avg.pair.cc  R Documentation 
Computes average pairwise crosssectional correlations of the data and the country models' residuals.
avg.pair.cc(object, digits=3)
object 
Either an object of class 
digits 
Number of digits that should be used to print output to the console. 
If used for analyzing the country models' residuals, avg.pair.cc
computes for each country and a given variable, the average crosssectional correlation (either for the data or for the residuals). In theory, including foreign variables should soak up crosssectional 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.
Returns a list with the following elements

is a matrix containing in the rows the crosssections and in the columns the crosssectional pairwise correlations of the data per variable. 

is a matrix containing in the rows the crosssections and in the columns the crosssectional pairwise correlations of the country models' residuals per variable. 

is a matrix containing in the rows the crosssections and in the columns the crosssectional pairwise correlations of the global models' residuals per variable. Only available when 

is a summary object showing the number and percentage of correlations <0.1, between 0.10.2, 0.20.5 and <0.5 per variable of the data. 

is a summary object showing the number and percentage of correlations <0.1, between 0.10.2, 0.20.5 and <0.5 per variable of the country models' residuals. This is also what is used by 

is a summary object showing the number and percentage of correlations <0.1, between 0.10.2, 0.20.5 and <0.5 per variable of the global models' residuals. Only available when 
Martin Feldkircher
Dees, S., Di Mauro F., Pesaran, M. H. and Smith, L. V. (2007) Exploring the international linkages of the euro area: A global VAR analysis. Journal of Applied Econometrics, Vol. 22, pp. 138.
bgvar
for estimation of a bgvar
object.
residuals
for calculating the residuals from a bgvar
object and creating a bgvar.res
object.
library(BGVAR) data(testdata) model.mn < bgvar(Data=testdata,W=W.test,plag=1,SV=TRUE, draws=100,burnin=100,prior="MN") avg.pair.cc(model.mn) res < residuals(model.mn) avg.pair.cc(res)
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