What is multicollinearity?Discuss causes and consequences of multicollinearity for OLS estimation. Suggest possible remedial measures.b)Suppose you are estimating parameters of the following regression model: Ŷt= 9941 + 0.25 X2t+ 15125 X3t (6114) (0.121) (7349) R2= 0.87, RSS = 10310 (The figures in parentheses are the estimated standard errors. RSS are residual sum of squares.) (i) Comment on the explanatory power of the regression. (ii)Using t-tests show whether individual coefficients are significantly different from zero at 5% level of significance. (iii)Test whether the coefficient of X2issignificantly different from 1 at 5% level of significance .(iv)Carry out an appropriate test to check ifcoefficients are jointly significant.
a)What is multicollinearity?Discuss causes and consequences of multicollinearity for OLS estimation. Suggest possible remedial measures.b)Suppose you are estimating parameters of the following regression model:
Ŷt= 9941 + 0.25 X2t+ 15125 X3t
(6114) (0.121) (7349)
R2= 0.87, RSS = 10310
(The figures in parentheses are the estimated standard errors. RSS are residual sum of squares.)
(i) Comment on the explanatory power of the regression.
(ii)Using t-tests show whether individual coefficients are significantly different from zero at 5% level of significance.
(iii)Test whether the coefficient of X2issignificantly different from 1 at 5% level of significance
.(iv)Carry out an appropriate test to check ifcoefficients are jointly significant.
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