Generates the bootstrap-related outputs

Generates the bootstrap-related outputs

Usage

Bootstrap(
  ModelType,
  ModelParaPE,
  NumOutPE,
  Economies,
  InputsForOutputs,
  FactorLabels,
  JLLlist,
  GVARlist,
  WishBC = FALSE,
  BRWlist = NULL,
  Folder2save = NULL,
  verbose = TRUE
)

Arguments

ModelType

character. Model type to be estimated. Permissible choices: "JPS original", "JPS global", "GVAR single", "JPS multi", "GVAR multi", "JLL original", "JLL No DomUnit", "JLL joint Sigma".

ModelParaPE

list. Point estimates of the model parameters. See outputs from Optimization.

NumOutPE

list. Point estimates from numerical outputs. See outputs from NumOutputs.

Economies

character vector. Names of the C economies included in the system.

InputsForOutputs

list. Inputs for generating IRFs, GIRFs, FEVDs, GFEVDs, and Term Premia.

FactorLabels

list. Labels for all variables present in the model, as returned by LabFac.

JLLlist

list. Inputs for JLL model estimation (see JLL). Default is NULL.

GVARlist

list. Inputs for GVAR model estimation (see GVAR). Default is NULL.

WishBC

logical. Whether to estimate the physical parameter model with bias correction (see Bias_Correc_VAR). Default is FALSE.

BRWlist

list. Inputs for bias-corrected estimation (see Bias_Correc_VAR).

Folder2save

character. Folder path where outputs will be stored. Default saves outputs in a temporary directory.

verbose

logical. Print progress messages. Default is TRUE.

Value

An object of class 'ATSMModelBoot' containing:

• List of model parameters for each draw

• List of numerical outputs (IRFs, GIRFs, FEVDs, GFEVDs) for each draw

• Confidence bounds for the chosen level of significance

Permissible options - Bootstrap list in InputsForOutputs

• methodBS : "bs" (standard bootstrap), "wild" (wild bootstrap), "block" (block bootstrap)

• BlockLength : required input for the block bootstrap method. Block length must be larger than 0 and smallar than the model time series dimension (Td).

• ndraws: number of draws. Must be a positive integer.

• pctg : confidence level. Must be a positive integer. Common choices are: 68, 90 and 95.

Available methods

- autoplot(object, NumOutPE, type)

Examples

# \donttest{
data("ParaSetEx")
data("InpForOutEx")
data("NumOutEx")
ModelType <- "JPS original"
Economy <- "Brazil"
FacLab <- LabFac(N = 1, DomVar = "Eco_Act", GlobalVar = "Gl_Eco_Act", Economy, ModelType)

# Adjust Forecasting setting
InpForOutEx[[ModelType]]$Bootstrap <- list(
  WishBootstrap = 1, methodBS = "bs", BlockLength = 4,
  ndraws = 5, pctg = 95
)

Boot <- Bootstrap(ModelType, ParaSetEx, NumOutEx, Economy, InpForOutEx, FacLab,
  JLLlist = NULL,
  GVARlist = NULL, WishBC = FALSE, BRWlist = NULL, Folder2save = NULL, verbose = FALSE
)
#> Warning: cannot create dir '/tmp/RtmpQXitSu/Outputs/JPS original/Bootstrap', reason 'No such file or directory'
#> Warning: cannot create dir '/tmp/RtmpQXitSu/Outputs/JPS original/Bootstrap/Model Brazil', reason 'No such file or directory'
# }