How to estimate SVAR model and see if it is stationary with eigenvalues

Hello, I am trying to solve this problem: We need to estimate the reduced form by OLS of the following equations: y_t=alpha*y_(t-1)+Beta*m_(t-1) + error term m_t=miu*m_(t-1)+omega*y_t-1 + error term

where y is the demeaned gdp growth and m is the demeaned money growth. We already estimate all the parameters, alpha=0.402 ; beta=0.233 ; miu=0.639 ; omega=-0.014

The problem is that now, we need to check if the process is stationary by calculate the eigenvalues. We know that we should put this in matrixes and use some matrix A, but we have no idea how to compute that.

Thank you so much for the help

-- Maryline Ribeiro

[John D'Errico]

Please don't post the same question an hour later just because your first question has not received an answer.

If you got no answer, it may have been that your question was confusing. It may have been that nobody was interested in your question sufficiently to figure out what it was that you were asking, what you actually needed.

So, try giving more information. Try making your question more readable. Show what you have done so far.

Personally, what you are asking is confusing, throwing around some jargon that I think you don't really understand. So why not look more carefully at what you have written? Think about it as if you were being asked that same question. What information would you need to answer it?