Earnings functions attempt to find the determinants of earnings, using both continuous
and binary variables.One of the central questions analyzed in this relationship is the
returns to education.
(a)Collecting data from 253 individuals, you estimate the following relationship $\begin{aligned}
\widehat{\ln \left(\text { Earn }_{i}\right)}= & 0.54+0.083 \times E d u c, R^{2}=0.20, S E R=0.445 \
& (0.14)(0.011)
\end{aligned}$ where Earn is average hourly earnings and Educ is years of education.
What is the effect of an additional year of schooling? If you had a strong belief that years
of high school education were different from college education, how would you modify
the equation? What if your theory suggested that there was a "diploma effect"?

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The Answer of Earnings functions attempt to find the determinants of earnings, using both continuous
and binary variables.One of the central questions analyzed in this relationship is the
returns to education.
(a)Collecting data from 253 individuals, you estimate the following relationship $\begin{aligned}
\widehat{\ln \left(\text { Earn }_{i}\right)}= & 0.54+0.083 \times E d u c, R^{2}=0.20, S E R=0.445 \
& (0.14)(0.011)
\end{aligned}$ where Earn is average hourly earnings and Educ is years of education.
What is the effect of an additional year of schooling? If you had a strong belief that years
of high school education were different from college education, how would you modify
the equation? What if your theory suggested that there was a "diploma effect"?