A QUANTITATIVE COMPARISON OF STICKY-PRICE AND STICKY-INFORMATION MODELS OF PRICE SETTING

Michael Kiley

No 183, Computing in Economics and Finance 2005 from Society for Computational Economics

Abstract: This paper presents baseline sticky-price and sticky-information models of price-setting, and modifies each to incorporate some “rule-of-thumb†price-setters that index to inflation over recent periods. These models are estimated for the United States via maximum-likelihood techniques. While the baseline sticky-information model generates a bit more endogenous inertia in inflation than the baseline sticky-price model, its overall fit is worse. The results point toward substantial gains in terms of fit for hybrid models with indexation that smoothes through quarterly volatility in inflation and clarify the relative performance of recent sticky-information models proposed in the literature

Keywords: Phillips curve; New-Keynesian model; Inflation (search for similar items in EconPapers)
JEL-codes: E3 (search for similar items in EconPapers)
Date: 2005-11-11
References: Add references at CitEc
Citations: View citations in EconPapers (16)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: A Quantitative Comparison of Sticky-Price and Sticky-Information Models of Price Setting (2007)
Working Paper: A quantitative comparison of sticky-price and sticky-information models of price setting (2006)
Journal Article: A quantitative comparison of sticky-price and sticky-information models of price setting (2005)
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:sce:scecf5:183

Access Statistics for this paper

More papers in Computing in Economics and Finance 2005 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().