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

Hui Feng
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Hui Feng: Department of Economics, Business and Mathematics, King's University College at UWO, London, Ontario, Canada, Postal: Department of Economics, Business and Mathematics, King's University College at UWO, London, Ontario, Canada

Journal of Forecasting, 2009, vol. 28, issue 3, 183-193

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.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:28:y:2009:i:3:p:183-193

DOI: 10.1002/for.1089

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