Federal Reserve Bank of Philadelphia
Do Phillips curves conditionally help to forecast inflation?
This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. We also find, however, that conditioning on the state of the economy sometimes does improve the performance of the Phillips curve model in a statistically significant manner. When we do find improvement, it is asymmetric -- Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. Any improvement we find, however, vanished over the post-1984 period. Supersedes WP 11-40.
Cite this item
Michael Dotsey & Shigeru Fujita & Tom Stark, Do Phillips curves conditionally help to forecast inflation?, Federal Reserve Bank of Philadelphia, Working Papers 15-16, 25 Mar 2015.
Note: Superseded by WP 17-26
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
Keywords: Phillips curve; unemployment gap; conditional predictive ability
This item with handle RePEc:fip:fedpwp:15-16
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