Breaks and the statistical process of inflation: the case of estimating the ‘modern’ long-run Phillips curve
Bill Russell () and
Dooruj Rambaccussing
Empirical Economics, 2019, vol. 56, issue 5, No 1, 1455-1475
Abstract:
Abstract ‘Modern’ theories of the Phillips curve inadvertently imply that inflation is an integrated or near-integrated process, but this implication is strongly rejected using US data. Alternatively, if we assume that inflation is a stationary process around a shifting mean (due to changes in monetary policy), then any estimate of long-run relationships in the data will suffer from a ‘small-sample’ problem as there are too few stationary inflation ‘regimes’. Using the extensive literature on identification of structural breaks, we identify inflation regimes which are used in turn to estimate with panel data techniques the US long-run Phillips curve.
Keywords: Phillips curve; Inflation; Structural breaks; Non-stationary data (search for similar items in EconPapers)
JEL-codes: C23 E31 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s00181-017-1404-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
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:spr:empeco:v:56:y:2019:i:5:d:10.1007_s00181-017-1404-5
Ordering information: This journal article can be ordered from
http://www.springer. ... rics/journal/181/PS2
DOI: 10.1007/s00181-017-1404-5
Access Statistics for this article
Empirical Economics is currently edited by Robert M. Kunst, Arthur H.O. van Soest, Bertrand Candelon, Subal C. Kumbhakar and Joakim Westerlund
More articles in Empirical Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().