Câu hỏi: 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 1: 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 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: 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

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 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 6: 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