Question

a) Suppose that wage is determined by the following true population model that satisfies the assumptions for the MLR model. wage=βo +β1edu+β2abil+u

where β2 > 0 and abil = γ0 +γ1edu+w, γ1 > 0. As abil is not observed, the following model is estimated instead

wage=αo +α1edu+v whereu,v,andwareerrorterms. ShowthatE[αˆ]>β andE[αˆ]>β .

(b) Consider the model:

log(wage) = β0 + β1female + β2exper + β3female ∗ exper + u

where exper is the years of work experience, and female is a dummy vari- able (1 if the person is female, and 0 otherwise). How would you calculate the difference in the return of experience between males and females in this model?

(c) Consider the model:

yt =α0 +β0xt +β1xt−1 +β2xt−2 +β3xt−3 +ut

Given a permanent increase in x, how would you measure the long run effect on y?

Answer #1

Suppose you want to investigate the differences in earnings
between men and women. Consider the following model:
ln(WAGE) = β1 + β2 EDUC + β3 EXPER + β4 MALE + β5 (EDUC*MALE) +
β6 (EXPER*MALE) + e
where EDUC = years of education, EXPER = years of work
experience, and MALE = an indicator variable that = 1 for males and
= 0 for females. Then the effect of being male (select the best
answer)
a) depends on the male’s...

The following model has been estimated using a large company's
human resource date:
log(wage) = 1.439 + 0.0834 x edu + 0.0512 x
exper + 0.1932 x male
where wage is hourly wage, edu is years of
schooling, exper is years of relevant work experience, and
male is a dummy variable for male
(i) How much more do men at the firm earn than women, on
average?
(ii) How much per hour will a fresh male college graduate (16
years...

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