GVARest: Estimate country-specific VAR in a GVAR setting

In GVARX: Perform Global Vector Autoregression Estimation and Inference

Estimate country-specific VAR in a GVAR setting

Description

Estimate country-specific VAR in a GVAR setting

Usage

GVARest(data,p,lag.max, type="const", ic,weight.matrix=NULL)

Arguments

data	Dataframe for bivariate VAR is allowed so far, which is also a strictly balanced panel data format,the first column is cross-section ID,and the second column is Time. For the sake of identification, both columns must be named by, respectively, id and Time. Restriction of bivariate VAR will be relaxed soon.
p	The number of lag for Xt matrix, foreign variables are set by FLag=p+1. Current version restricts p <= 2 with a view to avoiding too many paramaters in low-frequency data of many variables and many countries. It will be relaxed soon.
lag.max	The maximal number of lag for estimating country-specific VAR
type	Model specificaiton for VAR. As in package vars, we have four selection: "none","const","trend", "both".
ic	Information criteria for optimal lag.As in package vars, we have four selection: "AIC", "HQ", "SC", and "FPE".
weight.matrix	Bilateral trade weight matrix for computing foreign variables. If the computation of foreign variables are weighted by one weighting matrix, weight.matrix must be a "data.frame". If the computation of foreign variables are weighted on a year-to-year basis, then weight.matrix must be a "list, with the same length as the weighting frequency.

Value

gvar	Country-specific GVAR output list
White	Coefficient estimates with White robust covariance
NWHAC	Coefficient estimates withNewy-West robust covariance
p	Number of lags for endogeneous variables in VAR
K	Number of lags for Ft variables in VAR
type	Model specificaiton. As in package vars, we have four selection: "none","const","trend", and "both".
datamat	input data=data
lagmatrix	GVAR's Country-secific optimal lag number.
lagmatrix1	VAR's Country-secific optimal lag number.
exoLag	Ft lags
Ft	Foreign variables
NAMES	Names of countries
gvarRSD	Country-specific GVAR residuals
varRSD	VAR residuals
weight	weight.matrix

Author(s)

Ho Tsung-wu <[e-mail]>, College of Management, National Taiwan Normal University.

References

Mauro Filippo di and Pesaran H. M. (2013) The GVAR Handbook– Structure and Applications of a Macro Model of the Global Economy for Policy. Oxford University Press.

Examples

data("PriceVol")
data("tradeweight1")
data("tradeweightx")

p=2
lag.max=15
type="const"
ic="SC"
weight.matrix=tradeweightx
mainOUTPUT = GVARest(data=PriceVol,p,lag.max,type,ic,weight.matrix)

mainOUTPUT$lagmatrix    # Country-specific GVAR lags
mainOUTPUT$gvar
mainOUTPUT$gvar[[1]]
coef(mainOUTPUT$gvar[[17]])
mainOUTPUT$White[[17]]
mainOUTPUT$NWHAC[[17]][1]

GVARX documentation built on Feb. 16, 2023, 10:56 p.m.