Multi-Step Estimation for Forecasting
Michael Clements and
David Hendry ()
The Warwick Economics Research Paper Series (TWERPS) from University of Warwick, Department of Economics
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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Journal Article: Multi-step Estimation for Forecasting (1996)
Working Paper: MULTI-STEP ESTIMATION FOR FORECASTING (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:wrk:warwec:447
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