Does money matter in inflation forecasting?

Richard Anderson (), Jane M. Binner, Barry Jones, Graham Kendall, Jonathan Tepper and Peter Tino

No 2009-030, Working Papers from Federal Reserve Bank of St. Louis

Abstract: This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.

Keywords: Forecasting; Inflation (Finance); Monetary theory (search for similar items in EconPapers)
Date: 2009
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for, nep-mac and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://s3.amazonaws.com/real.stlouisfed.org/wp/2009/2009-030.pdf Full text (application/pdf)

Related works:
Journal Article: Does money matter in inflation forecasting? (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:2009-030

Ordering information: This working paper can be ordered from

DOI: 10.20955/wp.2009.030

Access Statistics for this paper

More papers in Working Papers from Federal Reserve Bank of St. Louis Contact information at EDIRC.
Bibliographic data for series maintained by Scott St. Louis ().