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Predicting interest rates in real-time

Author

Listed:
  • Alberto Caruso
  • Laura Coroneo

Abstract

We analyse the predictive ability of real-time macroeconomic information for the yield curve of interest rates. We specify a mixed-frequency macro-yields model in real-time that incorporates interest rate surveys and that treats macroeconomic factors as unobservable components. Results indicate that real-time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real-time macro data. Moreover, we find that incorporating interest rate surveys in the model can significantly improve its predictive ability.

Suggested Citation

  • Alberto Caruso & Laura Coroneo, 2019. "Predicting interest rates in real-time," Discussion Papers 19/18, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:19/18
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Government Bonds; Dynamic Factor Models; Real-time Forecasting; Mixed-frequencies.;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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