In order to explain the US defense budget, you are using the data from 1962 to...

    

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In order to explain the US defense budget, you are using the data from 1962 to 1981 with the following variables (all measured in billions USD) and estimate the corresponding model (Model 1):(Use a=0.05 for references) Defense budget outlay for year t US military sales in year t Y: Xx GNP for year t X X D Aerospace industry sales in year t Dummy variable presenting the military conflict involving more than 100,000 troops; D1-1 if more than 100,000 troops are involved and equal to 0 if fewer than 100,000 troops are involved. Dependent Variable: Y Method: Least Squares Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. 21.40251 1.496947 14.29744 0.0000 D1 -48.21987 6.871544 -7.017328 0.0000 X2 0.013879 0.003207 4.328062 0.0008 X3 0.073146 0.203805 0.358902 0.7254 X4 1.389753 0.130197 10.67423 0.0000 X4*D1 1.540792 0.325005 4.740818 0.0004 X2*D1 0.022406 0.005781 3.876038 0.0019 R-squared 0.996366 Mean dependent var 83.86000 Adjusted R-squared 0.994688 S.D. dependent var 28.97771 S.E. of regression 2.111972 Akaike info criterion 4.602338 Sum squared resid 57.98554 Schwarz criterion 4.950845 Log likelihood -39.02338 Durbin-Watson stat 2.233771 F-statistic Prob(F-statistic) 593.9815 0.000000 1. [10]Explain the meaning of each estimated coefficient and R in the above model. 2. [10] Test for significance of each independent variable and test for overall significance of the model. 3. [15]Conduct the test of autocorrelation in the model using the information above. State clearly the conditions to apply this test? If those conditions are not met, name other tests you can use instead. 4. [10] When GNP increases by 1 bil USD (other variables unchanged), what is the confidence interval of the difference in the changing levels of defense budget between the cases of there are more than 100,000 or fewer than 100,000 troops involved in the military conflict? 5. [20]For the case when there are fewer than 100,000 troops involving in the conflict (this condition indicates that we are concerning on the coefficients of X2 and X4 only), if we simultaneously increase X2 and X4 by 1 billions USD, test the proposition that the defense budget will increase 1.4 billions USD. What is the confidence interval for the increase in the level of defense budget in this case? (The covariance between two estimated coefficients of 2 variables X2 and X4 is -0.00036). Result (1) Result (2) 6 5 3 2 1 | 1 - 2 N Series: Residuals Sample 1962 1961 Observations 20 Mean -1.13E-14 Median 0.140813 Maximum 2.855637 Minimum -3.215228 Std. Dev. 1.746960 Skewness -0.218699 Kurtosis 2.211793 Jarque-Bera 0.677155 Probability 0.712783 White Heteroskedasticity Test (No cross term) F-statistic Obs*R-squared 2.379399 Probability 0.114212 15.31799 Probability 0.168397 Result (3) Breusch-Godfrey Serial Correlation LM Test: AR(2) F-statistic Obs*R-squared 1.950537 Probability 0.188349 5.235963 Probability 0.072950 Result (4) Ramsey RESET Test: F-statistic 2.110154 Probability 0.119102 Log likelihood ratio 7.432899 Probability 0.059308 In order to explain the US defense budget, you are using the data from 1962 to 1981 with the following variables (all measured in billions USD) and estimate the corresponding model (Model 1):(Use a=0.05 for references) Defense budget outlay for year t US military sales in year t Y: Xx GNP for year t X X D Aerospace industry sales in year t Dummy variable presenting the military conflict involving more than 100,000 troops; D1-1 if more than 100,000 troops are involved and equal to 0 if fewer than 100,000 troops are involved. Dependent Variable: Y Method: Least Squares Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. 21.40251 1.496947 14.29744 0.0000 D1 -48.21987 6.871544 -7.017328 0.0000 X2 0.013879 0.003207 4.328062 0.0008 X3 0.073146 0.203805 0.358902 0.7254 X4 1.389753 0.130197 10.67423 0.0000 X4*D1 1.540792 0.325005 4.740818 0.0004 X2*D1 0.022406 0.005781 3.876038 0.0019 R-squared 0.996366 Mean dependent var 83.86000 Adjusted R-squared 0.994688 S.D. dependent var 28.97771 S.E. of regression 2.111972 Akaike info criterion 4.602338 Sum squared resid 57.98554 Schwarz criterion 4.950845 Log likelihood -39.02338 Durbin-Watson stat 2.233771 F-statistic Prob(F-statistic) 593.9815 0.000000 1. [10]Explain the meaning of each estimated coefficient and R in the above model. 2. [10] Test for significance of each independent variable and test for overall significance of the model. 3. [15]Conduct the test of autocorrelation in the model using the information above. State clearly the conditions to apply this test? If those conditions are not met, name other tests you can use instead. 4. [10] When GNP increases by 1 bil USD (other variables unchanged), what is the confidence interval of the difference in the changing levels of defense budget between the cases of there are more than 100,000 or fewer than 100,000 troops involved in the military conflict? 5. [20]For the case when there are fewer than 100,000 troops involving in the conflict (this condition indicates that we are concerning on the coefficients of X2 and X4 only), if we simultaneously increase X2 and X4 by 1 billions USD, test the proposition that the defense budget will increase 1.4 billions USD. What is the confidence interval for the increase in the level of defense budget in this case? (The covariance between two estimated coefficients of 2 variables X2 and X4 is -0.00036). Result (1) Result (2) 6 5 3 2 1 | 1 - 2 N Series: Residuals Sample 1962 1961 Observations 20 Mean -1.13E-14 Median 0.140813 Maximum 2.855637 Minimum -3.215228 Std. Dev. 1.746960 Skewness -0.218699 Kurtosis 2.211793 Jarque-Bera 0.677155 Probability 0.712783 White Heteroskedasticity Test (No cross term) F-statistic Obs*R-squared 2.379399 Probability 0.114212 15.31799 Probability 0.168397 Result (3) Breusch-Godfrey Serial Correlation LM Test: AR(2) F-statistic Obs*R-squared 1.950537 Probability 0.188349 5.235963 Probability 0.072950 Result (4) Ramsey RESET Test: F-statistic 2.110154 Probability 0.119102 Log likelihood ratio 7.432899 Probability 0.059308

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The estimated equation for the defense budget Y is as follows based on the regression output for Mod... View the full answer