Conditional Variance Decomposition monetary policy

Hi there,
When estimating my model I find correct estimation for parameters in accordance with the litterature (SW).
So I run the model with 5 mh-block of 100 000 iterations with a current acceptance ratio to approximatively .4 (by adjusting the j-scale option, here to .25).
The problem is that the conditional variance decomposition find that monetary policy shock account for the majority of fluctuation of observable variables (gdp, cons, inv, wages, inflation, hours, interest rate ) using moment-varendo option.

Has anyone ever encountered this type of problem ?

Thanks in advance !

The question is at which forecast horizon?

Dear jpfeifer,
At 1 2 10 40 and to infinity. For example in gdp they account for 91% to 95%.

That is very strange. If you have the same parameters as in previous papers, but very different variance decomposition results, there must be something in your model structure that is different. Did you check the relative size of IRFs to the estimated shocks?

I didn’t check the relative size of IRFs to the estimated shock. If I understand, with my estimation impulse response from monetary policy should be more higher than other shocks ?
And if so how can fix this ?
Thanks a lot,