How to extract p-value in var package? - r

Question

How can we extract p-value in var package. When we write summary(var), where 'var' is the name of var model, we see p-value at the bottom the results, but how we can extract this value?
For example:
library(vars)
symbols=c('^N225','^FTSE','^GSPC')
getSymbols(symbols,src='yahoo', from="2003-04-28", to="2007-10-29")
period="daily"
A1=periodReturn(N225$N225.Adjusted,period=period)
B1=periodReturn(FTSE$FTSE.Adjusted,period=period)
C1=periodReturn(GSPC$GSPC.Adjusted,period=period)
datap_1<-cbind(A1,B1,C1)
datap_1<-na.omit(datap_1)
datap_1<-(datap_1)^2
vardatap_3<-VAR(datap_1,p=3,type="none")
summary(vardatap_3)
after summary(vardatap_3) we can see the p-value, like this:
VAR Estimation Results:
=========================
Endogenous variables: N225, FTSE, SP500
Deterministic variables: none
Sample size: 1055
Log Likelihood: 23637.848
Roots of the characteristic polynomial:
0.8639 0.6224 0.6224 0.5711 0.5711 0.5471 0.5471 0.4683 0.4683
Call:
VAR(y = datap_1, p = 3, type = "none")
Estimation results for equation N225:
=====================================
N225 = N225.l1 + FTSE.l1 + SP500.l1 + N225.l2 + FTSE.l2 + SP500.l2 + N225.l3 + FTSE.l3 + SP500.l3
Estimate Std. Error t value Pr(>|t|)
N225.l1 0.03436 0.03116 1.103 0.270
FTSE.l1 0.47025 0.06633 7.089 2.48e-12 ***
SP500.l1 0.60717 0.07512 8.083 1.74e-15 ***
N225.l2 0.14938 0.03057 4.886 1.19e-06 ***
FTSE.l2 -0.05440 0.06744 -0.807 0.420
SP500.l2 -0.09024 0.07782 -1.160 0.246
N225.l3 0.16809 0.02924 5.749 1.18e-08 ***
FTSE.l3 0.04480 0.06597 0.679 0.497
SP500.l3 -0.01007 0.07941 -0.127 0.899
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.0002397 on 1046 degrees of freedom
Multiple R-Squared: 0.3099, Adjusted R-squared: 0.304
F-statistic: 52.2 on 9 and 1046 DF, p-value: < 2.2e-16
at the end of thi output, we see that p-value is less than 2.2e-16.
when I run this code:
lapply(coef(vardatap_3), "[", , "Pr(>|t|)"))
the output is:
$N225
N225.l1 FTSE.l1 SP500.l1 N225.l2 FTSE.l2 SP500.l2
2.703965e-01 2.479333e-12 1.738649e-15 1.189843e-06 4.201011e-01 2.464906e-01
N225.l3 FTSE.l3 SP500.l3
1.177588e-08 4.971743e-01 8.990626e-01
$FTSE
N225.l1 FTSE.l1 SP500.l1 N225.l2 FTSE.l2 SP500.l2
8.849041e-01 2.730359e-09 3.415860e-10 8.673114e-01 5.232037e-02 2.887330e-10
N225.l3 FTSE.l3 SP500.l3
8.698535e-02 6.215429e-15 9.290871e-02
$SP500
N225.l1 FTSE.l1 SP500.l1 N225.l2 FTSE.l2 SP500.l2
2.431252e-01 3.928462e-02 4.362288e-02 1.007840e-01 1.141799e-01 8.819460e-03
N225.l3 FTSE.l3 SP500.l3
1.129084e-03 1.426315e-01 1.307562e-06
and it's not the p-value. How can I reach to this value?

Answer 1

If fit is the object returned by the VAR function, you can use
lapply(coef(fit), "[", , "Pr(>|t|)")
to generate a list of vectors of the p-values.
If you want to extract/calculate the p-values for the whole models, you can try
sapply(summary(fit)$varresult, function(x) {
tmp <- x[["fstatistic"]]
pf(tmp[1], tmp[2], tmp[3], lower.tail = FALSE)
})