The Reliability of Inflation Forecasts Based on Output Gaps in Real Time

Athanasios Orphanides and Simon van Norden
Authors registered in the RePEc Author Service: Athanasios Orphanides and Simon van Norden ()

No 247, Computing in Economics and Finance 2001 from Society for Computational Economics

Abstract: A stable predictive relationship between inflation and the output gap, often referred to as a Phillips curve, provides the basis for empirical formulations of countercyclical monetary policy in many models. However, evidence for the usefulness of output gap measures for forecasting inflation is often based on data that are not available when actual forecasts are made in practice. This ignores difficulties associated with estimation of the output gap in real-time and raises questions regarding the reliability of the resulting forecasts. In this paper we evaluate alternative multivariate methods for estimation of the output gap and assess their usefulness for predicting inflation. Our results suggest that inference based on ex-post constructed output gap measures severely overstates their usefulness for predicting inflation and, therefore, for the real-time policy process. Further, forecasts based on models that fail to control for the unreliability of the real-time estimates of the output gap are often less accurate than forecasts that abstract from the output gap concept altogether. These results bring into question the reliability of inflation forecasts based on output gaps for formulating monetary policy.

Keywords: Real-time data; business cycle measurement; inflation (search for similar items in EconPapers)
JEL-codes: E3 (search for similar items in EconPapers)
Date: 2001-04-01
References: Add references at CitEc
Citations: View citations in EconPapers (20)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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:sce:scecf1:247

Access Statistics for this paper

More papers in Computing in Economics and Finance 2001 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().