Provides summary of the Savage-Dickey density ratios for verification of structural shocks homoskedasticity. The outcomes can be used to make probabilistic statements about identification through heteroskedasticity closely following ideas by Lütkepohl& Woźniak (2020).
## S3 method for class 'SDDRidMSH'summary(object,...)
Arguments
object: an object of class SDDRidMSH obtained using the verify_identification.PosteriorBSVARMSH function.
...: additional arguments affecting the summary produced.
Returns
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.
Examples
# upload datadata(us_fiscal_lsuw)# specify the model and set seedspecification = specify_bsvar_msh$new(us_fiscal_lsuw, M =2)set.seed(123)# estimate the modelposterior = estimate(specification,10)# verify heteroskedasticitysddr = verify_identification(posterior)summary(sddr)# workflow with the pipe |>############################################################set.seed(123)us_fiscal_lsuw |> specify_bsvar_msh$new(M =2)|> estimate(S =10)|> verify_identification()|> summary()-> sddr_summary
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, tools:::Rd_expr_doi("10.1016/j.jedc.2020.103862") .