(25 pts.) Earnings functions attempt to nd the determinants of earnings, using both continuous and binary variables. One of the central questions analyzed in this relationship is the returns to education. 1.] Collecting data from 253 individuals, you estimate the following relationship inEEnF 0.54 + 0.083 x Educ, R2= 0.20, SER = 0.445 (0.14) (0.011) where Earn is average hourly earnings and Educ is years of education. a. What is the effect of an additional year of schooling? (3 pts.) 1.2 You read in the literature that there should also be returns to on-the-job training. To approximate on-the-j ob training, researchers often use the so-called Mincer or potential experience variable, which is dened as Exper = Age ~ Educ 6. 3. Explain the reasoning behind this approximation (i.e. Exper = Age Educ - 6). (3 pts.) You incorporate the experience variable into your original regression 111%; -0.01 + 0.101 x Educ + 0.033 x Exper 0.0005 x Experz , (0.16) (0.012) (0.006) (0.0001) R2 = 0.34, SER = 0.405 b. Is the effect of an additional year of experience on earnings constant regardless of the value of the years of experience? Explain. (3 pts.) 0. What is the effect of an additional year of experience for a person who is 40 years old and had 12 years of education? (3 pts.)