# Forecasting with Bayesian Panel Vector Autoregressions

## Documentation for package ‘bpvars’ version 2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

bpvars-package | Forecasting with Bayesian Panel Vector Autoregressions
bpvars | Forecasting with Bayesian Panel Vector Autoregressions
compute_forecast_performance | Computes forecasting performance measures for recursive pseudo-out-of-sample forecasts
compute_forecast_performance.ForecastsPANELpoos | Computes forecasting performance measures for recursive pseudo-out-of-sample forecasts
compute_variance_decompositions.PosteriorBVARGROUPPANEL | Computes posterior draws of the forecast error variance decomposition
compute_variance_decompositions.PosteriorBVARPANEL | Computes posterior draws of the forecast error variance decomposition
compute_variance_decompositions.PosteriorBVARs | Computes posterior draws of the forecast error variance decomposition
country_grouping_incomegroup | A vector with country grouping by income group for 189 countries
country_grouping_region | A vector with country grouping by region for 189 countries
country_grouping_subregionbroad | A vector with country grouping by subregion for 189 countries
country_grouping_subregiondetailed | A vector with country grouping by detailed subregion for 189 countries
estimate.BVARGROUPPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression with fixed or estimated country grouping
estimate.BVARGROUPPRIORPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression with fixed or estimated country grouping for global priors
estimate.BVARPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression using Gibbs sampler
estimate.BVARs | Bayesian estimation of a Bayesian Hierarchical Vector Autoregressions for cubic data using Gibbs sampler
estimate.PosteriorBVARGROUPPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression with fixed or estimated country grouping
estimate.PosteriorBVARGROUPPRIORPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression with fixed or estimated country grouping for global priors
estimate.PosteriorBVARPANEL | Bayesian estimation of a Bayesian Hierarchical Panel Vector Autoregression using Gibbs sampler
estimate.PosteriorBVARs | Bayesian estimation of a Bayesian Hierarchical Vector Autoregressions for cubic data using Gibbs sampler
forecast.PosteriorBVARGROUPPANEL | Forecasting using Hierarchical Panel Vector Autoregressions
forecast.PosteriorBVARGROUPPRIORPANEL | Forecasting using Hierarchical Panel Vector Autoregressions
forecast.PosteriorBVARPANEL | Forecasting using Hierarchical Panel Vector Autoregressions
forecast.PosteriorBVARs | Forecasting using Hierarchical Vector Autoregressions for Dynamic Panel Data
forecast_poos_recursively | Bayesian recursive pseudo-out-of-sample forecasting
forecast_poos_recursively.BVARGROUPPANEL | Bayesian recursive pseudo-out-of-sample forecasting
forecast_poos_recursively.BVARGROUPPRIORPANEL | Bayesian recursive pseudo-out-of-sample forecasting
forecast_poos_recursively.BVARPANEL | Bayesian recursive pseudo-out-of-sample forecasting
forecast_poos_recursively.BVARs | Bayesian recursive pseudo-out-of-sample forecasting
ilo_conditional_forecasts | Data containing future observations for 189 countries from 2025 to 2027 to be used for conditional forecasts given the future values of gdp.
ilo_dynamic_panel | A 4-variable annual system for forecasting labour market outcomes for 189 countries from 1991 to 2024
ilo_dynamic_panel_missing | A 4-variable annual system for forecasting labour market outcomes for 189 countries to 2024 containing only actual observations
ilo_exogenous_forecasts | Data containing future observations for 189 countries from 2025 to 2027 to be used to forecast with models with 'ilo_exogenous_variables'
ilo_exogenous_variables | A 3-variable annual system for of dummy observations for 2008, 2020, and 2021 to be used in the estimation of the Panel VAR model for 189 countries from 1991 to 2024
ilo_exogenous_variables_missing | A 3-variable annual system for of dummy observations for 2008, 2020, and 2021 to be used in the estimation of the Panel VAR model for 189 countries to 2024 containing observations for matching periods from 'ilo_dynamic_panel_missing'
plot.ForecastsPANEL | Plots fitted values of dependent variables
plot.PosteriorFEVDPANEL | Plots forecast error variance decompositions
specify_bvarGroupPANEL | R6 Class representing the specification of the BVARGROUPPANEL model
specify_bvarGroupPriorPANEL | R6 Class representing the specification of the BVARGROUPPRIORPANEL model
specify_bvarPANEL | R6 Class representing the specification of the BVARPANEL model
specify_bvars | R6 Class representing the specification of the BVARs model
specify_panel_data_matrices | R6 Class Representing DataMatricesBVARPANEL
specify_poosf_exercise | R6 Class Representing specification of the pseudo-out-of-sample forecasting exercise
specify_posterior_bvarGroupPANEL | R6 Class Representing PosteriorBVARGROUPPANEL
specify_posterior_bvarGroupPriorPANEL | R6 Class Representing PosteriorBVARGROUPPRIORPANEL
specify_posterior_bvarPANEL | R6 Class Representing PosteriorBVARPANEL
specify_posterior_bvars | R6 Class Representing PosteriorBVARs
specify_prior_bvarPANEL | R6 Class Representing PriorBVARPANEL
specify_prior_bvars | R6 Class Representing PriorBVARs
specify_starting_values_bvarGroupPANEL | R6 Class Representing StartingValuesBVARGROUPPANEL
specify_starting_values_bvarGroupPriorPANEL | R6 Class Representing StartingValuesBVARGROUPPRIORPANEL
specify_starting_values_bvarPANEL | R6 Class Representing StartingValuesBVARPANEL
specify_starting_values_bvars | R6 Class Representing StartingValuesBVARs
summary.ForecastsPANEL | Provides posterior summary of country-specific Forecasts
summary.PosteriorBVARGROUPPANEL | Provides posterior estimation summary for Bayesian Hierarchical Panel Vector Autoregressions
summary.PosteriorBVARGROUPPRIORPANEL | Provides posterior estimation summary for Bayesian Hierarchical Panel Vector Autoregressions with group-specific global prior
summary.PosteriorBVARPANEL | Provides posterior estimation summary for Bayesian Hierarchical Panel Vector Autoregressions
summary.PosteriorBVARs | Provides posterior estimation summary for Bayesian Vector Autoregressions for dynamic panel data
summary.PosteriorFEVDPANEL | Provides posterior summary of forecast error variance decompositions