Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?

Hui Feng

No 515, Econometrics Working Papers from Department of Economics, University of Victoria

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.

Keywords: Vintage Data; Real-time Data; Model Selection; SETAR Model; ARMA model; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2005-08-24
New Economics Papers: this item is included in nep-ets, nep-for and nep-mac
Note: ISSN 1485-6441
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.uvic.ca/socialsciences/economics/_asse ... ometrics/ewp0515.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vic:vicewp:0515

Access Statistics for this paper

More papers in Econometrics Working Papers from Department of Economics, University of Victoria PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2. Contact information at EDIRC.
Bibliographic data for series maintained by Kali Moon ().