If you had a two regressor regression model, then omitting one variable which is relevant
A) will have no effect on the coefficient of the included variable if the correlation between the excluded and the included variable is negative.
B) will always bias the coefficient of the included variable upwards.
C) can result in a negative value for the coefficient of the included variable, even though the coefficient will have a significant positive effect on Y if the omitted
Variable were included.
D) makes the sum of the product between the included variable and the residuals different from 0.
Correct Answer:
Verified
Q1: You have to worry about perfect multicollinearity
Q2: Q2: In the multiple regression model, the least Q3: When you have an omitted variable Q5: (Requires Calculus) In the multiple regression Q6: Under the least squares assumptions for Q9: Omitted variable bias a. will always Q12: One of the least squares assumptions in Q13: Under imperfect multicollinearity Q17: The OLS residuals in the multiple regression
A)the OLS estimator cannot be
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