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Non-parametric direct multi-step estimation for forecasting economic processes

Abstract:
We evaluate the asymptotic and finite-sample properties of direct multi-step estimation (DMS) for forecasting at several horizons. For forecast accuracy gains from DMS in finite samples, mis-specification and non-stationarity of the DGP are necessary, but when a model is well-specified, iterating the one-step ahead froecasts may not be asymptotically preferable. If a model is mis-specified for a non-stationary DGP, in particular omitting either negative residual serial correlation or regime shifts, DMS can forecast more accurately. Monte Carlo simulations clarify the non-linear dependence of the estimation and forecast biases on the parameters of the DGP, and explain existing results.
Publication status:
Published

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Publisher:
University of Oxford
Series:
Department of Economics Discussion Paper Series
Publication date:
2004-07-01
Paper number:
196


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Pubs id:
1144236
Local pid:
pubs:1144236
Deposit date:
2020-12-15
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