Stationarity means that the
A) error terms are not correlated.
B) probability distribution of the time series variable does not change over time.
C) time series has a unit root.
D) forecasts remain within 1.96 standard deviation outside the sample period.
Correct Answer:
Verified
Q2: An autoregression is a regression
A)of a dependent
Q3: Autoregressive distributed lag models include
A)current and lagged
Q4: Pseudo out of sample forecasting can be
Q5: Time series variables fail to be stationary
Q6: The root mean squared forecast error
Q8: The time interval between observations can be
Q9: In order to make reliable forecasts with
Q10: The first difference of the logarithm of
Q11: The forecast is
A)made for some date beyond
Q12: Negative autocorrelation in the change of a
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