Let$$s return to the wage determination example of Section $1\mathrm{.}2.$ In that example, we built a model of the wage of the ith worker in a particu$-$ lar field as a function of the work experience, education, and gender of that worker:

where:

WAGEi $=$ $0+$ $1$EXPi $+$ $2$EDUi $+$ $3$GENDi $+$ ei $(1\mathrm{.}10)$

Yi $=$ WAGEi $=$ the wage of the ith worker

X$1$i $=$ EXPi $=$ the years of work experience of the ith worker X$2$i $=$ EDUi $=$ the years of education beyond high school

of the ith worker

X$3$i $=$ GENDi $=$ the gender of the ith worker $(1=$ male and

$0=$ female$)$

a$.$ What is the real$-$world meaning of $2?($Hint: If you$$re unsure where to start, review Section $1\mathrm{.}2.)$ c$.$ Suppose that you wanted to add a variable to this equation to mea$-$ sure whether there might be discrimination against people of color. How would you define such a variable? Be specific.

d$.$ Suppose that you had the opportunity to add another variable to the equation. Which of the following possibilities would seem best? Explain your answer.

the age of the ith worker

the number of jobs in this field

the average wage in this field

the number of $$employee of the month$$ awards won by the ith

worker

the number of children of the ith worke

b$.$ What is the real$-$world meaning of $3?($Hint: Remember that GEND is a dummy variable.$)$