The data set consists of information on

4100

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, 0 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)
College (X1)	5.35	5.37	5.33
Female (X2)	2.59	2.57	2.57
Age (X3)		0.28	0.28
Northeast (X4)			0.68
Midwest (X5)			0.59
South (X6)			0.26
Intercept	12.44	4.31	3.68
Summary Statistics
SER	6.14	6.10	6.09
R2	0.172	0.186	0.190
R2
n	4100	4100	4100

Compute

R2

for each of the regressions.

R2

for column (1) is

enter your response here.

(Round

your response to three decimal

places.)

R2

for column (2) is

enter your response here.

(Round

your response to three decimal

places.)

R2

for column (3) is

enter your response here.

(Round

your response to three decimal

places.)

Using the regression results in column (1):

Workers with college degrees earn

$enter your response here

per hour

,

on average, than workers with only high school degrees.

(Round

your response to two decimal

places.)

Men earn

$enter your response here

per hour

more

less

than women on average.

(Round

your response to two decimal

places.)