Thi thử bài tập trắc nghiệm ôn tập Kinh tế lượng online - Đề #5

Danh sách câu hỏi

1. Câu 1:

   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

2. 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

3. Câu 3:

   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

4. Câu 4:

   If a residual series is negatively autocorrelated, which one of the following is the most likely value of the Durbin Watson statistic?

   • A. Close to zero
   • B. Close to two
   • C. Close to four
   • D. Close to one

5. Câu 5:

   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

6. Câu 6:

   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

7. Câu 7:

   Which of the following sets of characteristics would usually best describe an autoregressive process of order 3 (i.e. an AR(3))?

   • A. A slowly decaying acf, and a pacf with 3 significant spikes
   • B. A slowly decaying pacf and an acf with 3 significant spikes
   • C. A slowly decaying acf and pacf
   • D.  An acf and a pacf with 3 significant spikes

8. Câu 8:

   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

9. Câu 9:

   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

10. Câu 10:

    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

11. Câu 11:

    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

12. Câu 12:

    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

13. Câu 13:

    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

14. Câu 14:

    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)

15. Câu 15:

    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

16. Câu 16:

    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

17. Câu 17:

     Which one of the following best describes most series of asset prices?

    • A. An independently and identically distributed (iid, i.e. “completely random”) process
    • B. A random walk with drift
    • C. An explosive process
    • D. A deterministic trend process

18. Câu 18:

    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

19. Câu 19:

    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

20. Câu 20:

    If a Johansen “max” test for a null hypothesis of 1 cointegrating vectors is applied to a system containing 4 variables is conducted, which eigenvalues would be used in the test?

    • A. The largest 1
    • B. The Second largest
    • C. The Second smallest
    • D. The smallest