avg.pair.cc {BGVAR}R Documentation

Average pairwise cross-sectional correlations

Description

Computes average pairwise cross-sectional correlations of the data and the country models' residuals. To be more specific, for each country and a given variable, the average cross-sectional correlation is computed (either for the data or for the residuals). In theory, including foreign variables should soak up cross-sectional residual dependence and correlation of the residuals should be small. Otherwise dynamic analysis, especially using GIRFs, might lead to invalid results. See Dees et al. (2007) for more details.

Usage

avg.pair.cc(X, dig = 3)

Arguments

X

Either an object fitted by bgvar (class bgvar) or residuals extracted via get.res (class res).

dig

Number of digits that should be used to print output to the console.

Value

data.cor

is a matrix containing in the rows the cross-sections and in the columns the cross-sectional pairwise correlations of the data per variable.

resid.cor

is a matrix containing in the rows the cross-sections and in the columns the cross-sectional pairwise correlations of the country models' residuals per variable.

resid.corG

is a matrix containing in the rows the cross-sections and in the columns the cross-sectional pairwise correlations of the global models' residuals per variable. Only availabe when avg.pair.cc has been applied to a res object from get.res.

dat.res

is a summary object showing the number and percentage of correlations <0.1, between 0.1-0.2, 0.2-0.5 and <0.5 per variable of the data.

res.res

is a summary object showing the number and percentage of correlations <0.1, between 0.1-0.2, 0.2-0.5 and <0.5 per variable of the country models' residuals. This is also what is used by print.bgvar.

res.resG

is a summary object showing the number and percentage of correlations <0.1, between 0.1-0.2, 0.2-0.5 and <0.5 per variable of the global models' residuals. Only availabe when avg.pair.cc has been applied to a res object from get.res.

Author(s)

Martin Feldkircher

References

Dees, S., Di Mauro, F., Pesaran, M.H. and L. V. Smith (2007) Exploring the international linkages of the euro area: A global VAR analysis. In: Journal of Applied Econometrics, Vol. 22, pp. 1-38.

See Also

See also print.bgvar, get.res.

Examples

library(BGVAR)
data(eerData)
model.sims<-bgvar(Data=eer.data,W=W.trade0012,saves=100,burns=100,plag=1,Cpu=4,prior="SIMS",save_thin=1,eigen=TRUE,logfile=FALSE,stats=TRUE)
avg.pair.cc(model.sims)

get.Res<-get.res(model.sims)
avg.pair.cc(get.Res)


[Package BGVAR version 1.1.3 Index]