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Freeze VAR model then get the marginal likelihood.
For example:
freeze(tab01) var01
!mll=@val(tab01(r,c))

dlogrgdp to dlogop: impulse responses are insignificant for all periods dlogop to dlogop: impulse responses are significant for 1st period (impact period) dlogstir to dlogop: impulse responses are significant for 2nd period dlogltir to dlogop: impulse responses are significant for 1st period (impact...

First, do not impose the weak exogeneity restrictions, just impose the restrictions on the cointegration vectors based on the theory.
Second, if these restrictions is accepted then impose the weak exogeneity restrictions sequentially.

My suggestions:
1. If the second cointegration vector is money demand then you try to restrict foreign variables to zero.
2. Carefully impose the weak exogeneity restrictions.

The first restrictions is totally unacceptable. That is why Eviews did not estimate t statistics.
1. On the forum you posted B(2,2)=1, but you actually imposed zero restriction.
2. The convergence is not achieved (max iteration is reached)
3. LR test for binding restriction is rejected.

Could you post the results?

No built-in procedure. The trick is to make model from VAR model.(proc/make model). Then simulate it.

If the confidence interval (or band) does not contain zero (horizontal axis) then it is statistically significant.

If you define a new variable (for example, return) then your interpretation is almost correct. But you need to multiply Rt by 100.

Ok. Could you post the results?

Sorry, you mean that the samples were different?

Check your sample size.

Yes

Yes, they represents +-1|+-2 SD.

That is Eviews bug. You should update your Eviews.