compute_impulse_responses {bsvars}

Computes posterior draws of impulse responses

Description

Each of the draws from the posterior estimation of a model is transformed into a draw from the posterior distribution of the impulse responses.

Usage

compute_impulse_responses(posterior, horizon, standardise = FALSE)

Arguments

posterior

posterior estimation outcome - an object of either of the classes: PosteriorBSVAR, PosteriorBSVARMSH, PosteriorBSVARMIX, or PosteriorBSVARSV 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.

horizon

a positive integer number denoting the forecast horizon for the impulse responses computations.

standardise

a logical value. If TRUE, the impulse responses are standardised so that the variables' own shocks at horizon 0 are equal to 1. Otherwise, the parameter estimates determine this magnitude.

Value

An object of class PosteriorIR, that is, an NxNx(horizon+1)xS array with attribute PosteriorIR containing S draws of the impulse responses.

Author(s)

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, normalise_posterior

Examples

# upload data
data(us_fiscal_lsuw)

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

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

# estimate the model
posterior      = estimate(burn_in, 50)

# compute impulse responses 2 years ahead
irf           = compute_impulse_responses(posterior, horizon = 8)

# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
  specify_bsvar$new(p = 1) |>
  estimate(S = 10) |> 
  estimate(S = 50) |> 
  compute_impulse_responses(horizon = 8) -> ir