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354 Chapter 8 Nonlinear Regression Functions

E8.2 On the text website www.pearsonglobaleditions.com/Stock_Watson you
will find a data file CPS12, which contains data for full-time, full-year
workers, ages 25–34, with a high school diploma or B.A./B.S. as their high-
est degree. A detailed description is given in CPS12_Description, also
available on the website. (These are the same data as in CPS92_12, used
in Empirical Exercise 3.1, but are limited to the year 2012.) In this exercise,
you will investigate the relationship between a worker’s age and earnings.
(Generally, older workers have more job experience, leading to higher
productivity and higher earnings.)

a. Run a regression of average hourly earnings (AHE) on age (Age),
gender (Female), and education (Bachelor). If Age increases from
25 to 26, how are earnings expected to change? If Age increases from
33 to 34, how are earnings expected to change?

b. Run a regression of the logarithm of average hourly earnings,
ln(AHE), on Age, Female, and Bachelor. If Age increases from 25 to
26, how are earnings expected to change? If Age increases from 33 to
34, how are earnings expected to change?

c. Run a regression of the logarithm of average hourly earnings,
ln(AHE), on ln(Age), Female, and Bachelor. If Age increases from
25 to 26, how are earnings expected to change? If Age increases from
33 to 34, how are earnings expected to change?

d. Run a regression of the logarithm of average hourly earnings,
ln(AHE), on Age, Age2, Female, and Bachelor. If Age increases from
25 to 26, how are earnings expected to change? If Age increases from
33 to 34, how are earnings expected to change?

e. Do you prefer the regression in (c) to the regression in (b)? Explain.

f. Do you prefer the regression in (d) to the regression in (b)? Explain.

g. Do you prefer the regression in (d) to the regression in (c)? Explain.

h. Plot the regression relation between Age and ln(AHE) from (b), (c),
and (d) for males with a high school diploma. Describe the similari-
ties and differences between the estimated regression functions.
Would your answer change if you plotted the regression function for
females with college degrees?

i. Run a regression of ln(AHE) on Age, Age2, Female, Bachelor,
and the interaction term Female * Bachelor. What does the coef-
ficient on the interaction term measure? Alexis is a 30-year-old
female with a bachelor’s degree. What does the regression predict