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实时资讯全掌握
The table below shows the autocorrelations of the lagged residuals for the first differences of the natural logarithm of quarterly motorcycle sales that were fit to the AR(1) model: (ln salest − ln salest − 1) = b0 + b1(ln salest − 1 − ln salest − 2) + εt. The critical t-statistic at 5% significance is 2.0, which means that there is significant autocorrelation for the lag-4 residual, indicating the presence of seasonality. Assuming the time series is covariance stationary, which of the following models is most likely to CORRECT for this apparent seasonality?
A. ln salest = b0 + b1(ln salest − 1) − b2(ln salest − 4) + εt. B. (ln salest − ln salest − 1) = b0 + b1(ln salest − 1 − ln salest − 2) + b2(ln salest − 4 − ln salest − 5) + εt. C. (ln salest − ln salest − 4) = b0 + b1(ln salest − 1 − ln salest − 2) + εt. | ||||||||||||||||||||||||