Câu hỏi: Which of the following is the most accurate definition of the term “the OLS estimator”?

A. It comprises the numerical values obtained from OLS estimation

B. It is a formula that, when applied to the data, will yield the parameter estimates

C. It is equivalent to the term “the OLS estimate”

D. It is a collection of all of the data used to estimate a linear regression model.

Câu 1: Which of the following statements is correct concerning the conditions required for OLS to be a usable estimation technique?

A. The model must be linear in the parameters

B. The model must be linear in the variables

C. The model must be linear in the variables and the parameters

D. The model must be linear in the residuals

Câu 2: What result is proved by the Gauss-Markov theorem?

A. That OLS gives unbiased coefficient estimates

B. That OLS gives minimum variance coefficient estimates

C. That OLS gives minimum variance coefficient estimates only among the class of linear unbiased estimators

D. That OLS ensures that the errors are distributed normally

Câu 3: Which of the following would you expect to be a problem associated with adding lagged values of the dependent variable into a regression equation?

A. The assumption that the regressors are non-stochastic is violated

B. A model with many lags may lead to residual non-normality

C. Adding lags may induce multicollinearity with current values of variables

D. The standard errors of the coefficients will fall as a result of adding more explanatory variables

Câu 4: Two researchers have identical models, data, coefficients and standard error estimates. They test the same hypothesis using a two-sided alternative, but researcher 1 uses a 5% size of test while researcher 2 uses a 10% test. Which one of the following statements is correct?

A. Researcher 2 will use a larger critical value from the t-tables

B. Researcher 2 will have a higher probability of type I error

C. Researcher 1 will be more likely to reject the null hypothesis

D. Both researchers will always reach the same conclusion

Câu 5: Consider a standard normally distributed variable, a t-distributed variable with d degrees of freedom, and an F-distributed variable with (1, d) degrees of freedom. Which of the following statements is FALSE?

A. The standard normal is a special case of the t-distribution, the square of which is a special case of the F-distribution

B. Since the three distributions are related, the 5% critical values from each will be the same

C. Asymptotically, a given test conducted using any of the three distributions will lead to the same conclusion

D. The normal and t- distributions are symmetric about zero while the F- takes only positive values

Câu 6: Consider an increase in the size of the test used to examine a hypothesis from 5% to 10%. Which one of the following would be an implication?

A. The probability of a Type I error is increased

B. The probability of a Type II error is increased

C. The rejection criterion has become more strict

D. The null hypothesis will be rejected less often