[问答] 请教关于协整向量和协整方程问题 [推广有奖]

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乖乖的烤地瓜 发表于 2010-7-9 16:36:55 |AI写论文

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我用johansen协整检验得到如下结果
Date: 07/09/10 Time: 16:11
Sample (adjusted): 1997Q1 2009Q2
Included observations: 50 after adjustments
Trend assumption: Linear deterministic trend
Series: LOGCPI LOGE LOGGDP_SA
Lags interval (in first differences): 1 to 3

Unrestricted Cointegration Rank Test (Trace)

Hypothesized  Trace 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.439023  39.74279  29.79707  0.0026
At most 1  0.194359  10.83904  15.49471  0.2216
At most 2  0.000663  0.033182  3.841466  0.8554

Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized  Max-Eigen 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.439023  28.90375  21.13162  0.0033
At most 1  0.194359  10.80586  14.26460  0.1642
At most 2  0.000663  0.033182  3.841466  0.8554

Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Cointegrating Coefficients (normalized by b'*S11*b=I):

LOGCPI LOGE LOGGDP_SA
-42.30947 -21.53148  6.356762
58.59933 -18.75160 -5.731823
4.849178  11.41469  1.969624

Unrestricted Adjustment Coefficients (alpha):

D(LOGCPI)  0.001036 -0.000163 -4.94E-05
D(LOGE) -0.000218  0.003033 -2.62E-05
D(LOGGDP_SA)  0.007981  0.000957  0.000134

1 Cointegrating Equation(s): Log likelihood  567.2294

Normalized cointegrating coefficients (standard error in parentheses)
LOGCPI LOGE LOGGDP_SA
1.000000  0.508904 -0.150244
  (0.13132)  (0.01326)

Adjustment coefficients (standard error in parentheses)
D(LOGCPI) -0.043830
  (0.01544)
D(LOGE)  0.009227
  (0.04715)
D(LOGGDP_SA) -0.337672
  (0.07210)

2 Cointegrating Equation(s): Log likelihood  572.6323

Normalized cointegrating coefficients (standard error in parentheses)
LOGCPI LOGE LOGGDP_SA
1.000000  0.000000 -0.118055
(0.01145)
0.000000  1.000000 -0.063253
(0.02554)

Adjustment coefficients (standard error in parentheses)
D(LOGCPI) -0.053357 -0.019257
  (0.02630)  (0.01039)
D(LOGE)  0.186966 -0.052180
  (0.07249)  (0.02864)
D(LOGGDP_SA) -0.281564 -0.189797
  (0.12267)  (0.04846)

我个人的理解是在5%的显著性水平下迹统计量和最大特征值都表示存在一个协整向量，可是下面却出现了两个协整方程，三个协整向量？不知道选择哪个？是不是看极大似然函数小的那个选择方程？协整向量如何判断呢？

问题2：协整向量个数和协整方程个数应该是相同的吗？

望高手指教