compute_historical_decompositions.PosteriorBSVARSIGN {bsvarSIGNs}

Computes posterior draws of historical decompositions

Description

Each of the draws from the posterior estimation of models from packages bsvars or bsvarSIGNs is transformed into a draw from the posterior distribution of the historical decompositions. IMPORTANT! The historical decompositions are interpreted correctly for covariance stationary data. Application to unit-root non-stationary data might result in non-interpretable outcomes.

Usage

## S3 method for class 'PosteriorBSVARSIGN'
compute_historical_decompositions(posterior, show_progress = TRUE)

Arguments

posterior

posterior estimation outcome - an object of class PosteriorBSVARSIGN obtained by running the estimate function.

show_progress

a logical value, if TRUE the estimation progress bar is visible

Value

An object of class PosteriorHD, that is, an NxNxTxS array with attribute PosteriorHD containing S draws of the historical decompositions.

Author(s)

Xiaolei Wang [e-mail] and Tomasz Woźniak [e-mail]

References

Kilian, L., & Lütkepohl, H. (2017). Structural VAR Tools, Chapter 4, In: Structural vector autoregressive analysis. Cambridge University Press.

See Also

estimate.BSVARSIGN, summary, plot

Examples

# upload data
data(optimism)

# specify the model and set seed
set.seed(123)

# + no effect on productivity (zero restriction)
# + positive effect on stock prices (positive sign restriction) 
sign_irf       = matrix(c(0, 1, rep(NA, 23)), 5, 5)
specification  = specify_bsvarSIGN$new(optimism, sign_irf = sign_irf)

# estimate the model
posterior      = estimate(specification, 10)

# compute historical decompositions
hd            = compute_historical_decompositions(posterior)

# workflow with the pipe |>
############################################################
set.seed(123)
optimism |>
  specify_bsvarSIGN$new(sign_irf = sign_irf) |> 
  estimate(S = 10) |> 
  compute_historical_decompositions() -> hd