Quiz #8-S3

# The approximate difference δ between the earnings of

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10. The approximate difference ( Δ ) between the earnings of individuals whose look are rated “homely” and individuals whose looks are rated “average” is (in percentage terms):
Economics 420 (section 3) Professor Woodbury Fall Semester 2016 Answers to Quiz #8 10. E See the next page for answers to questions 6, 7, and 8.
Answers to 6, 7, and 8: ln( wage ) is quadratic in experience, so take the derivative of ln( wage ) with respect to exper : ln( wage ) = β 0 + β 1 educ + β 2 exper + β 3 exper 2 + u so ln( wage )/ exper = β 2 + 2 β 3 exper Plugging in the estimates for β 2 and β 3 gives ln( wage )/ exper = 0.0485 + 2(–0.0007) exper #6 asks for the expected change in earnings [ Δ ln( wage )] associated with 1 additional year of experience for someone who has no experience (that is, exper = 0). So set exper = 0 in the equation for ln( wage )/ exper : ln( wage )/ exper = 0.0485 + 2(–0.0007)(0) ln( wage )/ exper = 0.0485 or 4.85% #7 asks for the expected change in earnings [ Δ ln( wage )] associated with 1 additional year of experience for someone who has 25 years of experience (that is, exper = 25). So set exper = 25 in the equation for log(wage)/ exper : log(wage)/ exper = 0.0485 + 2(–0.0007)(25) log(wage)/ exper = 0.0485 – 0.035 = 0.0135 or 1.35% #8 asks for the turning point in the wage-experience profile, so set ln( wage )/ exper = 0 and solve for exper *: ln( wage )/ exper = 0.0485 + 2(–0.0007)( exper ) = 0 => 0.0485 =(0.0014)( exper *) => exper * = 34.6 So the wage experience profile increases for 34.6 years, reaches a maximum, then turns down. For more on quadratic relationships, see section 3 of <18,19-model specification.pdf>, and/or section 6.2 of Wooldridge.
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