MultiATSM (version 1.2.0)

GVAR: Estimates a GVAR(1) and a VARX(1,1,1) models

Description

Estimates a GVAR(1) and a VARX(1,1,1) models

Usage

GVAR(GVARinputs, N, CheckInputs = F)

Value

A list containing

1. parameters of the country-specific VARX(1,1,1)

   • intercept (M+Nx1);

   • phi_1 (M+N x M+N);

   • phi_1^star (M+N x M+N);

   • phi_g (M+N x M+N);

   • Sigma (M+N x G)

2. parameters of the GVAR.

   • F0 (F X 1);

   • F1 (F x F);

   • Sigma_y (F x F)

Arguments

GVARinputs

GVARinputs List. Inputs for GVAR model estimation:

1. Economies: A character vector containing the names of the economies included in the system.

2. GVARFactors: A list of all variables used in the estimation of the VARX model
   (see e.g. CM_Factors_GVAR file for details);

3. VARXtype: A character vector with three possible options:

   • 'unconstrained': model is estimated without constraints (each equation is estimated individually by ordinary least square);

   • 'constrained: Spanned Factors': The model is estimated with the restriction that foreign pricing factors do NOT affect (i) domestic economic variables and (ii) domestic pricing factors.
     (Equations are estimated using restricted least squares)

   • 'constrained : [factor_name]': The model is estimated with the restriction that the specified risk factor is influenced only by its own lagged values and the lagged values of its corresponding star variables. (Equations are estimated using restricted least squares.)

4. Wgvar: The GVAR transition matrix (C x C) used in the model solution.
   (See the output from the Transition_Matrix function.).

N

Integer. Number of country-specific spanned factors.

CheckInputs

A logical flag to indicate whether to perform a prior consistency check on the inputs provided in GVARinputs. The default is set to FALSE

References

Chudik and Pesaran, (2016). "Theory and Practice of GVAR modelling" (Journal of Economic Surveys)

Examples

data(CM_Factors_GVAR)

GVARinputs <- list( Economies = c("China", "Brazil", "Mexico", "Uruguay"),
                    GVARFactors = FactorsGVAR, VARXtype = "unconstrained")

GVARinputs$Wgvar <- matrix( c(0, 0.83, 0.86, 0.38,
                              0.65, 0, 0.13, 0.55,
                              0.32, 0.12, 0, 0.07,
                              0.03, 0.05, 0.01, 0), nrow = 4, ncol = 4)
N <- 3

GVARPara <- GVAR(GVARinputs, N)