Do Phillips Curves Conditionally Help to Forecast Inflation?

Michael Dotsey, Shigeru Fujita and Tom Stark

No 17-26, Working Papers from Federal Reserve Bank of Philadelphia

Abstract: 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. Significantly, we also find conditional inferiority, with some exceptions. 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.

Keywords: Phillips curve; unemployment gap; conditional predictive ability (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2017-08-21
New Economics Papers: this item is included in nep-cba, nep-for and nep-mac
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Do Phillips Curves Conditionally Help to Forecast Inflation? (2018)
Working Paper: Do Phillips curves conditionally help to forecast inflation? (2015)
Working Paper: Do Phillips curves conditionally help to forecast inflation? (2011)
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