compute_historical_decompositions function

Computes posterior draws of historical decompositions

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.

compute_historical_decompositions(posterior, show_progress = TRUE)

Arguments

• posterior: posterior estimation outcome obtained by running the estimate

  function. The interpretation depends on the normalisation of the shocks using function normalise_posterior(). Verify if the default settings are appropriate.

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

Returns

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

Examples

# upload data
data(us_fiscal_lsuw)

# specify the model and set seed
set.seed(123)
specification  = specify_bsvar$new(diff(us_fiscal_lsuw), p = 1)

# run the burn-in
burn_in        = estimate(specification, 10)

# estimate the model
posterior      = estimate(burn_in, 20)

# compute historical decompositions
hd            = compute_historical_decompositions(posterior)

# workflow with the pipe |>
############################################################
set.seed(123)
diff(us_fiscal_lsuw) |>
  specify_bsvar$new(p = 1) |>
  estimate(S = 10) |> 
  estimate(S = 20) |> 
  compute_historical_decompositions() -> hd

References

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

See Also

estimate, normalise_posterior, summary

Author(s)

Tomasz Woźniak wozniak.tom@pm.me