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Type 'q()' to quit R. > y <- c(325412,326011,328282,317480,317539,313737,312276,309391,302950,300316,304035,333476,337698,335932,323931,313927,314485,313218,309664,302963,298989,298423,310631,329765,335083,327616,309119,295916,291413,291542,284678,276475,272566,264981,263290,296806,303598,286994,276427,266424,267153,268381,262522,255542,253158,243803,250741,280445,285257,270976,261076,255603,260376,263903,264291,263276,262572,256167,264221,293860,300713,287224) > x <- c(285351,286602,283042,276687,277915,277128,277103,275037,270150,267140,264993,287259,291186,292300,288186,281477,282656,280190,280408,276836,275216,274352,271311,289802,290726,292300,278506,269826,265861,269034,264176,255198,253353,246057,235372,258556,260993,254663,250643,243422,247105,248541,245039,237080,237085,225554,226839,247934,248333,246969,245098,246263,255765,264319,268347,273046,273963,267430,271993,292710,295881,293299) > par8 = '8' > par7 = '1' > par6 = '1' > par5 = '1' > par4 = '12' > par3 = '1' > 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] -137 -554 -354 -49 -1679 243 -1506 3267 2146 -894 -3775 -3003 [13] 460 -9680 -1971 -5144 5639 -5076 -5406 -225 -6432 -7644 4693 1513 [25] -7904 9774 1459 7648 -1737 1356 1019 1850 -4235 11970 -2089 -2038 [37] 4966 2149 8386 5819 7118 7530 12658 912 4998 3278 -378 2772 [49] -1218 > y [1] -2365 -14272 798 499 2535 -2093 -3816 2467 2068 8489 [11] -10307 1096 -5701 -6496 -3199 -5061 1396 -3310 -1502 65 [21] -7019 -13899 14382 1474 -9137 7930 3200 5232 1099 1005 [31] 1223 1525 -1770 8629 -3812 -1980 2323 667 4530 4044 [41] 2299 6247 5965 1680 2950 1116 -65 2041 792 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:8) + Lags(, 1:8) Model 2: ~ Lags(, 1:8) Res.Df Df F Pr(>F) 1 24 2 32 -8 2.4531 0.04252 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:8) + Lags(, 1:8) Model 2: ~ Lags(, 1:8) Res.Df Df F Pr(>F) 1 24 2 32 -8 1.9214 0.1033 > postscript(file="/var/www/html/rcomp/tmp/14lho1260468854.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 0.265 0.422 0.573 0.608 0.564 0.528 0.533 0.580 0.613 0.604 0.579 0.573 0.616 -1 0 1 2 3 4 5 6 7 8 9 10 11 0.726 0.815 0.731 0.579 0.457 0.404 0.393 0.363 0.299 0.217 0.171 0.179 0.254 12 13 14 0.276 0.177 0.032 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -0.061 -0.171 0.196 0.017 -0.075 0.107 -0.019 0.244 -0.062 0.119 0.275 -2 -1 0 1 2 3 4 5 6 7 8 0.163 0.089 0.729 0.107 0.013 0.419 0.038 0.193 -0.065 0.102 0.193 9 10 11 12 13 0.064 -0.042 0.340 -0.070 0.007 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/24mh61260468854.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/3289o1260468854.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/407k01260468854.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/5gwdp1260468854.tab") > system("convert tmp/14lho1260468854.ps tmp/14lho1260468854.png") > system("convert tmp/24mh61260468854.ps tmp/24mh61260468854.png") > system("convert tmp/3289o1260468854.ps tmp/3289o1260468854.png") > > > proc.time() user system elapsed 0.956 0.474 1.086