Dear Mitch,
have you taken a look at ?SVAR in package (vars), though the inclusion of
exogenous variables is currently not supported.
In principle, your model form is a simultaneous interdependent multiple
equation model. For estimating these kind of models have a look at the package
systemfit and/or you can estimate your reaction functions by OLS, collect these
with -- if applicable -- identities and solve this model on a per period basis
by applying for instance the Gauß-Seidel algorithm.
As an aside, one can cast these type models with the Fair-Parke program and
call FP from R with system(). This last option is probably more appropriate for
larger macroeconomic models. For more information see:
http://fairmodel.econ.yale.edu/fp/fp.htm
Best,
Bernhard
|> -----Original Message-----
|> From: r-help-boun...@r-project.org
|> [mailto:r-help-boun...@r-project.org] On Behalf Of Downey, Patrick
|> Sent: Friday, March 12, 2010 12:53 AM
|> To: r-help@r-project.org
|> Subject: [R] VAR with contemporaneous effects
|>
|> Hi,
|>
|> I would like to estimate a VAR of the form:
|>
|> Ay_t = By_t-1 + Cy_t-2 + ... + Dx_t + e_t
|>
|> Where A is a non-diagonal matrix of coefficients, B and C
|> are matricies of
|> coefficients and D is a matrix of coefficients for the
|> exogenous variables.
|>
|> I don't think the package {vars} can do this because I
|> want to include
|> contemporaneous cross-variable impacts.
|>
|> So I want y1_t to affect y2_t and I think in {vars} I can
|> only have y1_t-1
|> affect y2_t.
|>
|> {vars} will only allow VARs of the form:
|>
|> y_t = By_t-1 + Cy_t-2 + ... + Dx_t + e_t
|>
|> Solutions? Maybe another package? Or maybe I'm thinking
|> about this wrong?
|>
|> (And I know that I have to put constraints on A to get
|> identification - I'm
|> willing to do that).
|>
|> Thanks,
|> Mitch Downey
|>
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