Forecast Error Variance Decomposition
This function calculates the forecast error variance decomposition (FEVDs) for Cholesky and sign-identified shocks.
fevd(x, rotation.matrix=NULL, var.slct=NULL, verbose=TRUE)
x |
an object of class |
rotation.matrix |
If |
var.slct |
character vector that contains the variables for which forecast error variance decomposition should be performed. If |
verbose |
If set to |
Since the calculations are very time consuming, the FEVDs are based on the posterior median only (as opposed to calculating FEVDs for each MCMC sweep). In case the underlying shock has been identified via sign restrictions, the rotation matrix corresponds to the one that fulfills the sign restrictions at the posterior median of the estimated coefficients. More precisely, the algorithm searches for 50 rotation matrices that fulfill the sign restrictions at the posterior median of the coefficients and then singles out the rotation matrix that minimizes the distance to the median of the impulse responses as suggested in Fry and Pagan (2011).
Returns a list with two elements
FEVD an array of size (K times horizon times N), where K are all variables in the system, horizon is the specified impulse response horizon and N is the size of the decomposed structural variables (if var.slct=NULL then K=N).
xglobal used data of the model.
Maximilian Boeck, Martin Feldkircher, Florian Huber
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