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Real time forecasts of inflation: the role of financial variables

Libero Monteforte and Gianluca Moretti ()
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Gianluca Moretti: Bank of Italy

No 767, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

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.

Keywords: forecasting inflation; real time forecasts; dynamic factor models; MIDAS regression; economic derivatives (search for similar items in EconPapers)
JEL-codes: C13 C51 C53 E37 G19 (search for similar items in EconPapers)
Date: 2010-07
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-eec, nep-for, nep-mac and nep-mon
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Real‐Time Forecasts of Inflation: The Role of Financial Variables (2013)
Working Paper: Real time forecasts of inflation: the role of financial variables Downloads
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