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MultiATSM (version 1.3.0)

SpecificMLEInputs: Concatenate the model-specific inputs in a list

Description

Concatenate the model-specific inputs in a list

Usage

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)