Comparing SVAR results in RATS with Eviews

Questions and discussions on Vector Autoregressions

Comparing SVAR results in RATS with Eviews

Postby alvarezcc » Fri Aug 05, 2011 1:48 pm

Hi! I estimated a SVAR in both Eviews and RATS but the IRF's that I get in both programs are different in direction even if the magnitud is similar (one seems to mirror the other but with the oposite direction). For what reason could I be getting these results?

On the other hand, I estimated an A-B model for the structural innovations. Comparing the estimations performed in both programs I get similar coeficients estimates for the parameters of the A matrix, but the parameters in the B matrix are strikingly different. What could be the source of these difference? (I know that there could exist differences because of the method used in the estimation: BFGS in RATS and analytic derivatives in Eviews)

Last, I would like to know if it is possible to calculate impulse responses for shocks in the exogenous variables and how to calculate 1% shocks instead of one standar deviation shock.
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Re: Comparing SVAR results in RATS with Eviews

Postby TomDoan » Fri Aug 05, 2011 3:58 pm

If FF' factors the matrix sigma, then so does F with any collection of sign flips on its columns. For most factorizations, we use the sign convention that F has positive values on its diagonal, which makes sense when we associate shock i with variable i. However, with some structural VAR's, there is no obvious association between shocks and variables---for instance in the Blanchard-Quah model, both the supply and demand shocks are interpreted as (positive) shocks to GDP. But the signs produced by estimating the model might not match with that. If you're using CVMODEL, you can get the sign pattern you want by putting the normalizing 1's at the locations you want; they don't have to be on the diagonal. If you're using a constructive factorization like BQ, you can flip the column signs if they come out wrong. For more, see section 7.5.3 in the Version 8 User's Guide.
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