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The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting

Author

Listed:
  • Giusto Andrea

    (Dalhousie University, Halifax, Canada)

  • İşcan Talan B.

    (Dalhousie University, Halifax, Canada)

Abstract

This paper introduces the rescaled representation of VAR models (R-VARs) and demonstrates its application in forecasting mixed-frequency macroeconomic data. We develop the model, illustrate how to implement it, and derive the asymptotic properties of the estimates. We show that R-VARs provide reliable estimates of the prediction error bands while maintaining the precision of the point forecasts. We illustrate these features by comparing it to a mixed-frequency Bayesian VAR model, the leading alternative in the existing literature.

Suggested Citation

  • Giusto Andrea & İşcan Talan B., 2018. "The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    • Handle: RePEc:bpj:sndecm:v:22:y:2018:i:4:p:16:n:4
    DOI: 10.1515/snde-2017-0047
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    forecasts confidence intervals; mixed-frequency data; real-time forecasting; rescaled VAR model;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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