What is tested in Figure 4? What is the conclusion? Note: anova(m3, m4, test="F") = getest (m3, m4) & seas = season(dlunemp). Figure 4: Granger Causality Test > #Model 4 seas = seasonaldummy (dlunemp)

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What is tested in Figure 4? What is the conclusion?
Note: anova(m3, m4, test="F") = getest (m3, m4) & seas = season(dlunemp).
Figure 4: Granger Causality Test
> #Model 4
> seas = seasonaldummy (dlunemp)
> m4 <- dyn Im (dlunemp L (dlunemp, 1:2)+L(dih, 0:2)+L(dlinc, 0:1)+seas)
> anova(m3, #4, test-"F")
Analysis of variance Table
Model 1: dlunemp~ L(dlunemp, 1:2)+L(dlh, 0:2)+L(dlinc, 0:1)
Model 2: dlunemp~ L(dlunemp, 1:2)+L(dlh, 0:2)+L(dlinc, 0:1) + seas
Res. Df
RSS Df Sum of Sq
F Pr(>F)
1 109 0.058974
2
98 0.057042 11 0.0019317 0.3017 0.9841
Transcribed Image Text:What is tested in Figure 4? What is the conclusion? Note: anova(m3, m4, test="F") = getest (m3, m4) & seas = season(dlunemp). Figure 4: Granger Causality Test > #Model 4 > seas = seasonaldummy (dlunemp) > m4 <- dyn Im (dlunemp L (dlunemp, 1:2)+L(dih, 0:2)+L(dlinc, 0:1)+seas) > anova(m3, #4, test-"F") Analysis of variance Table Model 1: dlunemp~ L(dlunemp, 1:2)+L(dlh, 0:2)+L(dlinc, 0:1) Model 2: dlunemp~ L(dlunemp, 1:2)+L(dlh, 0:2)+L(dlinc, 0:1) + seas Res. Df RSS Df Sum of Sq F Pr(>F) 1 109 0.058974 2 98 0.057042 11 0.0019317 0.3017 0.9841
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