Real-time inflation forecasting in a changing world

Arbeitspapier

This paper revisits inflation forecasting using reduced-form Phillips curve forecasts, that is, inflation forecasts that use activity and expectations variables. We propose a Phillips-curve-type model that results from averaging across different regression specifications selected from a set of potential predictors. The set of predictors includes lagged values of inflation, a host of real-activity data, term structure data, nominal data, and surveys. In each individual specification, we allow for stochastic breaks in regression parameters, where the breaks are described as occasional shocks of random magnitude. As such, our framework simultaneously addresses structural change and model uncertainty that unavoidably affect Phillips-curve-based predictions. We use this framework to describe personal consumption expenditure (PCE) deflator and GDP deflator inflation rates for the United States in the post-World War II period. Over the full 1960-2008 sample, the framework indicates several structural breaks across different combinations of activity measures. These breaks often coincide with policy regime changes and oil price shocks, among other important events. In contrast to many previous studies, we find less evidence of autonomous variance breaks and inflation gap persistence. Through a real-time out-of-sample forecasting exercise, we show that our model specification generally provides superior one-quarter-ahead and one-year-ahead forecasts for quarterly inflation relative to an extended range of forecasting models that are typically used in the literature.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Staff Report ; No. 388

Classification and Topics

• Classification: Wirtschaft ; Bayesian Analysis: General ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Forecasting Models; Simulation Methods ; Price Level; Inflation; Deflation
• Subject: Inflation forecasting ; Phillips correlations ; real-time data ; structural breaks ; model uncertainty ; Bayesian model averaging

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Groen, Jan J. J. ; Paap, Richard ; Ravazzolo, Francesco
• Event: Veröffentlichung
• (who): Federal Reserve Bank of New York
• (where): New York, NY
• (when): 2009

Further information

• Handle: http://hdl.handle.net/10419/60913
• Last update: 10.03.2025, 11:41 AM CET