Tests on A answer questions about common driving forces in the system. When constructing constraints, interpret the rows and columns of the n-by- r matrix A as follows:

• Row i of A contains the adjustment speeds of variable ${y}_{it}$ to disequilibrium in each of the r cointegrating relations.

• Column j of A contains the adjustment speeds of each of the n variables to disequilibrium in cointegrating relation j.

For example, an all-zero row in A indicates a variable that is weakly exogenous with respect to the coefficients in B. Such a variable may affect other variables, but does not adjust to disequilibrium in the cointegrating relations. Similarly, a standard unit vector column in A indicates a variable that is exclusively adjusting to disequilibrium in a particular cointegrating relation.

To demonstrate, we test for weak exogeneity of the inflation rate with respect to interest rates:

```load Data_Canada Y = Data(:,3:end); % Interest rate data y1 = Data(:,1); % CPI-based inflation rate YI = [y1,Y]; [hA,pValueA] = jcontest(YI,1,'ACon',[1 0 0 0]')```
```hA = logical 0 ```
```pValueA = 0.3206 ```

The test fails to reject the null hypothesis. Again, the test is conducted with default settings. Proper economic inference would require a more careful analysis of model and rank specifications.

Constrained parameter estimates are accessed via a fifth output argument from `jcontest`. For example, the constrained, rank 1 estimate of A is obtained by referencing the fifth output with dot (`.`) indexing:

```[~,~,~,~,mles] = jcontest(YI,1,'ACon',[1 0 0 0]'); Acon = mles.paramVals.A```
```Acon = 4×1 0 0.1423 0.0865 0.2862 ```

The first row of A is 0, as specified by the constraint.