Multi-Step Estimation for Forecasting

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Abstract
We delineate conditions which favour multi-step, or dynamic estimation for multi-step forecasting. An analytical example shows how dynamic estimation (DE) may accomodateincorrectly-specified models as the forecast lead alters, improving forecast performance for some mis-specifications. However, in correctly-specified models, reducing finite-sample biases does not justify DR. In a Monte Carlo forecasting study for integrated processes, estimating a unit root in the presence of a neglected negative moving-average error may favour DR, though other solutions exist to that scenario. A second Monte Carlo study obtains the estimator biases and explains these using asymptotic approximations.

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