Q6. Is the time series of WPM covariance stationary?

A)   Yes, because the computed t-statistic for a slope of 1 is significant.

B)   Yes, because the computed t-statistic for a slope of 1 is not significant.

C)   No, because the computed t-statistic for a slope of 1 is not significant.

Q7. The above model was specified as a(n):

A)   Moving Average (MA) Model.

B)   Autoregressive (AR) Model with a seasonal lag.

C)   Autoregressive (AR) Model.

Q8. Based upon the information provided, Morris would get more meaningful statistical results by:

A)   first differencing the data.

B)   adding more lags to the model.

C)   doing nothing. No information provided suggests that any of these will improve the specification.

答案和详解如下：

Q6. Is the time series of WPM covariance stationary?

A)   Yes, because the computed t-statistic for a slope of 1 is significant.

B)   Yes, because the computed t-statistic for a slope of 1 is not significant.

C)   No, because the computed t-statistic for a slope of 1 is not significant.

Correct answer is C)

The t-statistic for the test of the slope equal to 1 is computed by subtracting 1.0 from the coefficient, 1.3759 [= (1.0926 − 1.0) / 0.0673], which is not significant at the 5% level. The time series has a unit root and is not covariance stationary.

Q7. The above model was specified as a(n):

A)   Moving Average (MA) Model.

B)   Autoregressive (AR) Model with a seasonal lag.

C)   Autoregressive (AR) Model.

Correct answer is C)

The model is specified as an AR Model, but there is no seasonal lag. No moving averages are employed in the estimation of the model.

Q8. Based upon the information provided, Morris would get more meaningful statistical results by:

A)   first differencing the data.

B)   adding more lags to the model.

C)   doing nothing. No information provided suggests that any of these will improve the specification.

Correct answer is A)

Since the coefficient on the slope coefficient is greater than one, the process is not covariance stationary. A common technique to correct for this is to first difference the variable to perform the following regression: Δ(WPM)_t = b_o + b₁ Δ(WPM)_t-1 + ε _t.

thanx