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Real-time or current vintage: does the type of data matter for forecasting and model selection?

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  • Hui Feng

    (Department of Economics, Business and Mathematics, King's University College at UWO, London, Ontario, Canada)

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    Abstract

    In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000) and residential mortgage credit (1975-1998). The forecasting method we use is multi-step-ahead non-adaptive forecasting. Copyright © 2008 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.1089
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 28 (2009)
    Issue (Month): 3 ()
    Pages: 183-193

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    Handle: RePEc:jof:jforec:v:28:y:2009:i:3:p:183-193

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    Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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