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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) 5.84 5.86 5.82 -2.80 -2.82 -2.80 0.31 0.31 College (X) Female) Age (X3) Northeast (X4) Midwest X) South (X) Intercept 0.74 0.64 -0.29 13.58 4.71 4.01 Summary Statistics SER 6.71 0.188 6.66 0.203 6.64 0.208 0.207 R? 0.188 0.202 n 3900 3900 3900 in column (3)
Workers in the Northeastern Using the regression results in column (3) more per hour than workers in the West, on average controlling to other variable in the remon Hound your posts decima eta Workers in the floom &* per hour than workers in the West, on warage, controlling for other variables in the repromien (Round your response to two decimal places) Do there appear to be important regional difference? OA No, because the difference in wages is minimal OB Yes, because wages are not consistent across the region OC. No, because workers in the Midwest earn more per hour than workers in the Northeast, while worken in the South eamless per hour then werken in the West OD Yes, because workers in the Northeast am significantly more than workers in the South Why the ressor West omitted from the regression? What would happen if it was included? OA The regressor Westin mited to avoid the OS stimator bias if West is included, then the OLS stimator isbied. OB. Thesegresor West in omitted to make the OS estimator linear. If Wordt in included. then the intercept can no longer be written as a perfect linear function of the four regional regresor OC. The regressor West is omiled to minimize the sum of squared residuals. If West is included, then the sum of squared residualne fonger min med OD. The regressar Wat is cmited to avoid perfect musiciary West is included, then the OS estimator cannot be computed in a station Junta na 33-year-old female colege graduate from the South Jennifer a 33year-old female colege graduate from the Midwest Calculate the expected difference in camp between suuntaan Jerni The expected afference in mamnings between Juanita and Jennifer is per hour. (Round your response to two decimal places)