reorder_W_columns {gmvarkit}

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)

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.

Value

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

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 Unpublished working paper, available as arXiv:2109.13648.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