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We show that the use of prior information derived from former empirical findings and/or subject matter theory regarding the lag structure of the observable variables together with an AR process for the error terms can produce univariate and single equation models that are intuitively appealing, simple to implement and work well in practice.

The ARAR Error Model for Univariate Time Series and Distributed Lag