A measure of first-order autocorrelation; that is, of autocorrelation in time series where independent variables are not lagged.
The Durbin-Watson statistic lies in the range 0-4. A value of 2 or nearly 2 indicates that there is no first-order autocorrelation. An acceptable range is 1.50 - 2.50. Where successive error differences are small, Durbin-Watson is low (less than 1.50); this indicates the presence of positive autocorrelation. Positive autocorrelation is very common. Where successive error differences are large, Durbin-Watson is high (more than 2.50); this indicates the presence of negative autocorrelation. Negative autocorrelation is not particularly common.
If the Durbin-Watson statistic is greater than R square, it is likely that autocorrelation exists. Autocorrelation indicates that the forecast model could be improved on.
In time series with lagged variables, the Durbin-Watson statistic is unreliable as it tends toward a value of 2.0.
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