bootstrap_irf function

Empirical estimation of PVAR Impulse Response Confidence Bands

Uses blockwise sampling of individuals (bootstrapping).

bootstrap_irf(
  model,
  typeof_irf,
  n.ahead,
  nof_Nstar_draws,
  confidence.band,
  mc.cores
)

## S3 method for class 'pvargmm'
bootstrap_irf(
  model,
  typeof_irf = c("OIRF", "GIRF"),
  n.ahead,
  nof_Nstar_draws,
  confidence.band = 0.95,
  mc.cores = getOption("mc.cores", 2L)
)

## S3 method for class 'pvarfeols'
bootstrap_irf(
  model,
  typeof_irf = c("OIRF", "GIRF"),
  n.ahead,
  nof_Nstar_draws,
  confidence.band = 0.95,
  mc.cores = getOption("mc.cores", 2L)
)

Arguments

• model: A PVAR model
• typeof_irf: "OIRF" or GIRF
• n.ahead: n ahead steps
• nof_Nstar_draws: Number of draws
• confidence.band: Confidence band
• mc.cores: Number of cores to use

Examples

## Not run:

data("ex1_dahlberg_data")
ex1_dahlberg_data_bs <-  bootstrap_irf(ex1_dahlberg_data, typeof_irf = c("GIRF"),
                                       n.ahead = 8,
                                       nof_Nstar_draws = 500,
                                       confidence.band = 0.95,
                                       mc.cores = 100)
## End(Not run)

data("ex1_dahlberg_data")
ex1_dahlberg_data_girf <-  girf(ex1_dahlberg_data, n.ahead = 8, ma_approx_steps= 8)
data("ex1_dahlberg_data_bs")
plot(ex1_dahlberg_data_girf, ex1_dahlberg_data_bs)