Arbeitspapier

Real-time inflation forecasting in a changing world

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.

Sprache
Englisch

Erschienen in
Series: Staff Report ; No. 388

Klassifikation
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
Thema
Inflation forecasting
Phillips correlations
real-time data
structural breaks
model uncertainty
Bayesian model averaging

Ereignis
Geistige Schöpfung
(wer)
Groen, Jan J. J.
Paap, Richard
Ravazzolo, Francesco
Ereignis
Veröffentlichung
(wer)
Federal Reserve Bank of New York
(wo)
New York, NY
(wann)
2009

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Groen, Jan J. J.
  • Paap, Richard
  • Ravazzolo, Francesco
  • Federal Reserve Bank of New York

Entstanden

  • 2009

Ähnliche Objekte (12)