The data set consists of information on 4700 full-time full-year workers. 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 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if college, O if high school) Female = binary variable (1 if female. O if male) Age = age in years) Ntheast = binary variable (1 if Region = Northeast, otherwise) Midwest = binary variable (1 if Region = Midwest, otherwise) South = binary variable (1 if Region = South, 0 otherwise) West = binary variable (1 if Region = West, otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) 5.24 5.26 5.22 -2.53 -2.52 -2.52 0.28 0.28 College (X1) Female (X2) Age (X3) Northeast (X4) Midwest (5) South (X) Intercept 0.66 0.58 -0.26 12.18 4.22 3.60 Summary Statistics SER R2 R2 6.02 0.169 5.97 0.182 5.96 0.186 n 4700 4700 4700 Compute for each of the regressions. R? for column (1) is (Round your response to three decimal places.) R? for column (2) is (Round your response to three decimal places.) R? for column (3) is (Round your response to three decimal places.) Using the regression results in column (1): Workers with college degrees earn $ per hour on average, than workers with only high school degrees. (Round your response to two decimal places.) Men earn $ per hour than women on average. (Round your response to two decimal places.) The data set consists of information on 4700 full-time full-year workers. 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 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if college, O if high school) Female = binary variable (1 if female. O if male) Age = age in years) Ntheast = binary variable (1 if Region = Northeast, otherwise) Midwest = binary variable (1 if Region = Midwest, otherwise) South = binary variable (1 if Region = South, 0 otherwise) West = binary variable (1 if Region = West, otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor (1) (2) (3) 5.24 5.26 5.22 -2.53 -2.52 -2.52 0.28 0.28 College (X1) Female (X2) Age (X3) Northeast (X4) Midwest (5) South (X) Intercept 0.66 0.58 -0.26 12.18 4.22 3.60 Summary Statistics SER R2 R2 6.02 0.169 5.97 0.182 5.96 0.186 n 4700 4700 4700 Compute for each of the regressions. R? for column (1) is (Round your response to three decimal places.) R? for column (2) is (Round your response to three decimal places.) R? for column (3) is (Round your response to three decimal places.) Using the regression results in column (1): Workers with college degrees earn $ per hour on average, than workers with only high school degrees. (Round your response to two decimal places.) Men earn $ per hour than women on average. (Round your response to two decimal places.)
