Câu hỏi: 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

Câu 1: 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 2: If there are three variables that are being tested for cointegration, what is the maximum number of linearly independent cointegrating relationships that there could be?

A. 0

B. 1

C. 2

D. 3

Câu 3: 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 4: What would be the consequences for the OLS estimator if autocorrelation is present in a regression model but ignored?

A. It will be biased

B. It will be inconsistent

C. It will be inefficient

D. All of a, b and c will be true

Câu 5: 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 6: Which of the following conditions must hold for the autoregressive part of an ARMA model to be stationary?

A. All roots of the characteristic equation must lie outside the unit circle

B. All roots of the characteristic equation must lie inside the unit circle

C. All roots must be smaller than unity

D. At least one of the roots must be bigger than one in absolute value