Câu hỏi: Under the five extended least squares assumptions, the homoskedasticity-only tdistribution in this chapter:

A. has a Student t distribution with n-2 degrees of freedom

B. has a normal distribution

C. has a Student t distribution with n degrees of freedom

Câu 1: If the errors are heteroskedastic, then:

A. the OLS estimator is still BLUE as long as the regressors are nonrandom

B. the usual formula cannot be used for the OLS estimator

C. your model becomes overidentified

D. the OLS estimator is not BLUE

Câu 2: The EG-ADF test:

A. Is the similar to the DF-GLS test

B. Is a test for cointegration

C. Has as a limitation that it can only test if two variables, but not more than two, are cointegrated

D. Uses the ADF in the second step of its procedure

Câu 3: The advantage of using heteroskedasticity-robust standard errors is that:

A. that they are easier to compute than the homoskedasticity-only standard errors

B. they produce asymptotically valid inferences even if you do not know the form of the conditional variance function.

C. it makes the OLS estimator BLUE, even in the presence of heteroskedasticity

D. they do not unnecessarily complicate matters, since in real-world applications, the functional form of the conditional variance can easily be found

Câu 4: ARCH and GARCH models are estimated using the:

A. OLS estimation method

B. the method of maximum likelihood

C. DOLS estimation method

D. VAR specification

Câu 5: Trong kiểm định Lagrange để phát hiện mô hình hồi quy bị thiếu biến ta phải tính qs2 . Nếu qs2 =nR2>χα(1) thì kết luận mô hình thiếu biến. Các kết luận sau, kết luận nào đúng?

A. Nếu qs2 =nR2>χα(1) thì kết luận mô hình thiếu biến

B. Nếu qs2 =nR2>χα(1) thì kết luận mô hình không thiếu biến

C. Nếu qs2 =nR2>χα(2) thì kết luận mô hình thiếu biến

D. Nếu qs2 =nR2>χα(2) thì kết luận mô hình không thiếu biến

Câu 6: The order of integration:

A. can never be zero

B. is the number of times that the series needs to be differenced for it to be stationary

C. is the value of \({\phi _1}\) in the quasi difference \(\Delta {Y_t} – {\phi _1}{Y_{t – 1}}\)

D. depends on the number of lags in the VAR specification