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Why I ncludinh too few lags of dependent variable in time series will casue seriel correlation?

Why I ncludinh too few lags of dependent variable in time series will casue seriel correlation?
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Distributed slack model is a model for time arrangement information in which a relapse condition is utilized to foresee current estimations of a needy variable dependent on both the present estimations of an illustrative variable and the slacked (past period) estimations of this logical variable.

Autocorrelation (also called serial correlation) occurs when the error term observations in a regression are correlated. The theoretical error term "e" is a random variable that is part of the regression model, even before it is estimated. This error term represents a random “shock” to the model, or something that is missing from the model. However, we can never see the actual error term "e".

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