SpecificMLEInputs function

Concatenate the model-specific inputs in a list

Concatenate the model-specific inputs in a list

SpecificMLEInputs( ModelType, Economies, RiskFactors, FactorLabels, GVARlist = NULL, JLLlist = NULL, WishBRW = 0, BRWlist = NULL, DataPathTrade = NULL )

Arguments

  • ModelType: string-vector containing the label of the model to be estimated

  • Economies: string-vector containing the names of the economies of the system

  • RiskFactors: time series of risk factors (F x T)

  • FactorLabels: string-list based which contains the labels of all the variables present in the model

  • GVARlist: A list of required inputs to estimate the GVAR-based setups:

    1. VARXtype string-vector containing the VARX feature (see "GVAR" function) (GVAR-based models)
    2. t_First_Wgvar Sample starting date (year) (GVAR-based models)
    3. t_Last_Wgvar Sample last date (year) (GVAR-based models)
    4. W_type Criterion used in the computation of the star variables (see "Transition_Matrix" function) (GVAR-based models)
  • JLLlist: A list of required inputs to estimate the JLL-based setups:

    1. DomUnit name of the economy which is assigned as the dominant unit (JLL-based models)
    2. WishSigmas equal to "1" if one wishes the variance-covariance matrices and the Cholesky factorizations (JLL-based models)
    3. SigmaNonOrtho NULL or some F x F matrix from the non-orthogonalized dynamics (JLL-based models)
  • WishBRW: Whether the user wishes to estimate the physical parameter model with the Bias correction model from BRW (2012) (see "Bias_Correc_VAR" function).

    Default is set to 0.

  • BRWlist: A list of required inputs to estimate the bias corrected setups of the type of BRW:

    1. BiasCorrection binary variable. it takes value equal to 1 if the user whishes the estimates to be bias-corrected and 0, otherwise. (BRW model)
    2. flag_mean flag whether mean- (TRUE) or median- (FALSE) unbiased estimation is desired
    3. gamma adjustment parameter (BRW model)
    4. N_iter number of iterations (BRW model)
    5. N_burn number of burn-in iterations (BRW model)
    6. B number of bootstrap samples (BRW model)
    7. checkBRW flag whether the user wishes to perform the closeness check (BRW model)
    8. B_check number of bootstrap samples for closeness check
  • DataPathTrade: path of the Excel file containing the data (if any)

  • Maintainer: Rubens Moura
  • License: GPL-2 | GPL-3
  • Last published: 2025-03-24