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VAR, Error Correction and Pretest Forecasts at Long Horizons

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Author Info
Stock, James H

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Abstract

This paper focuses on the construction of forecasts over long horizons where a typical, long-horizon forecast might span four years using twenty to forty years' data. It is argued that the presence of persistence in the form of unit or near-unit autoregressive roots poses substantial difficulties for long-horizon interval and point forecasting. These difficulties may not be overcome even by efficient pretesting or model-selection procedures and might, in general, lead to point forecasts with large asymptotic root mean squared errors and undesirably wide prediction intervals. Copyright 1996 by Blackwell Publishing Ltd

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Publisher Info
Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 58 (1996)
Issue (Month): 4 (November)
Pages: 685-701
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Handle: RePEc:bla:obuest:v:58:y:1996:i:4:p:685-701

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  5. Serena Ng & Timothy Vogelsang, 1999. "Forecasting Dynamic Time Series in the Presence of Deterministic Components," Boston College Working Papers in Economics 445, Boston College Department of Economics. [Downloadable!]
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  7. Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests Are Useful for Selecting Forecasting Models," NBER Working Papers 6928, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  8. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  9. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal. [Downloadable!]
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