Suppose you are estimating parameters of the following regression model: Ŷt = 9941 + 0.25 X2t+ 15125 X3t (6114) (0.121) (7349) R 2= 0.87, RSS = 10310 (The figures in parentheses are the estimated standard errors. RSS are residual sum of squares.) (i) Comment on the signs of the variables in the model. (ii) Interpret and explain individual coefficients. (iii) Suppose X3 increases by 0.25; what is the expected impact of this change on Y? (iv) Comment on the explanatory power of the regression. (v) Using t-tests show whether individual coefficients are significantly different from zero at 5% level of significance. (vi) Test whether the coefficient of X2 is significantly different from 1 at 5% level of significance. (vii) Carry out an appropriate test to check if coefficients are jointly significant.

Suppose you are estimating parameters of the following regression
model:

Ŷt = 9941 + 0.25 X2t+ 15125 X3t

(6114) (0.121) (7349)

R 2= 0.87, RSS = 10310

(The figures in parentheses are the estimated standard errors. RSS are
residual sum of squares.)

(i) Comment on the signs of the variables in the model.

(ii) Interpret and explain individual coefficients.

(iii) Suppose X3 increases by 0.25; what is the expected impact of
this change on Y?

(iv) Comment on the explanatory power of the regression.

(v) Using t-tests show whether individual coefficients are
significantly different from zero at 5% level of significance.

(vi) Test whether the coefficient of X2 is significantly different
from 1 at 5% level of significance.

(vii) Carry out an appropriate test to check if coefficients are
jointly significant.