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Vars bag with grangertest functionCodePudding user response:
Can refer to the var (), use the causality (x, cause=NULL, vcov.=NULL, the boot=FALSE, boot. Runs=100)CodePudding user response:
The landlord directly next vars package inside haveUr. Df (y, type=c (" none ", "drift", "trend"), lags=1, selectlags=c (" Fixed ", "AIC", "BIC")) unit root test
Ur. Df (diff ()) after the difference of unit root test
Causality (x, cause=NULL, vcov.=NULL, the boot=FALSE, boot. Runs=100) cause and effect analysis, the results of a granger causality test
From management
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Lmtest package can,The library (lmtest)
Grangertest (GDP to consumption, the order=2, data=https://bbs.csdn.net/topics/ts.data)
Granger causality test
Model 1: ~ Lags GDP (GDP, 1:2) + Lags (consumption, 1:2)
Model 2: ~ Lags GDP (GDP, 1:2)
Res. Df Df F Pr (& gt; F)
1
1820-2 1.6437 0.221
Grangertest (consumption to GDP, the order=2, data=https://bbs.csdn.net/topics/ts.data)
Granger causality test
Model 1: consumption ~ Lags (consumption, 1:2) + Lags (GDP, 1:2)
Model 2: consumption ~ Lags (consumption, 1:2)
Res. Df Df F Pr (& gt; F)
1
1820-2 13.411 0.0002717 * * *
-- -- --
Signif. Codes: 0 '* * *' 0.001 '* *' 0.01 '*' 0.05 '. '0.1' '1
Inspection results, said when the null hypothesis is "consumption is not the Granger cause of change of GDP", P value is 0.221 & gt; 0.05 that we are unable to refuse to null hypothesis; And when the null hypothesis is "GDP is not the Granger cause of the change of the consumption, the P value is 0.0002717 & lt; 0.05, we can reject the null hypothesis, therefore, can prove that GDP is the Granger cause of consumption,