Effects of contemporaneous aggregation on the predictive power of information variables
AbstractObtaining reliable forecasts of the future path of inflation is crucial for inflation targeting. The importance of information variable approach in forecasting inflation is widely stated. Studies that explore the information content of money basically rely upon the Granger-causality tests and use contemporaneously aggregated time series. For a potential information variable such as a monetary variable, failing to find predictive power for a contemporaneously aggregated series such as the inflation level does not necessarily imply that the potential information variable lacks predictive power. This letter shows that, provided that such a causal relationship is valid for, at least, one of the components of the aggregate, then it is possible to obtain better forecasts of the aggregate using a disaggregated model.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 9 (2002)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAEL20
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Michael McNulty).
If references are entirely missing, you can add them using this form.