a) State the estimated OLS regression and interpret the slope coefficients. b) Test at 5% significance level whether or not the coefficient on GNP is significantly less than one. c) Test at 5%...


a) State the estimated OLS regression and interpret the slope coefficients.<br>b) Test at 5% significance level whether or not the coefficient on GNP is significantly<br>less than one.<br>c) Test at 5% significance level whether or not the coefficient on military sales/assistance<br>is significant.<br>

Extracted text: a) State the estimated OLS regression and interpret the slope coefficients. b) Test at 5% significance level whether or not the coefficient on GNP is significantly less than one. c) Test at 5% significance level whether or not the coefficient on military sales/assistance is significant.
In order to explain the U.S. defense budget, the following variables are considered. Data from<br>1962-1981 is collected.<br>Variable<br>Definition<br>Y<br>Defense budget-outlay for year t, $ billions<br>X2<br>GNP for year t, $ billions<br>X3<br>U.S. military sales/assistance in year t, $ billions<br>X4<br>Aerospace industry sales, $ billions<br>Dependent Variable: Y<br>Method: Least Squares<br>Date: 11/22/21 Time: 11:20<br>Sample: 1962 1981<br>Included observations: 20<br>Variable<br>Coefficient<br>Std. Error<br>t-Statistic<br>Prob.<br>X2<br>0.016703<br>0.007017<br>2.380261<br>0.0301<br>X3<br>-0.696174<br>0.453978<br>-1.533497<br>0.1447<br>X4<br>1.467729<br>0.277608<br>5.287047<br>0.0001<br>22.77514<br>3.311695<br>6.877186<br>0.0000<br>R-squared<br>0.971088<br>Mean dependent var<br>83.86000<br>Adjusted R-squared<br>0.965667<br>S.D. dependent var<br>28.97771<br>S.E. of regression<br>Sum squared resid<br>5.369339<br>Akaike info criterion<br>6.376143<br>461.2769<br>Schwarz criterion<br>6.575290<br>Log likelihood<br>-59.76143<br>Hannan-Quinn criter.<br>6.415019<br>F-statistic<br>179.1337<br>Durbin-Watson stat<br>0.676777<br>Prob(F-statistic)<br>0.000000<br>

Extracted text: In order to explain the U.S. defense budget, the following variables are considered. Data from 1962-1981 is collected. Variable Definition Y Defense budget-outlay for year t, $ billions X2 GNP for year t, $ billions X3 U.S. military sales/assistance in year t, $ billions X4 Aerospace industry sales, $ billions Dependent Variable: Y Method: Least Squares Date: 11/22/21 Time: 11:20 Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. X2 0.016703 0.007017 2.380261 0.0301 X3 -0.696174 0.453978 -1.533497 0.1447 X4 1.467729 0.277608 5.287047 0.0001 22.77514 3.311695 6.877186 0.0000 R-squared 0.971088 Mean dependent var 83.86000 Adjusted R-squared 0.965667 S.D. dependent var 28.97771 S.E. of regression Sum squared resid 5.369339 Akaike info criterion 6.376143 461.2769 Schwarz criterion 6.575290 Log likelihood -59.76143 Hannan-Quinn criter. 6.415019 F-statistic 179.1337 Durbin-Watson stat 0.676777 Prob(F-statistic) 0.000000

Jun 10, 2022
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