No further values were supplied for variable age.

Question 3 (this question has four parts, (a), (b), (c) and (d)) Consider the following house sale price regression model log(pricei)= Bo+ 1 age; + B2 bedrooms + B3 baths;+ B4 pooli+ B5 fireplace; + Bo waterfronti + Ui where price: sale price in thousands of dollars, age: age of the house in years, bedrooms: number of bedrooms in the house, baths: number of bathrooms in the house, pool: a dummy(binary) variable which takes the value of 1 if the house has a swimming pool and the value of 0 otherwise, fireplace: a dummy(binary) variable which takes the value of 1 if the house has a fireplace and the value of 0 otherwise. waterfront: a dummy (binary) variable which takes the value of 1 if the house has a waterfront view the value of 0 otherwise, Estimation results using 1080 observations and modified versions of the regression model obtained by dropping some of the variables are displayed in the table below. House Sale Price Estimates Dependent Variable: log(price) Coefficients Estimates and (Standard Independent Variables Errors) Equation 1 Equation 2 Equation 3 Intercept 5.683 6.676 5.682 (0.052) (0.021) (0.054) Age -0.004 -0.005 (0.001) (0.001) Bedrooms 0.136 0.132 (0.017) (0.018) Baths 0.407 0.489 (0.022) (0.022) Pool 0.109 0.278 (0.038) (0.051) Fireplace 0.192 0.422 (0.022) (0.028) Waterfront 0.211 0.433 (0.040) (0.054) N (number of observations) 1080 1080 1080 SSR (Sum of Squared Residuals) R-squared 114.799 0.613 218.207 0.265 127.887 0.569 a) Using Equation 1 estimates calculate the predicted dollar value of a brand-new 3 bedroom, 2 bathroom house which has a pool but does not have a fireplace or a waterfront view. (2 Marks) b) According to Equation 1 estimates, keeping all else constant, predict the new approximate sale value of a $500,000 house if it is renovated to extend for an additional bedroom. (2 Marks) c) Interpret the coefficient estimate of binary (dummy) variable pool in Equation 1 and determine if having a swimming pool is a significant factor in determining house sale price at 1% level of significance. (4 Marks) d) Test whether all of the continuous variables included in Equation 1 are jointly significant at 5 % level of significance. State your null and alternative hypotheses clearly. (4 Marks) Question 3 (this question has four parts, (a), (b), (c) and (d)) Consider the following house sale price regression model log(pricei)= Bo+ 1 age; + B2 bedrooms + B3 baths;+ B4 pooli+ B5 fireplace; + Bo waterfronti + Ui where price: sale price in thousands of dollars, age: age of the house in years, bedrooms: number of bedrooms in the house, baths: number of bathrooms in the house, pool: a dummy(binary) variable which takes the value of 1 if the house has a swimming pool and the value of 0 otherwise, fireplace: a dummy(binary) variable which takes the value of 1 if the house has a fireplace and the value of 0 otherwise. waterfront: a dummy (binary) variable which takes the value of 1 if the house has a waterfront view the value of 0 otherwise, Estimation results using 1080 observations and modified versions of the regression model obtained by dropping some of the variables are displayed in the table below. House Sale Price Estimates Dependent Variable: log(price) Coefficients Estimates and (Standard Independent Variables Errors) Equation 1 Equation 2 Equation 3 Intercept 5.683 6.676 5.682 (0.052) (0.021) (0.054) Age -0.004 -0.005 (0.001) (0.001) Bedrooms 0.136 0.132 (0.017) (0.018) Baths 0.407 0.489 (0.022) (0.022) Pool 0.109 0.278 (0.038) (0.051) Fireplace 0.192 0.422 (0.022) (0.028) Waterfront 0.211 0.433 (0.040) (0.054) N (number of observations) 1080 1080 1080 SSR (Sum of Squared Residuals) R-squared 114.799 0.613 218.207 0.265 127.887 0.569 a) Using Equation 1 estimates calculate the predicted dollar value of a brand-new 3 bedroom, 2 bathroom house which has a pool but does not have a fireplace or a waterfront view. (2 Marks) b) According to Equation 1 estimates, keeping all else constant, predict the new approximate sale value of a $500,000 house if it is renovated to extend for an additional bedroom. (2 Marks) c) Interpret the coefficient estimate of binary (dummy) variable pool in Equation 1 and determine if having a swimming pool is a significant factor in determining house sale price at 1% level of significance. (4 Marks) d) Test whether all of the continuous variables included in Equation 1 are jointly significant at 5 % level of significance. State your null and alternative hypotheses clearly. (4 Marks)