Câu hỏi: 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 1: 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 2: Suppose that we wanted to sum the 2007 returns on ten shares to calculate the return on a portfolio over that year. What method of calculating the individual stock returns would enable us to do this?

A. Simple

B. Continuously compounded

C. Neither approach would allow us to do this validly

D. Either approach could be used and they would both give the same portfolio return

Câu 3: The numerical score assigned to the credit rating of a bond is best described as what type of number?

A. Continuous

B. Cardinal

C. Ordinal

D. Nominal

Câu 4:  Which of the following is NOT a good reason for including lagged variables in a regression?

A. Slow response of the dependent variable to changes in the independent variables

B. Over-reactions of the dependent variables

C. The dependent variable is a centred moving average of the past 4 values of the series

D. The residuals of the model appear to be non-normal

Câu 5: 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 6: Which of the following would NOT be a potential remedy for the problem of multicollinearity between regressors?

A. Removing one of the explanatory variables

B. Transforming the data into logarithms

C. Transforming two of the explanatory variables into ratios

D. Collecting higher frequency data on all of the variables