(c) You recall from your textbook that additional years of experience are supposed to result in higher earnings. You reason that this is because experience is related to "on the job training." One frequently used measure for (potential) experience is "Age-Education-6." Explain the underlying rationale. Assuming, heroically, that education is constant across the 1,744 individuals, you consider regressing earnings on age and a binary variable for gender. You estimate two specifications initially:

= 323.70 + 5.15 Age - 169.78 Female, R2 = 0.13, SER=274.75

(21.18) (0.55) (13.06)

= 5.44 + 0.015 Age - 0.421 Female, R2 = 0.17, SER = 0.75

(0.08) (0.002) (0.036)

where Earn are weekly earnings in dollars, Age is measured in years, and Female is a binary variable, which takes on the value of one if the individual is a female and is zero otherwise. Interpret each regression carefully. For a given age, how much less do females earn on average? Should you choose the second specification on grounds of the higher regression R2?