Answer Happy

You believe that the relationship between earnings and age is nonlinear. You estimate the following three polynomial regression models, controlling for the effect of gender by using a binary variable that takes on the value of one for females and is zero otherwise: Earn Earn – 795.90 + 82.93 x Age – 1.69 x Age? + 0.015 ~ Age + 0.0005 * Age+ – 163.19 x Female (283.11) (29.29) (1.06) (0.016) (0.0009) (12.45) –683.21 + 65.83 x Age – 1.05 * Age+ 0.005 * Age 163.23 x Female (120.13) (9.27) (0.22) (0.002) (12.45) -344.88 + 41.48 x Age – 0.45 x Age– 163.81 ~ Female (51.58) (2.64) (12.47) Earn (0.03)
(e) Are you concerned about the negative coefficient on the regression intercept in all the three polynomial regressions? (f) Suppose that we only consider the quadratic regression. Someone concerns the nonlinearity of not only the age variable, but also the female variable. Thus, in the quadratic regression, she adds the square term of female. That is, she is running the following regression: Earn; = Bo+By Age + B2 Age? +B3Female; + B4Female+ ui Is there anything wrong with this model specification?