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

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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.

Suggested Citation

  • Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicewp:0515
    Note: ISSN 1485-6441
    as

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    File URL: https://www.uvic.ca/socialsciences/economics/_assets/docs/econometrics/ewp0515.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Vintage Data; Real-time Data; Model Selection; SETAR Model; ARMA model; Forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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