Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?
AbstractIn 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.
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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0515.
Length: 19 pages
Date of creation: 24 Aug 2005
Date of revision:
Note: ISSN 1485-6441
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Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
Web page: http://web.uvic.ca/econ
More information through EDIRC
Vintage Data; Real-time Data; Model Selection; SETAR Model; ARMA model; Forecasting;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-09 (All new papers)
- NEP-ETS-2005-11-09 (Econometric Time Series)
- NEP-FOR-2005-11-09 (Forecasting)
- NEP-MAC-2005-11-09 (Macroeconomics)
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