Real time forecasts of inflation: the role of financial variables
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.
|Date of creation:||Jul 2010|
|Date of revision:|
|Contact details of provider:|| Postal: Via Nazionale, 91 - 00184 Roma|
Web page: http://www.bancaditalia.it
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:bdi:wptemi:td_767_10. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.