Bayesian Estimation of Structural Vector Autoregressive Models

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Documentation for package ‘bsvars’ version 2.0.0

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bsvars-package Bayesian Estimation of Structural Vector Autoregressive Models
bsvars Bayesian Estimation of Structural Vector Autoregressive Models
compute_conditional_sd Computes posterior draws of structural shock conditional standard deviations
compute_fitted_values Computes posterior draws of dependent variables' fitted values
compute_historical_decompositions Computes posterior draws of historical decompositions
compute_impulse_responses Computes posterior draws of impulse responses
compute_regime_probabilities Computes posterior draws of regime probabilities
compute_structural_shocks Computes posterior draws of structural shocks
compute_variance_decompositions Computes posterior draws of the forecast error variance decomposition
estimate Bayesian estimation of Structural Vector Autoregressions via Gibbs sampler
estimate.BSVAR Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler
estimate.BSVARMIX Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler
estimate.BSVARMSH Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler
estimate.BSVARSV Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler
estimate.PosteriorBSVAR Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler
estimate.PosteriorBSVARMIX Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler
estimate.PosteriorBSVARMSH Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler
estimate.PosteriorBSVARSV Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler
forecast Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVAR Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARMIX Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARMSH Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARSV Forecasting using Structural Vector Autoregression
normalise_posterior Waggoner & Zha (2003) row signs normalisation of the posterior draws for matrix B
specify_bsvar R6 Class representing the specification of the homoskedastic BSVAR model
specify_bsvar_mix R6 Class representing the specification of the BSVAR model with a zero-mean mixture of normals model for structural shocks.
specify_bsvar_msh R6 Class representing the specification of the BSVAR model with Markov Switching Heteroskedasticity.
specify_bsvar_sv R6 Class representing the specification of the BSVAR model with Stochastic Volatility heteroskedasticity.
specify_data_matrices R6 Class Representing DataMatricesBSVAR
specify_identification_bsvars R6 Class Representing IdentificationBSVARs
specify_posterior_bsvar R6 Class Representing PosteriorBSVAR
specify_posterior_bsvar_mix R6 Class Representing PosteriorBSVARMIX
specify_posterior_bsvar_msh R6 Class Representing PosteriorBSVARMSH
specify_posterior_bsvar_sv R6 Class Representing PosteriorBSVARSV
specify_prior_bsvar R6 Class Representing PriorBSVAR
specify_prior_bsvar_mix R6 Class Representing PriorBSVARMIX
specify_prior_bsvar_msh R6 Class Representing PriorBSVARMSH
specify_prior_bsvar_sv R6 Class Representing PriorBSVARSV
specify_starting_values_bsvar R6 Class Representing StartingValuesBSVAR
specify_starting_values_bsvar_mix R6 Class Representing StartingValuesBSVARMIX
specify_starting_values_bsvar_msh R6 Class Representing StartingValuesBSVARMSH
specify_starting_values_bsvar_sv R6 Class Representing StartingValuesBSVARSV
us_fiscal_lsuw A 3-variable US fiscal system for the period 1950 Q1 - 2021 Q4