Question

The data set consists of information on 4900 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, 0 if high school) Female = binary variable (1 if female, o if male) Age = age (in years) Ntheast = binary variable (1 if Region = Northeast, 0 otherwise) Midwest = binary variable (1 if Region = Midwest, 0 otherwise) South = binary variable (1 if Region = South, 0 otherwise) West = binary variable (1 if Region = West, 0 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) 5.02 5.04 5.00 College (X1) Female (X2) -2.43 - 2.41 -2.41

Answer 1

(1) Since the coefficient on northeast is 0.63, workers in Northeast earn $0.63 more on average than workers in the west

(2) Since the coefficient on south is -0.25, workers in Northeast earn $0.25 less on average than workers in the west

(3) The answer is (d) as wages ar eindeed not the same across regions which points to important r egional differences.

(4) The answer is (a) as it will lead to a dummy variable trap and thus perfect multiclllinearity.

(5) The expected difference between wages = 0.55 - (-0.25) = $0.8