y <- c(280.2
,299.9
,339.2
,374.2
,393.5
,389.2
,381.7
,375.2
,369
,357.4
,352.1
,346.5
,342.9
,340.3
,328.3
,322.9
,314.3
,308.9
,294
,285.6
,281.2
,280.3
,278.8
,274.5
,270.4
,263.4
,259.9
,258
,262.7
,284.7
,311.3
,322.1
,327
,331.3
,333.3
,321.4
,327
,320
,314.7
,316.7
,314.4
,321.3
,318.2
,307.2
,301.3
,287.5
,277.7
,274.4
,258.8
,253.3
,251
,248.4
,249.5
,246.1
,244.5
,243.6
,244
,240.8
,249.8
,248
,259.4
,260.5
,260.8
,261.3
,259.5
,256.6
,257.9
,256.5
,254.2
,253.3
,253.8
,255.5
,257.1
,257.3
,253.2
,252.8
,252
,250.7
,252.2
,250
,251
,253.4
,251.2
,255.6
,261.1
,258.9
,259.9
,261.2
,264.7
,267.1
,266.4
,267.7
,268.6
,267.5
,268.5
,268.5
,270.5
,270.9
,270.1
,269.3
,269.8
,270.1
,264.9
,263.7
,264.8
,263.7
,255.9
,276.2
,360.1
,380.5
,373.7
,369.8
,366.6
,359.3
,345.8
,326.2
,324.5
,328.1
,327.5
,324.4
,316.5
,310.9
,301.5
,291.7
,290.4
,287.4
,277.7
,281.6
,288
,276
,272.9
,283
,283.3
,276.8
,284.5
,282.7
,281.2
,287.4
,283.1
,284
,285.5
,289.2
,292.5
,296.4
,305.2
,303.9
,311.5
,316.3
,316.7
,322.5
,317.1
,309.8
,303.8
,290.3
,293.7
,291.7
,296.5
,289.1
,288.5
,293.8
,297.7
,305.4
,302.7
,302.5
,303
,294.5
,294.1
,294.5
,297.1
,289.4
,292.4
,287.9
,286.6
,280.5
,272.4
,269.2
,270.6
,267.3
,262.5
,266.8
,268.8
,263.1
,261.2
,266
,262.5
,265.2
,261.3
,253.7
,249.2
,239.1
,236.4
,235.2
,245.2
,246.2
,247.7
,251.4
,253.3
,254.8
,250
,249.3
,241.5
,243.3
,248
,253
,252.9
,251.5
,251.6
,253.5
,259.8
,334.1
,448
,445.8
,445
,448.2
,438.2
,439.8
,423.4
,410.8
,408.4
,406.7
,405.9
,402.7
,405.1
,399.6
,386.5
,381.4
,375.2
,357.7
,359
,355
,352.7
,344.4
,343.8
,338
,339
,333.3
,334.4
,328.3
,330.7
,330
,331.6
,351.2
,389.4
,410.9
,442.8
,462.8
,466.9
,461.7
,439.2
,430.3
,416.1
,402.5
,397.3
,403.3
,395.9
,387.8
,378.6
,377.1
,370.4
,362
,350.3
,348.2
,344.6
,343.5
,342.8
,347.6
,346.6
,349.5
,342.1
,342
,342.8
,339.3
,348.2
,333.7
,334.7
,354
,367.7
,363.3
,358.4
,353.1
,343.1
,344.6
,344.4
,333.9
,331.7
,324.3
,321.2
,322.4
,321.7
,320.5
,312.8
,309.7
,315.6
,309.7
,304.6
,302.5
,301.5
,298.8
,291.3
,293.6
,294.6
,285.9
,297.6
,301.1
,293.8
,297.7
,292.9
,292.1
,287.2
,288.2
,283.8
,299.9
,292.4
,293.3
,300.8
,293.7
,293.1
,294.4
,292.1
,291.9
,282.5
,277.9
,287.5
,289.2
,285.6
,293.2
,290.8
,283.1
,275
,287.8
,287.8
,287.4
,284
,277.8
,277.6
,304.9
,294
,300.9
,324
,332.9
,341.6
,333.4
,348.2
,344.7
,344.7
,329.3
,323.5
,323.2
,317.4
,330.1
,329.2
,334.9
,315.8
,315.4
,319.6
,317.3
,313.8
,315.8
,311.3)
x <- c(87.28
,87.28
,87.09
,86.92
,87.59
,90.72
,90.69
,90.3
,89.55
,88.94
,88.41
,87.82
,87.07
,86.82
,86.4
,86.02
,85.66
,85.32
,85
,84.67
,83.94
,82.83
,81.95
,81.19
,80.48
,78.86
,69.47
,68.77
,70.06
,73.95
,75.8
,77.79
,81.57
,83.07
,84.34
,85.1
,85.25
,84.26
,83.63
,86.44
,85.3
,84.1
,83.36
,82.48
,81.58
,80.47
,79.34
,82.13
,81.69
,80.7
,79.88
,79.16
,78.38
,77.42
,76.47
,75.46
,74.48
,78.27
,80.7
,79.91
,78.75
,77.78
,81.14
,81.08
,80.03
,78.91
,78.01
,76.9
,75.97
,81.93
,80.27
,78.67
,77.42
,76.16
,74.7
,76.39
,76.04
,74.65
,73.29
,71.79
,74.39
,74.91
,74.54
,73.08
,72.75
,71.32
,70.38
,70.35
,70.01
,69.36
,67.77
,69.26
,69.8
,68.38
,67.62
,68.39
,66.95
,65.21
,66.64
,63.45
,60.66
,62.34
,60.32
,58.64
,60.46
,58.59
,61.87
,61.85
,67.44
,77.06
,91.74
,93.15
,94.15
,93.11
,91.51
,89.96
,88.16
,86.98
,88.03
,86.24
,84.65
,83.23
,81.7
,80.25
,78.8
,77.51
,76.2
,75.04
,74
,75.49
,77.14
,76.15
,76.27
,78.19
,76.49
,77.31
,76.65
,74.99
,73.51
,72.07
,70.59
,71.96
,76.29
,74.86
,74.93
,71.9
,71.01
,77.47
,75.78
,76.6
,76.07
,74.57
,73.02
,72.65
,73.16
,71.53
,69.78
,67.98
,69.96
,72.16
,70.47
,68.86
,67.37
,65.87
,72.16
,71.34
,69.93
,68.44
,67.16
,66.01
,67.25
,70.91
,69.75
,68.59
,67.48
,66.31
,64.81
,66.58
,65.97
,64.7
,64.7
,60.94
,59.08
,58.42
,57.77
,57.11
,53.31
,49.96
,49.4
,48.84
,48.3
,47.74
,47.24
,46.76
,46.29
,48.9
,49.23
,48.53
,48.03
,54.34
,53.79
,53.24
,52.96
,52.17
,51.7
,58.55
,78.2
,77.03
,76.19
,77.15
,75.87
,95.47
,109.67
,112.28
,112.01
,107.93
,105.96
,105.06
,102.98
,102.2
,105.23
,101.85
,99.89
,96.23
,94.76
,91.51
,91.63
,91.54
,85.23
,87.83
,87.38
,84.44
,85.19
,84.03
,86.73
,102.52
,104.45
,106.98
,107.02
,99.26
,94.45
,113.44
,157.33
,147.38
,171.89
,171.95
,132.71
,126.02
,121.18
,115.45
,110.48
,117.85
,117.63
,124.65
,109.59
,111.27
,99.78
,98.21
,99.2
,97.97
,89.55
,87.91
,93.34
,94.42
,93.2
,90.29
,91.46
,89.98
,88.35
,88.41
,82.44
,79.89
,75.69
,75.66
,84.5
,96.73
,87.48
,82.39
,83.48
,79.31
,78.16
,72.77
,72.45
,68.46
,67.62
,68.76
,70.07
,68.55
,65.3
,58.96
,59.17
,62.37
,66.28
,55.62
,55.23
,55.85
,56.75
,50.89
,53.88
,52.95
,55.08
,53.61
,58.78
,61.85
,55.91
,53.32
,46.41
,44.57
,50
,50
,53.36
,46.23
,50.45
,49.07
,45.85
,48.45
,49.96
,46.53
,50.51
,47.58
,48.05
,46.84
,47.67
,49.16
,55.54
,55.82
,58.22
,56.19
,57.77
,63.19
,54.76
,55.74
,62.54
,61.39
,69.6
,79.23
,80
,93.68
,107.63
,100.18
,97.3
,90.45
,80.64
,80.58
,75.82
,85.59
,89.35
,89.42
,104.73
,95.32
,89.27
,90.44
,86.97
,79.98
,81.22
,87.35
,83.64
,82.22
,94.4)
par8 = '11'
par7 = '0'
par6 = '1'
par5 = '1'
par4 = '12'
par3 = '0'
par2 = '1'
par1 = '1'
#'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
#Author: Prof. Dr. P. Wessa
#To cite this work: Wessa P., (2008), Bivariate Granger Causality (v1.0.0) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_grangercausality.wasp#output/
#Source of accompanying publication: Office for Research, Development, and Education
#Technical description: 
library(lmtest)
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
par8 <- as.numeric(par8)
ox <- x
oy <- y
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
(gyx <- grangertest(y ~ x, order=par8))
(gxy <- grangertest(x ~ y, order=par8))
postscript(file="/var/www/html/rcomp/tmp/1c52s1260377230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
op <- par(mfrow=c(2,1))
(r <- ccf(ox,oy,main='Cross Correlation Function (raw data)',ylab='CCF',xlab='Lag (k)'))
(r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)'))
par(op)
dev.off()
postscript(file="/var/www/html/rcomp/tmp/2b0vc1260377230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
op <- par(mfrow=c(2,1))
acf(ox,lag.max=round(length(x)/2),main='ACF of x (raw)')
acf(x,lag.max=round(length(x)/2),main='ACF of x (transformed and differenced)')
par(op)
dev.off()
postscript(file="/var/www/html/rcomp/tmp/3xjoc1260377230.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
op <- par(mfrow=c(2,1))
acf(oy,lag.max=round(length(y)/2),main='ACF of y (raw)')
acf(y,lag.max=round(length(y)/2),main='ACF of y (transformed and differenced)')
par(op)
dev.off()

#Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
load(file="/var/www/html/rcomp/createtable")

a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Granger Causality Test: Y = f(X)',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Model',header=TRUE)
a<-table.element(a,'Res.DF',header=TRUE)
a<-table.element(a,'Diff. DF',header=TRUE)
a<-table.element(a,'F',header=TRUE)
a<-table.element(a,'p-value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Complete model',header=TRUE)
a<-table.element(a,gyx$Res.Df[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Reduced model',header=TRUE)
a<-table.element(a,gyx$Res.Df[2])
a<-table.element(a,gyx$Df[2])
a<-table.element(a,gyx$F[2])
a<-table.element(a,gyx$Pr[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file="/var/www/html/rcomp/tmp/48pcp1260377230.tab") 
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Model',header=TRUE)
a<-table.element(a,'Res.DF',header=TRUE)
a<-table.element(a,'Diff. DF',header=TRUE)
a<-table.element(a,'F',header=TRUE)
a<-table.element(a,'p-value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Complete model',header=TRUE)
a<-table.element(a,gxy$Res.Df[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Reduced model',header=TRUE)
a<-table.element(a,gxy$Res.Df[2])
a<-table.element(a,gxy$Df[2])
a<-table.element(a,gxy$F[2])
a<-table.element(a,gxy$Pr[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file="/var/www/html/rcomp/tmp/5pyjl1260377230.tab") 

system("convert tmp/1c52s1260377230.ps tmp/1c52s1260377230.png")
system("convert tmp/2b0vc1260377230.ps tmp/2b0vc1260377230.png")
system("convert tmp/3xjoc1260377230.ps tmp/3xjoc1260377230.png")