Misspecification of functional form of the regression function
A. is overcome by adding the squares of all explanatory variables.
B. is more serious in the case of homoskedasticity-only standard error.
C. results in a type of omitted variable bias.
D. requires alternative estimation methods such as maximum likelihood.
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Errors-in-variables bias
A. is only a problem in small samples.
B. arises from error in the measurement of the independent variable.
C. becomes larger as the variance in the explanatory variable increases relative to the error variance.
D. is particularly severe when the source is an error in the measurement of the dependent variable.
A survey of earnings contains an unusually high fraction of individuals who state their weekly earnings in 100s, such as 300, 400, 500, etc. This is an example of
A. errors-in-variables bias.
B. sample selection bias.
C. simultaneous causality bias.
D. companies that typically bargain with workers in 100s of dollars.
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.
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.
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