Multiple Choice
By including another variable in the regression, you will
A) decrease the regression R2 if that variable is important.
B) eliminate the possibility of omitted variable bias from excluding that variable.
C) look at the t-statistic of the coefficient of that variable and include the variable only if the coefficient is statistically significant at the 1% level.
D) decrease the variance of the estimator of the coefficients of interest.
Correct Answer:

Verified
Correct Answer:
Verified
Q37: In the case of errors-in-variables bias,<br>A)maximum likelihood
Q38: Simultaneous causality<br>A)means you must run a second
Q39: Consider a situation where Y is
Q40: One of the most frequently used
Q41: Sir Francis Galton (1822-1911), an anthropologist
Q43: Keynes postulated that the marginal propensity
Q44: Your textbook uses the following example
Q45: Correlation of the regression error across observations<br>A)results
Q46: Several authors have tried to measure
Q47: Errors-in-variables bias<br>A)is present when the probability