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

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

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Article ID: iaor20052617
Country: Netherlands
Volume: 21
Issue: 2
Start Page Number: 201
End Page Number: 218
Publication Date: Apr 2005
Journal: International Journal of Forecasting
Authors: ,
Keywords: forecasting: applications
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 forecasts 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 nonlinear dependence of the estimation and forecast biases on the parameters of the DGP, and explain existing results.

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