Câu hỏi: 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 1: Which criticism of Dickey-Fuller (DF) -type tests is addressed by stationarity tests, such as the KPSS test?

A. DF tests have low power to reject the null hypothesis of a unit root, particularly in small samples

B.  DF tests are always over-sized

C. DF tests do not allow the researcher to test hypotheses about the cointegrating vector

D. DF tests can only find at most one cointegrating relationship

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 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 4: 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 5: A process, xt, which has a constant mean and variance, and zero autocovariance for all non-zero lags is best described as:

A. A white noise process

B. A covariance stationary process

C. An autocorrelated process

D. A moving average process

Câu 6: 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