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 = '1'
> 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)
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]  3805.510993    37.538460   769.307690   668.818180 -3763.532470
 [6]  2397.380960 -1070.666670  3468.000000 -2979.000000  -847.000000
[11]  2389.090910 -3964.662340  3955.417580 -2939.846150   100.312500
[16] -1319.371320  5311.240640 -4828.306820  5114.663460 -6109.538460
[21]  2049.687500  -505.334560 -2394.405572  -269.169590  1263.748542
[26]  2213.036180   849.904170 -2467.841670   988.000000  -901.683820
[31]  -250.641180 -1378.000000  1135.910530  1828.201230 -1350.189540
[36] -1576.801167  2320.637767  -575.058820 -1239.857143 -2391.226190
[41]   913.683333   103.040000  -244.716923  2211.940563 -1895.463640
[46]    -1.935714  -538.000000 -1696.050493  1294.152874  -395.082796
[51] -1048.001112   -88.223500  1205.649832  -691.469091  1129.820870
[56] -1307.107024   640.889632  1254.365613  1316.924242
> y
 [1]  2507.50000    31.61538  1022.05129  1489.96969 -4147.13636  2444.75000
 [7] -1334.78333  3055.16969 -2657.48251  -482.22052  1469.79394 -2469.58441
[13]  2736.08791 -2771.09744   622.74167  -613.05147  5267.44920 -5346.21023
[19]  5420.62981 -6492.28055  1642.83824  -532.36765 -2517.88235   755.44444
[25]   378.29240  2279.01316   904.31667 -1960.94167   661.18750 -1014.95956
[31]  -414.05294 -1181.70000  1258.71579  1409.09597 -1023.46732 -1318.99707
[37]  1943.40557  -321.90294  -921.83095 -1944.03572   748.89667  -520.76000
[43]   182.58769  2167.87413 -2105.34182   103.76714  -570.03571 -1115.81281
[49]   873.70805  -355.82151  -763.88654   -81.42529  1173.34849 -1116.80182
[55]  1156.55478 -1533.55017   574.07191  1408.49802   763.48990
> (gyx <- grangertest(y ~ x, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:1) + Lags(, 1:1)
Model 2:  ~ Lags(, 1:1)
  Res.Df Df      F Pr(>F)
1     55                 
2     56 -1 0.0054 0.9417
> (gxy <- grangertest(x ~ y, order=par8))
Granger causality test

Model 1:  ~ Lags(, 1:1) + Lags(, 1:1)
Model 2:  ~ Lags(, 1:1)
  Res.Df Df      F Pr(>F)
1     55                 
2     56 -1 0.1311 0.7187
> postscript(file="/var/www/html/rcomp/tmp/1p7uh1260471388.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 
-0.138  0.095 -0.162  0.136 -0.085  0.060  0.077 -0.078  0.035 -0.042  0.077 
    -3     -2     -1      0      1      2      3      4      5      6      7 
-0.250  0.365 -0.624  0.976 -0.593  0.326 -0.235  0.066  0.006 -0.049 -0.003 
     8      9     10     11     12     13     14 
 0.013  0.064 -0.022  0.075 -0.134  0.095 -0.169 
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2k1bw1260471388.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/3amhq1260471388.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$Pr[2])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4na0a1260471388.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Model',header=TRUE)
> a<-table.element(a,'Res.DF',header=TRUE)
> a<-table.element(a,'Diff. DF',header=TRUE)
> a<-table.element(a,'F',header=TRUE)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Complete model',header=TRUE)
> a<-table.element(a,gxy$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/5liwf1260471388.tab") 
> 
> system("convert tmp/1p7uh1260471388.ps tmp/1p7uh1260471388.png")
> system("convert tmp/2k1bw1260471388.ps tmp/2k1bw1260471388.png")
> system("convert tmp/3amhq1260471388.ps tmp/3amhq1260471388.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.896   0.458   1.049