1.
Suppose the variable x2 has been omitted from the following regression equation, y = β0 + β1x1 +β2x2 + u. b1 is the estimator obtained when x2 is omitted from the equation. The bias in b1 is positive if
A. |
β2<0 and x1 and x2 are positive correlated |
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B. |
β2=0 and x1 and x2 are negative correlated |
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C. |
β2>0 and x1 and x2 are negative correlated |
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D. |
β2>0 and x1 and x2 are positive correlated |
2.
Suppose the true population model of y is given by y=β0+β1x1+β2x2+β3x3+u. Which of the following will lead to a higher variance of the OLS estimator on x3.
(i) A smaller sample size
(ii) Greater variation in x3
(iii) Greater variation in u
(iv) Higher correlation between x1 and x2
(v) Higher correlation between x1 and x3
A. |
(i), (iii) and (v) only |
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B. |
(i), (ii), (iii), (iv), and (v) |
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C. |
(ii) and (v) only |
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D. |
(i), (ii), (iii), and (v) only |
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