In the case of errors-in-variables bias,
A. maximum likelihood estimation must be used.
B. the OLS estimator is consistent if the variance in the unobservable variable is relatively large compared to variance in the measurement error.
C. the OLS estimator is consistent, but no longer unbiased in small samples.
D. binary variables should not be used as independent variables.
查看答案
Sample selection bias occurs when
A. the choice between two samples is made by the researcher.
B. data are collected from a population by simple random sampling.
C. samples are chosen to be small rather than large.
D. the availability of the data is influenced by a selection process that is related to the value of the dependent variable.
Simultaneous causality
A. means you must run a second regression of X on Y.
B. leads to correlation between the regressor and the error term.
C. means that a third variable affects both Y and X.
D. cannot be established since regression analysis only detects correlation between variables.
Correlation of the regression error across observations
A. results in incorrect OLS standard errors.
B. makes the OLS estimator inconsistent, but not unbiased.
C. results in correct OLS standard errors if heteroskedasticity-robust standard errors are used.
D. is not a problem in cross-sections since the data can always be "reshuffled."
The guidelines for whether or not to include an additional variable include all of the following, with the exception of
A. providing "full disclosure" representative tabulations of the results.
B. testing whether additional questionable variables have nonzero coefficients.
C. determining whether it can be measured in the population of interest.
D. being specific about the coefficient or coefficients of interest.
微信支付 
支付宝支付