Câu hỏi: 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 1: 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 2: 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 3: A normal distribution has coefficients of skewness and excess kurtosis which are respectively:

A. 0 and 0

B. 0 and 3

C. 3 and 0

D. Will vary from one normal distribution to another

Câu 4: If a regression equation contains an irrelevant variable, the parameter estimates will be

A. Consistent and unbiased but inefficient

B. Consistent and asymptotically efficient but biased

C. Inconsistent

D. Consistent, unbiased and efficient

Câu 5: 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 6: Consider the following picture and suggest the model from the following list that best characterises the process:

A. An AR(1)

B. An AR(2)

C. An ARMA(1,1)

D. An MA(3)