GVECM.jo: Estimate country-specific Johansen test results in a Global...

In GVARX: Perform Global Vector Autoregression Estimation and Inference

Estimate country-specific Johansen test results in a Global VECM setting

Description

Estimate country-specific Johansen test results in a Global VECM setting

Usage

GVECM.jo(data,p=2,ecdet = "const", type = "eigen",spec = "longrun",
season = NULL,weight.matrix)

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. 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.
ecdet	Character, 'none' for no intercept in cointegration, 'const' for constant term in cointegration and 'trend' for trend variable in cointegration.
type	Model specificaiton for VECM. As in package VECMs, we have four selection: "none","const","trend", "both".
spec	Determines the specification of the VECM, see details in pakcage urca.
season	If seasonal dummies should be included, the data frequency must be set accordingly,i.e '4' for quarterly data.
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

JO.test	List object of country-specific Johansen test results
VECMoutputs	List object of country-specific VECM results
RESID	List object of country-specific VECM residuals, obtained by using vars::vec2var

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
type="const"
ic="SC"
weight.matrix=tradeweight1
mainOUT.JO=GVECM.jo(data=PriceVol,p=2,weight.matrix=weight.matrix)
mainOUT.JO$JO.test

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