Exam Prep | Regression With Time-Series Data – Ch.12

File: Chapter 12 – Regression with Time-Series Data: Nonstationary Variables

Multiple Choice

1. How do you find the first difference in?

a.

b.

c.

d.

2. Which of the following is NOT a necessary condition for a variable to be stationary?

a.

b.

c.

d.

3. A stochastic process is best described as _____.

a. deterministic

b. theoretical

c. random

d. mean reverting

4. Which non-stationary time series has a constant mean but non-constant variance?

a. Random walk

b. AR(1) with linear trend

c. Random walk with drift

d. Deterministic trend

5. What is a spurious regression?

a. Statistically significant but meaningless results generated by regression analysis of non-stationary data

b. The results generated by regression analysis of a station variable dependent on a non-stationary series

c. Regression analysis where endogenous and exogenous variables are reversed

d. Regression analysis that is impossible due to lack of identification

6. What is the null hypothesis of the Dickey-Fuller Test for testing with no constant and no trend?

a.

b.

c.

d.

7. What is the null hypothesis of the Dickey-Fuller Test for testing with a constant but no trend?

a.

b.

c.

d.

8. What is the null hypothesis of the Dickey-Fuller Test for testing with a constant and a trend?

a.

b.

c.

d.

9. What is the alternative hypothesis of the Dickey-Fuller Test for testing with no constant and no trend?

a.)

b.)

c.)

d.)

10. What is the alternative hypothesis of the Dickey-Fuller Test for testing with a constant but no trend?

a.

b.

c.

d.

11. What is the alternative hypothesis of the Dickey-Fuller Test for testing with a constant and a trend?

a.

b.

c.

d.

12. Why should augmented Dickey-Fuller tests always be used when performing econometric analysis?

a. The augmented tests allow for more degrees of freedom.

b. So that we can test hypotheses using a t-distribution.

c. Because no assumptions about the sign of are needed to perform a one- tailed test.

d. To confirm that error terms are not autocorrelated.

13. What does it mean for a series to have a unit root?

a. It has a constant mean equal to 1.

b. It has a constant variance equal to 1.

c. It has a stochastic trend and is nonstationary.

d. It is integrated of order 1.

14. The minimum number of times a series must be differenced to generate a stationary series is the _____.

a. unit root

b. order of integration

c. trend coefficient

d. spurious regression degree

15. If series y and z have similar stochastic trends, but are otherwise unrelated, they are said to be _____.

a. cointegrated

b. cotrending

c. converging

d. jointly stationary

16. How do you check for cointegration of two series?

a. Estimate a regression of one series as a function of the other, then perform an augmented Dickey-Fuller test on estimated residuals.

b. Estimate a regression of one as a function of the other and test the significance of the parameter estimates.

c. Test the significance of the covariance between the two series.

d. Subtract one series from the other and check for stationarity of the difference.

17. An ARDL model with nonstationary variables is _____.

a. an error correction model

b. a VEC

c. a VAR

d. a variance decomposition

18. Which of the following is a common way to convert a series with a stochastic trend to a stationary series?

a. First differencing

b. Cointegrating

c. Running a spurious regression

d. Estimating distributed lags

19. Which of the following is a common way to convert a series with a deterministic trend to a stationary series?

a. Detrending

b. Autoregression

c. Estimating distributed lags

d. Cointegrating

20. Suppose you have two series that you have tested and have found them to be cointegrated. You are interested in explaining the dynamics of the relative short- run movements of the series. Which of the following estimation choices should you use?

a. An ARDL model in levels

b. A simple regression model with least squares

c. An error-correction model

d. An ARDL model in first-differences

21. Suppose you have two series that you have tested and have found to contain a stochastic trend but failed to find any evidence that they are cointegrated. Which of the following estimation choices should you use?

a. An ARDL model in levels

b. A simple regression model with least squares

c. An error-correction model

d. An ARDL model in first-differences