Average Pairwise Cross-sectional Correlations
Computes average pairwise cross-sectional 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 cross-sectional correlation (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.
Returns a list with the following elements
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is a matrix containing in the rows the cross-sections and in the columns the cross-sectional pairwise correlations of the data per variable. |
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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. |
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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 available when |
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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. |
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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 |
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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 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. 1-38.
library(BGVAR)
data(eerDatasmall)
model.mn <- bgvar(Data=eerDatasmall,W=W.trade0012.small,plag=1,SV=TRUE,
draws=100,burnin=100,prior="MN")
avg.pair.cc(model.mn)
res <- residuals(model.mn)
avg.pair.cc(res)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.