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The VARMAX Procedure

I(2) Model

The VARX(,) model can be written in the error correction form:

     

Let .

If and have full-rank , and , then is an process.

If the condition fails and has reduced-rank where and are matrices with , then and are defined as matrices of full rank such that and .

If and have full-rank , then the process is , which has the implication of model for the moving-average representation.

     

The matrices , , and are determined by the cointegration properties of the process, and and are determined by the initial values. For details, see Johansen (1995a).

The implication of the model for the autoregressive representation is given by

     

where and .

Test for I(2)

The cointegrated model is given by the following parameter restrictions:

     

where and are matrices with . Let represent the model where and have full-rank , let represent the model where and have full-rank , and let represent the model where and have rank . The following table shows the relation between the models and the models.

Table 32.2 Relation between the and Models
         

       

 

k

 

k-1

 

 

       

0

1

   

           

           

Johansen (1995a) proposed the two-step procedure to analyze the model. In the first step, the values of are estimated using the reduced rank regression analysis, performing the regression analysis , , and on and . This gives residuals , , and , and residual product moment matrices

     

Perform the reduced rank regression analysis on corrected for , and , and solve the eigenvalue problem of the equation

     

where for .

In the second step, if are known, the values of are determined using the reduced rank regression analysis, regressing on corrected for , and .

The reduced rank regression analysis reduces to the solution of an eigenvalue problem for the equation

     

where

     
     
     

where .

The solution gives eigenvalues and eigenvectors . Then, the ML estimators are

     
     

The likelihood ratio test for the reduced rank model with rank in the model is given by

     

The following statements compute the rank test to test for cointegrated order 2:

proc varmax data=simul2;
   model y1 y2 / p=2 cointtest=(johansen=(iorder=2));
run;

The last two columns in Figure 32.60 explain the cointegration rank test with integrated order 1. The results indicate that there is the cointegrated relationship with the cointegration rank 1 with respect to the 0.05 significance level because the test statistic of 0.5552 is smaller than the critical value of 3.84. Now, look at the row associated with . Compare the test statistic value, 211.84512, to the critical value, 3.84, for the cointegrated order 2. There is no evidence that the series are integrated order 2 at the 0.05 significance level.

Figure 32.60 Cointegrated I(2) Test (IORDER= Option)
The VARMAX Procedure

Cointegration Rank Test for I(2)
r\k-r-s 2 1 Trace
of I(1)
5% CV of I(1)
0 720.40735 308.69199 61.7522 15.34
1   211.84512 0.5552 3.84
5% CV I(2) 15.34000 3.84000    

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