One reason for computing the logarithms (ln) , or changes in logarithms, of economic time series is that
A) numbers often get very large.
B) economic variables are hardly ever negative.
C) they often exhibit growth that is approximately exponential.
D) natural logarithms are easier to work with than base 10 logarithms.
Correct Answer:
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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
Q13: The Granger Causality Test
A)uses the F-statistic to
Q14: The Times Series Regression with Multiple Predictors
A)is
Q16: One of the sources of error in
Q17: The jth autocorrelation coefficient is defined
Q18: The ADL(p,q)model is represented by the following
Q19: The AR(p)model
A)is defined as Yt = β0
Q20: Departures from stationarity
A)jeopardize forecasts and inference based
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