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

  • Chevillon, Guillaume
  • Hendry, David F.

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.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 21 (2005)
Issue (Month): 2 ()
Pages: 201-218

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Handle: RePEc:eee:intfor:v:21:y:2005:i:2:p:201-218
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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