gmvarkit (version 2.1.4)

reorder_W_columns: Reorder columns of the W-matrix and lambda parameters of a structural GMVAR, StMVAR, or G-StMVAR model.

Description

reorder_W_columns reorder columns of the W-matrix and lambda parameters of a structural GMVAR, StMVAR, or G-StMVAR model.

Usage

reorder_W_columns(gsmvar, perm)

Value

Returns an object of class 'gsmvar' defining a structural GMVAR, StMVAR, or G-StMVAR model with the modified structural parameters and constraints.

Arguments

gsmvar

an object of class 'gsmvar', typically created with fitGSMVAR or GSMVAR.

perm

an integer vector of length \(d\) specifying the new order of the columns of \(W\). Also lambda parameters of each regime will be reordered accordingly.

Details

The order of the columns of \(W\) can be changed without changing the implied reduced form model as long as the order of lambda parameters is also changed accordingly. Note that the constraints imposed on \(W\) (or the B-matrix) will also be modified accordingly.

This function does not support models with constraints imposed on the lambda parameters!

Also all signs in any column of \(W\) can be swapped (without changing the implied reduced form model) with the function swap_W_signs but this obviously also swaps the sign constraints in the corresponding columns of \(W\).

References

• Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485-498.

• Virolainen S. (forthcoming). A statistically identified structural vector autoregression with endogenously switching volatility regime. Journal of Business & Economic Statistics.

• Virolainen S. 2022. Gaussian and Student's t mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks in the Euro area. Unpublished working paper, available as arXiv:2109.13648.

@keywords internal

See Also

fitGSMVAR, GSMVAR, GIRF, gsmvar_to_sgsmvar, stmvar_to_gstmvar, swap_W_signs

Examples

# Structural GMVAR(2, 2), d=2 model identified with sign-constraints:
params22s <- c(0.36, 0.121, 0.484, 0.072, 0.223, 0.059, -0.151, 0.395,
  0.406, -0.005, 0.083, 0.299, 0.218, 0.02, -0.119, 0.722, 0.093, 0.032,
  0.044, 0.191, 0.057, 0.172, -0.46, 0.016, 3.518, 5.154, 0.58)
W_22 <- matrix(c(1, 1, -1, 1), nrow=2, byrow=FALSE)
mod22s <- GSMVAR(p=2, M=2, d=2, params=params22s, structural_pars=list(W=W_22))
mod22s

# The same reduced form model, reordered W and lambda in the structual model:
mod22s_2 <- reorder_W_columns(mod22s, perm=2:1)
mod22s_2

# Structural StMVAR(2, 2), d=2 model identified with sign-constraints:
mod22ts <- GSMVAR(p=2, M=2, d=2, params=c(params22s, 10, 20), model="StMVAR",
                 structural_pars=list(W=W_22))
mod22ts

# The same reduced form model, reordered W and lambda in the structual model:
mod22ts_2 <- reorder_W_columns(mod22ts, perm=2:1)
mod22ts_2