Let edu denote years of education, exper years of experience, wage denote wages measured in dollars per hour, and assume that the following model is correct: wage=B₁ + B₂edu + e where E[eledu, exper] = 0 and the error e is homoskedastic, so that Var(eledu, exper) = ². Consider two regressions: (I) A first regression estimates the given model (denote those estimates by b₁,b₂); (II) A second regression also adds exper as a regressor -- i.e. estimates wage = B₁ + B₂edu + ß3exper + e (denote those estimates by b₁,b₂, 53). Which of the following statements is true? a. The estimator b₂ may be biased (i.e. we may have E[b₂] # B₂). O b. If wage and exper are positively correlated, then E[b3] > 0. O c. Var(b₂) depends on the correlation between exper and edu (Hint: this is not asking the variance of b2.) O d. If Var(b₂) = Var(5₂), then the correlation between exper and edu must be zero. O e. The correlation between wage and exper must be equal to zero.
Let edu denote years of education, exper years of experience, wage denote wages measured in dollars per hour, and assume that the following model is correct: wage=B₁ + B₂edu + e where E[eledu, exper] = 0 and the error e is homoskedastic, so that Var(eledu, exper) = ². Consider two regressions: (I) A first regression estimates the given model (denote those estimates by b₁,b₂); (II) A second regression also adds exper as a regressor -- i.e. estimates wage = B₁ + B₂edu + ß3exper + e (denote those estimates by b₁,b₂, 53). Which of the following statements is true? a. The estimator b₂ may be biased (i.e. we may have E[b₂] # B₂). O b. If wage and exper are positively correlated, then E[b3] > 0. O c. Var(b₂) depends on the correlation between exper and edu (Hint: this is not asking the variance of b2.) O d. If Var(b₂) = Var(5₂), then the correlation between exper and edu must be zero. O e. The correlation between wage and exper must be equal to zero.
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![Let edu denote years of education, exper years of experience, wage denote wages measured in dollars per hour, and assume that the following model is correct:
wage = B1 + B2edu + e
where E[eledu, exper] = 0 and the error e is homoskedastic, so that Var(e|edu, exper) =
Consider two regressions: (I) A first regression estimates the given model (denote those estimates by b1, b2); (I) A second regression also adds exper as a regressor -- i.e.
estimates wage = ß1 + Bzedu + ßzexper + e (denote those estimates by b1, b2, b3). Which of the following statements is true?
O a.
The estimator b2 may be biased (i.e. we may have E[b2] # B2).
O b. If wage and exper are positively correlated, then E[b3] > 0.
O c. Var(b2) depends on the correlation between exper and edu (Hint: this is not asking the variance of b2.)
O d. If Var(b2) = Var(b2), then the correlation between exper and edu must be zero.
Oe.
The correlation between wage and exper must be equal to zero.
Clear my choice](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7fd47556-f3ce-4f39-818d-be563d9523c8%2F2803cd98-7af7-437d-9b58-0a421ba05e0b%2Fwepoafc_processed.png&w=3840&q=75)
Transcribed Image Text:Let edu denote years of education, exper years of experience, wage denote wages measured in dollars per hour, and assume that the following model is correct:
wage = B1 + B2edu + e
where E[eledu, exper] = 0 and the error e is homoskedastic, so that Var(e|edu, exper) =
Consider two regressions: (I) A first regression estimates the given model (denote those estimates by b1, b2); (I) A second regression also adds exper as a regressor -- i.e.
estimates wage = ß1 + Bzedu + ßzexper + e (denote those estimates by b1, b2, b3). Which of the following statements is true?
O a.
The estimator b2 may be biased (i.e. we may have E[b2] # B2).
O b. If wage and exper are positively correlated, then E[b3] > 0.
O c. Var(b2) depends on the correlation between exper and edu (Hint: this is not asking the variance of b2.)
O d. If Var(b2) = Var(b2), then the correlation between exper and edu must be zero.
Oe.
The correlation between wage and exper must be equal to zero.
Clear my choice
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