R语言在选择带有趋势项的johansen检验之后，做VECM模型，为什么模型中没有trend项?

yueyueer-

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收藏 2019-02-18

悬赏 20 个论坛币未解决

R语言程序如下：
jo1=ca.jo(data1,type="trace",ecdet = ('trend'),K=3,spec="longrun",season=NULL)
vecm.ols=cajorls(jo1,r=1)
summary(vecm.ols$rlm)

结果是这样的：
Response b.d :

Call:
lm(formula = b.d ~ ect1 + constant + b.dl1 + a.dl1 + b.dl2 +
a.dl2 - 1, data = data.mat)

Residuals:
   Min       1Q Median       3Q    Max
-0.147699 -0.012363  0.001038  0.015584  0.098315

Coefficients:
         Estimate Std. Error t value Pr(>|t|)
ect1    0.0004875  0.0009597 0.508 0.612
constant -0.1299624  0.2585723  -0.503 0.616
b.dl1    0.0844789  0.0649283 1.301 0.194
a.dl1 -0.0039859  0.0236960  -0.168 0.867
b.dl2    0.0618550  0.0648104 0.954 0.341
a.dl2    0.0104587  0.0305578 0.342 0.732

Residual standard error: 0.033 on 236 degrees of freedom
Multiple R-squared:  0.01655,       Adjusted R-squared:  -0.008451
F-statistic: 0.662 on 6 and 236 DF,  p-value: 0.6804

Response a.d :

Call:
lm(formula = a.d ~ ect1 + constant + b.dl1 + a.dl1 + b.dl2 +
a.dl2 - 1, data = data.mat)

Residuals:
   Min    1Q Median    3Q    Max
-1.24493 -0.01642  0.00068  0.02846  0.23329

Coefficients:
      Estimate Std. Error t value Pr(>|t|)
ect1    -0.015848 0.002615  -6.062 5.30e-09 ***
constant  4.280570 0.704459 6.076 4.89e-09 ***
b.dl1 -0.044655 0.176892  -0.252 0.801
a.dl1 -0.844534 0.064558 -13.082  < 2e-16 ***
b.dl2    0.116768 0.176571 0.661 0.509
a.dl2 -0.695510 0.083252  -8.354 5.66e-15 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.0899 on 236 degrees of freedom
Multiple R-squared:  0.4225,       Adjusted R-squared:  0.4078
F-statistic: 28.77 on 6 and 236 DF,  p-value: < 2.2e-16

johansen检验的时候我的选的是带有趋势项的，为什么估计出的VECM模型里面是constant项呢,而不是trend项，还有就是请问为什么第一个方程的系数都不显著，而第二个方程有的显著呢？