R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(10284.5,12792,12823.61538,13845.66667,15335.63636,11188.5,13633.25,12298.46667,15353.63636,12696.15385,12213.93333,13683.72727,11214.14286,13950.23077,11179.13333,11801.875,11188.82353,16456.27273,11110.0625,16530.69231,10038.41176,11681.25,11148.88235,8631,9386.444444,9764.736842,12043.75,12948.06667,10987.125,11648.3125,10633.35294,10219.3,9037.6,10296.31579,11705.41176,10681.94444,9362.947368,11306.35294,10984.45,10062.61905,8118.583333,8867.48,8346.72,8529.307692,10697.18182,8591.84,8695.607143,8125.571429,7009.758621,7883.466667,7527.645161,6763.758621,6682.333333,7855.681818,6738.88,7895.434783,6361.884615,6935.956522,8344.454545,9107.944444)
> x <- c(9904.642857,13710.15385,13747.69231,14517,15185.81818,11422.28571,13819.66667,12749,16217,13238,12391,14780.09091,10815.42857,14770.84615,11831,11931.3125,10611.94118,15923.18182,11094.875,16209.53846,10100,12149.6875,11644.35294,9249.947368,8980.777778,10244.52632,12457.5625,13307.46667,10839.625,11827.625,10925.94118,10675.3,9297.3,10433.21053,12261.41176,10911.22222,9334.421053,11655.05882,11080,9840.142857,7448.916667,8362.6,8465.64,8220.923077,10432.86364,8537.4,8535.464286,7997.464286,6301.413793,7595.566667,7200.483871,6152.482759,6064.259259,7269.909091,6578.44,7708.26087,6401.153846,7042.043478,8296.409091,9613.333333)
> par8 = '11'
> par7 = '0'
> par6 = '0'
> par5 = '1'
> par4 = '12'
> par3 = '0'
> par2 = '0'
> 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)
Loading required package: zoo

Attaching package: 'zoo'


	The following object(s) are masked from package:base :

	 as.Date.numeric 

> 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
 [1]  9903.643 13709.154 13746.692 14516.000 15184.818 11421.286 13818.667
 [8] 12748.000 16216.000 13237.000 12390.000 14779.091 10814.429 14769.846
[15] 11830.000 11930.312 10610.941 15922.182 11093.875 16208.538 10099.000
[22] 12148.688 11643.353  9248.947  8979.778 10243.526 12456.562 13306.467
[29] 10838.625 11826.625 10924.941 10674.300  9296.300 10432.211 12260.412
[36] 10910.222  9333.421 11654.059 11079.000  9839.143  7447.917  8361.600
[43]  8464.640  8219.923 10431.864  8536.400  8534.464  7996.464  6300.414
[50]  7594.567  7199.484  6151.483  6063.259  7268.909  6577.440  7707.261
[57]  6400.154  7041.043  8295.409  9612.333
> y
 [1] 10283.500 12791.000 12822.615 13844.667 15334.636 11187.500 13632.250
 [8] 12297.467 15352.636 12695.154 12212.933 13682.727 11213.143 13949.231
[15] 11178.133 11800.875 11187.824 16455.273 11109.062 16529.692 10037.412
[22] 11680.250 11147.882  8630.000  9385.444  9763.737 12042.750 12947.067
[29] 10986.125 11647.312 10632.353 10218.300  9036.600 10295.316 11704.412
[36] 10680.944  9361.947 11305.353 10983.450 10061.619  8117.583  8866.480
[43]  8345.720  8528.308 10696.182  8590.840  8694.607  8124.571  7008.759
[50]  7882.467  7526.645  6762.759  6681.333  7854.682  6737.880  7894.435
[57]  6360.885  6934.957  8343.455  9106.944
> (gyx <- grangertest(y ~ x, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:11) + Lags(, 1:11)
Model 2:  ~ Lags(, 1:11)
  Res.Df  Df      F Pr(>F)
1     26                  
2     37 -11 1.7388 0.1198
> (gxy <- grangertest(x ~ y, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:11) + Lags(, 1:11)
Model 2:  ~ Lags(, 1:11)
  Res.Df  Df      F Pr(>F)
1     26                  
2     37 -11 1.3655 0.2468
> postscript(file="/var/www/html/rcomp/tmp/1npma1260469780.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)'))

Autocorrelations of series 'X', by lag

  -14   -13   -12   -11   -10    -9    -8    -7    -6    -5    -4    -3    -2 
0.150 0.215 0.220 0.341 0.363 0.446 0.486 0.477 0.516 0.538 0.577 0.570 0.738 
   -1     0     1     2     3     4     5     6     7     8     9    10    11 
0.644 0.989 0.643 0.715 0.553 0.556 0.516 0.467 0.456 0.443 0.424 0.359 0.310 
   12    13    14 
0.207 0.199 0.128 
> (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)'))

Autocorrelations of series 'X', by lag

  -14   -13   -12   -11   -10    -9    -8    -7    -6    -5    -4    -3    -2 
0.150 0.215 0.220 0.341 0.363 0.446 0.486 0.477 0.516 0.538 0.577 0.570 0.738 
   -1     0     1     2     3     4     5     6     7     8     9    10    11 
0.644 0.989 0.643 0.715 0.553 0.556 0.516 0.467 0.456 0.443 0.424 0.359 0.310 
   12    13    14 
0.207 0.199 0.128 
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2900q1260469780.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()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3ynob1260469780.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()
null device 
          1 
> 
> #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$Pr[2])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4nvmn1260469780.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Model',header=TRUE)
> a<-table.element(a,'Res.DF',header=TRUE)
> a<-table.element(a,'Diff. DF',header=TRUE)
> a<-table.element(a,'F',header=TRUE)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Complete model',header=TRUE)
> a<-table.element(a,gxy$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/5fdou1260469780.tab") 
> 
> system("convert tmp/1npma1260469780.ps tmp/1npma1260469780.png")
> system("convert tmp/2900q1260469780.ps tmp/2900q1260469780.png")
> system("convert tmp/3ynob1260469780.ps tmp/3ynob1260469780.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.999   0.470   1.175