Do Phillips Curves Conditionally Help to Forecast Inflation?

Michael Dotsey, Shigeru Fujita and Tom Stark
Additional contact information
Michael Dotsey: Federal Reserve Bank of Philadelphia
Tom Stark: Federal Reserve Bank of Philadelphia

International Journal of Central Banking, 2018, vol. 14, issue 4, 43-92

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.

JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (35)

Downloads: (external link)
http://www.ijcb.org/journal/ijcb18q3a2.pdf (application/pdf)
http://www.ijcb.org/journal/ijcb18q3a2.htm (text/html)

Related works:
Working Paper: Do Phillips Curves Conditionally Help to Forecast Inflation? (2017)
Working Paper: Do Phillips curves conditionally help to forecast inflation? (2015)
Working Paper: Do Phillips curves conditionally help to forecast inflation? (2011)
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:ijc:ijcjou:y:2018:q:3:a:2

Access Statistics for this article

International Journal of Central Banking is currently edited by Loretta J. Mester

More articles in International Journal of Central Banking from International Journal of Central Banking
Bibliographic data for series maintained by Bank for International Settlements ().