There is some economic research which suggests that oil prices play a central role in causing recessions in developed countries. Some of this work suggests that it is only oil price increases that matter and even more specifically, that it is the percentage point difference between oil prices at date t and the maximum value over the previous year. Realizing that energy prices in general can fluctuate quite dramatically in both directions and that geographic areas also benefit substantially from oil price decreases, you decide to estimate the following distributed lag model using annual data (numbers in parenthesis are HAC standard errors): $\begin{array} { c }
\hat { \mathrm { Y } } _ { \mathrm { t } } = 3.39 - 0.009 ( \text { Poil } / C P I ) \mathrm { t } - 0.028 ( \text { Poil } / C P I ) \mathrm { t } - 1 \
( 0.27 ) ( 0.010 ) \quad ( 0.011 ) \
\mathrm { t } = 1960 - 2008 , R ^ { 2 } = 0.15 , \text { SER } = 1.88
\end{array}$
a. What is the impact effect of a 25 percent increase in real oil prices?
b. What is the predicted cumulative change in GDP Growth over two years of this effect?
c. The HAC F-statistic is 4.07. Can you reject the null hypothesis that oil price changes have no effect on real GDP growth? What is the critical value you considered? Is there any reason why you should be cautious using an F-test in this case, given the sample period?

Question

There is some economic research which suggests that oil prices play a central role in causing recessions in developed countries. Some of this work suggests that it is only oil price increases that matter and even more specifically, that it is the percentage point difference between oil prices at date t and the maximum value over the previous year. Realizing that energy prices in general can fluctuate quite dramatically in both directions and that geographic areas also benefit substantially from oil price decreases, you decide to estimate the following distributed lag model using annual data (numbers in parenthesis are HAC standard errors): $\begin{array} { c } 
\hat { \mathrm { Y } } _ { \mathrm { t } } = 3.39 - 0.009 ( \text { Poil } / C P I ) \mathrm { t } - 0.028 ( \text { Poil } / C P I ) \mathrm { t } - 1 \
( 0.27 ) ( 0.010 ) \quad ( 0.011 ) \
\mathrm { t } = 1960 - 2008 , R ^ { 2 } = 0.15 , \text { SER } = 1.88
\end{array}$
a. What is the impact effect of a 25 percent increase in real oil prices?
b. What is the predicted cumulative change in GDP Growth over two years of this effect?
c. The HAC F-statistic is 4.07. Can you reject the null hypothesis that oil price changes have no effect on real GDP growth? What is the critical value you considered? Is there any reason why you should be cautious using an F-test in this case, given the sample period?

Quizplus · Accepted Answer

The Answer of There is some economic research which suggests that oil prices play a central role in causing recessions in developed countries. Some of this work suggests that it is only oil price increases that matter and even more specifically, that it is the percentage point difference between oil prices at date t and the maximum value over the previous year. Realizing that energy prices in general can fluctuate quite dramatically in both directions and that geographic areas also benefit substantially from oil price decreases, you decide to estimate the following distributed lag model using annual data (numbers in parenthesis are HAC standard errors): $\begin{array} { c } 
\hat { \mathrm { Y } } _ { \mathrm { t } } = 3.39 - 0.009 ( \text { Poil } / C P I ) \mathrm { t } - 0.028 ( \text { Poil } / C P I ) \mathrm { t } - 1 \
( 0.27 ) ( 0.010 ) \quad ( 0.011 ) \
\mathrm { t } = 1960 - 2008 , R ^ { 2 } = 0.15 , \text { SER } = 1.88
\end{array}$
a. What is the impact effect of a 25 percent increase in real oil prices?
b. What is the predicted cumulative change in GDP Growth over two years of this effect?
c. The HAC F-statistic is 4.07. Can you reject the null hypothesis that oil price changes have no effect on real GDP growth? What is the critical value you considered? Is there any reason why you should be cautious using an F-test in this case, given the sample period?

There Is Some Economic Research Which Suggests That Oil Prices