The table below is the result for an estimated regression of 4000 full time full year workers' data for 1998. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 34 years. The data set also contained information on the region of the country where the person lived, marital status and number of children. 1 Results of Regressions of Average Hourly Eamings on Gender and Education Binary Variables and Other Characteristics Using 1998 Data from the Current Population Survey Dependent Variable: werage hourly earnings (HE). Regressor College (2) 5.46 5.45 (0.21) (0.21) Female (X) (0.20 (0.20) Age (X) 0.29 5.44 (0.21) 1 - 262 10:04) - 2.62 (0.20) 0.29 (0.04) 0.89 (0.30) Northeast (X4) Midwest (X) (0.28) South (X) -0.27 (0.26) Intercept 12.69 (0.14 440 (1.05) 3.75 (1.06) 6,10 Summary Statistics and Joint Tests F-statistic for regional effects=0 SER R 6.22 6.21 0.176 0.190 0.194 1000 4000 4000 The followings are the variables used in the regression: AHE: Average hourly earnings College: binary variable (1 College, O High School) Female: binary variable (1 Female, O Male) Age: Age in years Ntheast: binary variable (1 Northeast 0 otherwise) Midwest: binary variable (1 Midwest, o otherwise) South: binary variable (1 South,0 otherwise) West: binary variable (1 West, 0 otherwise) Please refer to the table below to answer the following questions. a. Compute the adjusted R2 for column (1) and (2) b. Using the regression results in column (1): i. Do workers with college degrees earn more on average than workers with only high school degrees? How much more? ii. Do men earn more than women? How much more? c. Using the regression results in column (3): Jenny is a 28-year old female college graduate from the South. Bella is a 28-year old female college graduate from the Midwest. Calculate the expected difference in earnings between Jenny and Bella d. Using the regression results in column (2): i. Is age an important determinant of earnings? Justify your answer. N il. Construct a 95% confidence interval for age. The table below is the result for an estimated regression of 4000 full time full year workers' data for 1998. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 34 years. The data set also contained information on the region of the country where the person lived, marital status and number of children. 1 Results of Regressions of Average Hourly Eamings on Gender and Education Binary Variables and Other Characteristics Using 1998 Data from the Current Population Survey Dependent Variable: werage hourly earnings (HE). Regressor College (2) 5.46 5.45 (0.21) (0.21) Female (X) (0.20 (0.20) Age (X) 0.29 5.44 (0.21) 1 - 262 10:04) - 2.62 (0.20) 0.29 (0.04) 0.89 (0.30) Northeast (X4) Midwest (X) (0.28) South (X) -0.27 (0.26) Intercept 12.69 (0.14 440 (1.05) 3.75 (1.06) 6,10 Summary Statistics and Joint Tests F-statistic for regional effects=0 SER R 6.22 6.21 0.176 0.190 0.194 1000 4000 4000 The followings are the variables used in the regression: AHE: Average hourly earnings College: binary variable (1 College, O High School) Female: binary variable (1 Female, O Male) Age: Age in years Ntheast: binary variable (1 Northeast 0 otherwise) Midwest: binary variable (1 Midwest, o otherwise) South: binary variable (1 South,0 otherwise) West: binary variable (1 West, 0 otherwise) Please refer to the table below to answer the following questions. a. Compute the adjusted R2 for column (1) and (2) b. Using the regression results in column (1): i. Do workers with college degrees earn more on average than workers with only high school degrees? How much more? ii. Do men earn more than women? How much more? c. Using the regression results in column (3): Jenny is a 28-year old female college graduate from the South. Bella is a 28-year old female college graduate from the Midwest. Calculate the expected difference in earnings between Jenny and Bella d. Using the regression results in column (2): i. Is age an important determinant of earnings? Justify your answer. N il. Construct a 95% confidence interval for age