180 câu trắc nghiệm Kinh tế lượng – Phần 3

Chapter 9: Assessing Studies Based on Multiple Regression

KTL_001_C9_1: 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
● errors-in-variables bias.
○ sample selection bias.
○ simultaneous causality bias.
○ companies that typically bargain with workers in 100s of dollars.

KTL_001_C9_2: In the case of a simple regression, where the independent variable is measured with i.i.d. error,
● \({{\hat \beta }_1} \to \frac{{\sigma _x^2}}{{\sigma _x^2 + \sigma _w^2}}{\beta _1}\)
○ \({{\hat \beta }_1} \to \frac{{\sigma _x^2}}{{\sigma _x^2 + \sigma _w^2}}\)
○ \({{\hat \beta }_1} \to \frac{{\sigma _w^2}}{{\sigma _x^2 + \sigma _w^2}}{\beta _1}\)
○ \({{\hat \beta }_1} \to {\beta _1} + \frac{{\sigma _x^2}}{{\sigma _x^2 + \sigma _w^2}}\)

KTL_001_C9_3: In the case of errors-in-variables bias,
○ maximum likelihood estimation must be used.
● the OLS estimator is consistent if the variance in the unobservable variable is relatively large compared to variance in the measurement error.
○ the OLS estimator is consistent, but no longer unbiased in small samples.
○ binary variables should not be used as independent variables.

KTL_001_C9_4: Comparing the California test scores to test scores in Massachusetts is appropriate for external validity if
○ Massachusetts also allowed beach walking to be an appropriate P.E. activity.
○ the two income distributions were very similar.
○ the student-to-teacher ratio did not differ by more than five on average.
● the institutional settings in California and Massachusetts, such as organization in classroom instruction and curriculum, were similar in the two states.

KTL_001_C9_5: In the case of errors-in-variables bias, the precise size and direction of the bias depend on
○ the sample size in general.
● the correlation between the measured variable and the measurement error.
○ the size of the regression \({R^2}\) .
○ whether the good in question is price elastic.

KTL_001_C9_6: The question of reliability/unreliability of a multiple regression depends on
○ internal but not external validity
○ the quality of your statistical software package
● internal and external validity
○ External but not internal validity

KTL_001_C9_7: A statistical analysis is internally valid if
○ all t-statistics are greater than |1.96|
○ the regression \({R^2}\) > 0.05
○ the population is small, say less than 2,000, and can be observed
● the statistical inferences about causal effects are valid for the population studied

KTL_001_C9_8: Internal validity is that
● the estimator of the causal effect should be unbiased and consistent
○ the estimator of the causal effect should be efficient
○ inferences and conclusions can be generalized from the population to other populations
○ OLS estimation has been used in your statistical package

KTL_001_C9_9: Threats to internal validity lead to
○ perfect multicollinearity
○ the inability to transfer data sets into your statistical package
● failures of one or more of the least squares assumptions
○ a false generalization to the population of interest

KTL_001_C9_10: The true causal effect might not be the same in the population studied and the population of interest because
○ of differences in characteristics of the population
○ of geographical differences
○ the study is out of date
● all of the above