# Some Multiple Choice Questions (MCQs) on Autocorrelation in Econometrics

**1. Autocorrelation refers to:**

a) Correlation between two variables

b) Correlation between a variable and its lagged values

c) Correlation between two different time series

d) Correlation between two different populations

Answer: b) Correlation between a variable and its lagged values

**2. What is the range of values that** **the** **autocorrelation coefficient can take?**

a) -1 to 0

b) 0 to 1

c) -1 to 1

d) 0 to infinity

Answer: c) -1 to 1

**3. In a time series plot, if the data points appear to be randomly scattered, then the autocorrelation is:**

a) High

b) Low

c) Cannot be determined from time series plot

d) None of the above

Answer: b) Low

**4. Which of the following can be used to test the null hypothesis of no autocorrelation?**

a) Box-Ljung test

b) Student's t-test

c) Chi-square test

d) ANOVA

Answer: a) Box-Ljung test

**5. In a time series plot, if the data points show a periodic pattern, then the autocorrelation is:**

a) High

b) Low

c) Cannot be determined from time series plot

d) None of the above

Answer: a) High

**6. Which of the following is a possible cause of autocorrelation in time series data?**

a) Seasonality

b) Trend

c) Measurement error

d) All of the above

Answer: d) All of the above

**7. What does a positive autocorrelation coefficient indicate?**

a) There is a positive association between the variable and its lagged values

b) There is a negative association between the variable and its lagged values

c) There is no association between the variable and its lagged values

d) The variable is not stationary

Answer: a) There is a positive association between the variable and its lagged values

**8. What does a negative autocorrelation coefficient indicate?**

a) There is a positive association between the variable and its lagged values

b) There is a negative association between the variable and its lagged values

c) There is no association between the variable and its lagged values

d) The variable is not stationary

Answer: b) There is a negative association between the variable and its lagged values

**9. Which of the following is true about autocorrelation in a stationary time series?**

a) The autocorrelation coefficient is constant for all lags

b) The autocorrelation coefficient decreases as the lag increases

c) The autocorrelation coefficient increases as the lag increases

d) The autocorrelation coefficient is zero for all lags

Answer: a) The autocorrelation coefficient is constant for all lags

**10. Which of the following methods can be used to remove autocorrelation from a time series?**

a) Differencing

b) Smoothing

c) Regression

d) All of the above

Answer: a) Differencing