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Real time forecasts of inflation: the role of financial variables

Author

Listed:
  • Libero Monteforte

    (Bank of Italy)

  • Gianluca Moretti

    (Bank of Italy)

Abstract

We present a mixed-frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real-time is compared with that of standard VARs and of daily quotes of economic derivatives on euro area inflation. We find that the inclusion of daily variables helps to reduce forecast errors with respect to models that consider only monthly variables. The mixed-frequency model also displays superior predictive performance with respect to forecasts solely based on economic derivatives.

Suggested Citation

  • Libero Monteforte & Gianluca Moretti, 2010. "Real time forecasts of inflation: the role of financial variables," Temi di discussione (Economic working papers) 767, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_767_10
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    Keywords

    forecasting inflation; real time forecasts; dynamic factor models; MIDAS regression; economic derivatives;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G19 - Financial Economics - - General Financial Markets - - - Other

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