## Multivariate time series

Hi all

I am stuck on a HW problem that goes as follows:

"Consider the following following bivariate AR model:

Xt,1= -.003595-.12539Xt-1,1 - 2.483324Xt-1,2 + Zt,1
Xt,2= -.000267+.007929Xt-1,1+.7937959Xt-1,2+Zt,2

Zt is multivariate white noise. Prove or disprove the model causal.

So I know that to show that a bivariate model is causal I have to find the determinant of the above matrix and if it's non zero then my model is causal. I'm just not sure if it's really that easy...am I missing something? Thanks.