 0.86365] [-0.92566] [ 1.15632] [ 1.84782] [ 0.06035] [ 0.92124]
D(LNFDI(-1)) -0.021511 -0.079647 -0.530801 -0.238828 -0.082079 -0.160049
(0.18827) (0.16100) (0.49267) (0.23970) (0.18969) (0.24879)
[-0.11425] [-0.49470] [-1.07740] [-0.99635] [-0.43271] [-0.64331]
D(LNPATENT(-1)) -0.691660 0.084489 -0.934094 -0.383517 -0.140282 -0.985706
(0.52517) (0.44909) (1.37424) (0.66863) (0.52911) (0.69397)
[-1.31703] [ 0.18813] [-0.67972] [-0.57359] [-0.26513] [-1.42038]
D(LNSCALE(-1)) -0.071146 -0.157115 1.043457 -0.245429 0.368399 0.194795
(0.31732) (0.27135) (0.83034) (0.40400) (0.31970) (0.41931)
[-0.22421] [-0.57901] [ 1.25666] [-0.60750] [ 1.15233] [ 0.46456]
D(LNER(-1)) -0.317409 0.097761 -1.396960 -0.072860 -0.144667 -0.653158
(0.39006) (0.33356) (1.02070) (0.49661) (0.39299) (0.51544)
[-0.81374] [ 0.29308] [-1.36863] [-0.14671] [-0.36812] [-1.26718]
C 0.276743 0.288050 0.485036 0.292294 0.115131 0.327504
(0.14149) (0.12100) (0.37025) (0.18015) (0.14256) (0.18697)
[ 1.95587] [ 2.38064] [ 1.31001] [ 1.62255] [ 0.80763] [ 1.75160]
R-squared 0.676188 0.858629 0.606359 0.661126 0.747717 0.541264
Adj. R-squared 0.411251 0.742962 0.284289 0.383865 0.541303 0.165935
Sum sq. resids 0.060195 0.044019 0.412183 0.097574 0.061102 0.105112
S.E. equation 0.073975 0.063259 0.193575 0.094183 0.074530 0.097753
F-statistic 2.552257 7.423283 1.882695 2.384490 3.622419 1.442106
Log likelihood 31.67644 34.96271 11.47579 26.60478 31.51945 25.82339
Akaike AIC -2.064423 -2.377401 -0.140551 -1.581407 -2.049472 -1.506990
Schwarz SC -1.567031 -1.880009 0.356840 -1.084016 -1.552080 -1.009598
Mean dependent 0.148895 0.121957 0.100863 0.221375 0.101583 0.028914
S.D. dependent 0.096410 0.124774 0.228813 0.119987 0.110045 0.107036
Determinant resid covariance (dof adj.) 4.69E-15
Determinant resid covariance 9.69E-17
Log likelihood 208.3782
Akaike information criterion -12.41697
Schwarz criterion -8.537312
另外，想请教你下，标准化的协整向量里为什么我估计出来的不含常数项，而且系数都很大，是什么原因呢？ 我在做协整检验的时候，外生变量那栏填了C啊？万分感谢~~~~
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