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
Q2: The components of internal validity are
A)a large
Q3: Applying the analysis from the California test
Q7: Misspecification of functional form of the regression
Q9: A study based on OLS regressions is
Q11: The reliability of a study using multiple
Q11: In the case of a simple regression,where
Q13: The analysis is externally valid if
A)the statistical
Q15: Comparing the California test scores to test
Q19: Panel data estimation can sometimes be used
A)to
Q20: In the case of errors-in-variables bias,
A)maximum likelihood
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