9. [40pts] Suppose you're interested in the following model log (y)i = a + Balog (height); + Bzlog (Weight); + &i where earnings, height, and weight are measured in $, inches, and pounds, respectively. You estimated the model and obtained the following result. reg log_earnings log_height log_weight Source SS df MS Model Residual 113.28004 7717.1403 2 56.6400199 17,867.431921436 Number of obs F(2, 17867) Prob > F R-squared Adj R-squared Root MSE 17,870 131.14 0.0000 0.0145 0.0144 .65721 Total 7830.42034 17,869 .438212566 log_earnings Coef. Std. Err. t P>It! (95% Conf. Intervall log_height log_weight 1.494383 -.0972874 4.777558 0948291 .0224106 .3576247 15.76 -4.34 13.36 0.000 0.000 0.000 1.308509 -.1412143 4.076579 1.680257 -.0533605 5.478537 -cons a. Interpret the effect of weight on earnings from the regression. b. Interpret the effect of height on earnings from the regression. C. Explain what R-squared means. d. You would like to test B1 = B2 = 0. Provide (i) unrestricted regression and (ii) restricted regression. e. What statistics are you going to use to test the hypothesis in d.? How would you find the value of the statistics? 9. [40pts] Suppose you're interested in the following model log (y)i = a + Balog (height); + Bzlog (Weight); + &i where earnings, height, and weight are measured in $, inches, and pounds, respectively. You estimated the model and obtained the following result. reg log_earnings log_height log_weight Source SS df MS Model Residual 113.28004 7717.1403 2 56.6400199 17,867.431921436 Number of obs F(2, 17867) Prob > F R-squared Adj R-squared Root MSE 17,870 131.14 0.0000 0.0145 0.0144 .65721 Total 7830.42034 17,869 .438212566 log_earnings Coef. Std. Err. t P>It! (95% Conf. Intervall log_height log_weight 1.494383 -.0972874 4.777558 0948291 .0224106 .3576247 15.76 -4.34 13.36 0.000 0.000 0.000 1.308509 -.1412143 4.076579 1.680257 -.0533605 5.478537 -cons a. Interpret the effect of weight on earnings from the regression. b. Interpret the effect of height on earnings from the regression. C. Explain what R-squared means. d. You would like to test B1 = B2 = 0. Provide (i) unrestricted regression and (ii) restricted regression. e. What statistics are you going to use to test the hypothesis in d.? How would you find the value of the statistics