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Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes

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  • Guillaume Chevillon

    ()
    (Economcis Department, University of Oxford)

  • David F. Hendry

    ()
    (Economics Department, University of Oxford)

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, 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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Bibliographic Info

Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2004-W12.

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Length: 27 pages
Date of creation: 24 May 2004
Date of revision:
Handle: RePEc:nuf:econwp:0412

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Web page: http://www.nuff.ox.ac.uk/economics/

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Keywords: Adaptive estimation; multi-step estimation; dynamic forecasts; model mis-specification.;

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