Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the regression function (standard errors in parentheses) $$\begin{array} { llll }
Defen\widehat {se ~Spe}nding _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$
a)How many years' worth of data do you have? How can you tell? Explain.
b)Do you suspect that autocorrelation might be present in this model? If so,what type? Why? Explain.
c)How would you use the Regression test for AR(2)to determine whether autocorrelation is present? Explain.
d)What is the preferred method of correct for potential autocorrelation? Why is it preferred? Explain.
Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the sample regression function (standard errors in parentheses) $$\begin{array} { llll }
Defen\widehat {se ~Spe}nding _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$

Question

Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the regression function (standard errors in parentheses) $$\begin{array} { llll } 
Defen\widehat {se ~Spe}nding  _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$ 
a)How many years' worth of data do you have? How can you tell? Explain.
b)Do you suspect that autocorrelation might be present in this model? If so,what type? Why? Explain.
c)How would you use the Regression test for AR(2)to determine whether autocorrelation is present? Explain.
d)What is the preferred method of correct for potential autocorrelation? Why is it preferred? Explain.
Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the sample regression function (standard errors in parentheses) $$\begin{array} { llll } 
Defen\widehat {se ~Spe}nding  _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$

Quizplus · Accepted Answer

The Answer of Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the regression function (standard errors in parentheses) $$\begin{array} { llll } 
Defen\widehat {se ~Spe}nding  _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$ 
a)How many years' worth of data do you have? How can you tell? Explain.
b)Do you suspect that autocorrelation might be present in this model? If so,what type? Why? Explain.
c)How would you use the Regression test for AR(2)to determine whether autocorrelation is present? Explain.
d)What is the preferred method of correct for potential autocorrelation? Why is it preferred? Explain.
Suppose you are interested in explaining variation in annual Defense Spending (billions)and that you estimate the sample regression function (standard errors in parentheses) $$\begin{array} { llll } 
Defen\widehat {se ~Spe}nding  _ { t } = &207.66 + &0.48 \text { Population } _ { t } + &1.39 \text { Tax Revenue } _ { t } \
& (22.95)& (0.09) &(0.68) \
n = 78 \
R ^ { 2 } = .9683 \
\end{array}$$

Suppose You Are Interested in Explaining Variation in Annual Defense