Provides summary of the Savage-Dickey density ratios for verification of structural shocks homoskedasticity.
Usage
# S3 method for class 'SDDRvolatility'
summary(object, ...)
Arguments
- object
an object of class
SDDRvolatility
obtained using theverify_volatility()
function.- ...
additional arguments affecting the summary produced.
Value
A table reporting the logarithm of Bayes factors of homoskedastic to
heteroskedastic posterior odds "log(SDDR)"
for each structural shock,
their numerical standard errors "NSE"
, and the implied posterior
probability of the homoskedasticity and heteroskedasticity hypothesis,
"Pr[homoskedasticity|data]"
and "Pr[heteroskedasticity|data]"
respectively.
Author
Tomasz Woźniak wozniak.tom@pm.me
Examples
# upload data
data(us_fiscal_lsuw)
# specify the model and set seed
specification = specify_bsvar_msh$new(us_fiscal_lsuw, p = 1, M = 2)
#> The identification is set to the default option of lower-triangular structural matrix.
set.seed(123)
# estimate the model
posterior = estimate(specification, 10)
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#> Gibbs sampler for the SVAR-stationaryMSH model |
#> **************************************************|
#> Progress of the MCMC simulation for 10 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
# verify heteroskedasticity
sddr = verify_volatility(posterior)
summary(sddr)
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#> Summary of structural shocks |
#> homoskedasticity verification |
#> **************************************************|
#> log(SDDR) NSE Pr[homoskedasticity|data] Pr[heteroskedasticity|data]
#> shock 1 2.3062403 0 0.9093925 0.09060746
#> shock 2 0.6630149 0 0.6599373 0.34006267
#> shock 3 -1.8201037 0 0.1394214 0.86057858
# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
specify_bsvar_msh$new(p = 1, M = 2) |>
estimate(S = 10) |>
verify_volatility() |>
summary() -> sddr_summary
#> The identification is set to the default option of lower-triangular structural matrix.
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#> Gibbs sampler for the SVAR-stationaryMSH model |
#> **************************************************|
#> Progress of the MCMC simulation for 10 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
#> **************************************************|
#> bsvars: Bayesian Structural Vector Autoregressions|
#> **************************************************|
#> Summary of structural shocks |
#> homoskedasticity verification |
#> **************************************************|