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 TableModel 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) + seasRes. DfRSS Df Sum of SqF Pr(>F)1 109 0.058974298 0.057042 11 0.0019317 0.3017 0.9841

Timeseries data is used to analyze the impact of the independent variable on the dependent variable…

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)

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)

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Question

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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