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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)

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.

Suggested Citation

  • Hui Feng, 2009. "Real-time or current vintage: does the type of data matter for forecasting and model selection?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 183-193.
    • Handle: RePEc:jof:jforec:v:28:y:2009:i:3:p:183-193
    DOI: 10.1002/for.1089
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    References listed on IDEAS

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