Question
(10 marks) Consider the following regression model Yi = 0+ 1 X 1 i + 2 X 2 i + 3 X 3 i +
(10 marks) Consider the following regression model
Yi=0+1X1i+2X2i+3X3i+4X4i+5X5i+ui
This model has been estimated by OLS. The Gretl output is below, followed by the estimate of the covariance matrix of the estimated parameters.
Model 1: OLS, using observations 1-64
coefficient std. error t-ratio p-value
Const -2.1251 0.6699 -3.1722 0.0024
X1 1.0808 0.2870 3.7654 0.0004
X2 0.3086 0.6461 0.4777 0.6347
X3 -0.1845 0.1963 -0.9399. 0.3512
X4 -1.1133 0.1819 -6.1205 0.0000
X5. 1.1584 0.1610 7.1974 0.0000
Mean dependent var = 2.4923
S.D. dependent var = 3.5275
Sum squared resid = 242.69
S.E. of regression = 2.0456
R-squared = 0.69042
Adjusted R-squared = 0.66373
F(5, 58) = 25.87
P-value(F) = 0
Log-likelihood = 133.47
Akaike criterion = 278.93
Schwarz criterion = 291.88
Hannan-Quinn = 284.03
Const X1 X2 X3 X4 X5
Const 0.44875 0.06749- 0.23991 -0.04240 -0.04398. -0.04214
X1 0.06749 0.08239. 0.00832. -0.00466 0.00449. -0.00669
X2 -0.23991 0.00832 0.41743 -0.01234 -0.00227. -0.00740
X3 -0.04240. -0.00466 -0.01234. 0.03854 0.00301 -0.00216
X4 -0.04398. 0.00449. -0.00227. 0.00301 0.03309 0.00245
X5 -0.04214 -0.00669 -0.00740 -0.00216 0.00245. 0.02590
Use a t-test with the critical value method and a significance level of 5% to test 0:4=3against1:43
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