GVECMest {GVARX}

Estimate country-specific Engle-Granger VECM in a Global VECM setting

Description

Estimate country-specific Engle-Granger VECM in a Global VECM setting

Usage

GVECMest(data,p=2,lag.max=NULL, type="const", ic,weight.matrix=NULL)

Arguments

data

Dataframe is 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.

p

The number of lag for Xt matrix. Foreign variables are set by FLag=p+1. Current version restricts p <= 2 for simplicity, which aims at 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 VECM

type

Model specificaiton for VECM. As in package VECMs, we have four selection: "none","const","trend", "both".

ic

Information criteria for optimal lag.As in package VECMs, we have four selection: "AIC", "HQ", "SC", and "FPE".

weight.matrix

Bilateral trade weight matrix for computing foreign VECMiables. If the computation of foreign VECMiables are weighted by one weighting matrix, weight.matrix must be a "data.frame". If the computation of foreign VECMiables are weighted on a year-to-year basis, then weight.matrix must be a "list, with the same length as the weighting frequency.

Value

gvecm

Country-specific GVECM output list

White

Coefficient estimates with White robust coVECMiance

NWHAC

Coefficient estimates withNewy-West robust coVECMiance

p

Number of lags for endogeneous VECMiables in VECM

K

Number of lags for Ft VECMiables in VECM

type

Model specificaiton. As in package VECMs, we have four selection: "none","const","trend", and "both".

datamat

input data=data

lagmatrix

GVECM's Country-secific optimal lag number.

lagmatrix1

VECM's Country-secific optimal lag number.

exoLag

Ft lags

Ft

Foreign VECMiables

NAMES

Names of countries

gvecmRSD

Country-specific Global VECM residuals

vecmRSD

VECM residuals

Author(s)

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

References

Mauro Filippo di and Pesaran H. M. (2013) The GVECM 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
FLag=2
lag.max=15
type="const"
ic="SC"
weight.matrix=tradeweightx
mainOUTPUT = GVECMest(data=PriceVol,p,lag.max,type,ic,weight.matrix)

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