Câu hỏi: What is the optimal three-step ahead forecast from the AR(2) model given in question 14?

A. -0.1

B. 0.27

C. -0.34

D. -0.31

Câu 1: If a series, yt, follows a random walk (with no drift), what is the optimal 1-step ahead forecast for y?

A. The current value of y

B. Zero

C. The historical unweighted average of y

D. An exponentially weighted average of previous values of y

Câu 2: Which of the following would probably NOT be a potential “cure” for non-normal residuals?

A. Transforming two explanatory variables into a ratio

B. Removing large positive residuals

C. Using a procedure for estimation and inference which did not assume normality

D. Removing large negative residuals

Câu 3: If the number of non-zero eigenvalues of the pi matrix under a Johansen test is 2, this implies that

A. There are 2 linearly independent cointegrating vectors

B. There are at most 2 linearly independent cointegrating vectors

C. There are 3 variables in the system

D. There are at least 2 linearly independent cointegrating vectors

Câu 4: If the residuals of a model containing lags of the dependent variable are autocorrelated, which one of the following could this lead to?

A. Biased but consistent coefficient estimates

B. Biased and inconsistent coefficient estimates

C. Unbiased but inconsistent coefficient estimates

D. Unbiased and consistent but inefficient coefficient estimates

Câu 5: If a Johansen “max” test for a null hypothesis of 1 cointegrating vectors is applied to a system containing 4 variables is conducted, which eigenvalues would be used in the test?

A. The largest 1

B. The Second largest

C. The Second smallest

D. The smallest

Câu 6: Consider a series that follows an MA(1) with zero mean and a moving average coefficient of 0.4. What is the value of the autocorrelation function at lag 1?

A. 0.4

B. 0.34

C. 1

D. It is not possible to determine the value of the autocovariances without knowing the disturbance variance