Verifies identification through heteroskedasticity or non-normality of of structural shocks

Displays information that the model is homoskedastic and with normal shocks.

Usage

# S3 method for class 'PosteriorBSVAR'
verify_identification(posterior)

Arguments

posterior: the estimation outcome obtained using estimate function

Value

Nothing. Just displays a message.

References

Lütkepohl, H., and Woźniak, T., (2020) Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity. Journal of Economic Dynamics and Control 113, 103862, doi:10.1016/j.jedc.2020.103862 .

Lütkepohl, H., Shang, F., Uzeda, L., and Woźniak, T. (2024) Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference. University of Melbourne Working Paper, 1–57, doi:10.48550/arXiv.2404.11057 .

Author

Tomasz Woźniak wozniak.tom@pm.me

Examples

# simple workflow
############################################################
# specify the model
specification  = specify_bsvar$new(us_fiscal_lsuw, p = 1)
#> The identification is set to the default option of lower-triangular structural matrix.

# estimate the model
posterior      = estimate(specification, 10)
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#>  Gibbs sampler for the SVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|

# verify heteroskedasticity
sddr           = verify_identification(posterior)
#> The model is homoskedastic with normal shocks.

# workflow with the pipe |>
############################################################
us_fiscal_lsuw |>
  specify_bsvar$new(p = 1) |>
  estimate(S = 10) |> 
  verify_identification() -> sddr
#> The identification is set to the default option of lower-triangular structural matrix.
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#>  Gibbs sampler for the SVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|
#> The model is homoskedastic with normal shocks.