Use the regression results in columns: (a) using the regression results in column (1), is the college-high school earningsdifference estimated from this regression statistically significant at the 5% ofsignificance level (α = 0.05)? use a 95% confidence interval of the difference, whereyou can use the standard normal approximation for a critical value (i. e. tcrit ≈ 1.: think about the meaning of dummy ) using the regression results in column (2), is age a determinant of earnings? usean appropriate statistical test of age at the 5% significance level (α = 0.) using the regression results in column (2), sally is a 29-year-old female collegegraduate. sophie is a 32-year-old female college graduate. using the standardnormal approximation (i. e. tcrit ≈ 1.96), construct a 95% confidence interval forthe expected difference between their earnings. (hint: think about what makesthem different and the meaning of dummy ) using the regression results in column (3), do there appear to be importantregional differences? assuming the variance of errors is homoskedastic, use anappropriate hypothesis test to explain your answer. (hint: you have multipleparameters in your null ) the regression shown in column (2) was estimated again, this time using data from1992 (inflation-adjusted to 2012 dollars). the results are: +8.66(.33)college+4.24(.29)f emale− .65(.05)age, n = 7440, ser = 9.57, adj. r2 = 0.21,comparing this regression to the regression for 2012 shown in col-umn (2), was there a statistically significant change in the coefficient oncollege? that is, test for h0 : βcollege,2012 − βcollege,1992 = 0.
dependent variable: average hourly earnings (ahe) regressor college (x1) female (x2) age (x3) northeast (x4) midwest (xs) south xe) intercept 8.31 8.32 8.34 (0.23) (0.22) (0.22) 3.85 -3.81 3.8o (0.23) (0.22) 0.22) 0.51 0.52 (0.04) (0.04) 0.18 (0.36) (0.31) 0.43 (0.30) 17.02 87 2.05 summary statistics ser r2 adj. r2 (or r2) 9.79 9.68 9.67 0.162 0.180 0.182 7440 7440 7440 note: the standard errors are in parentheses along with the estimates.