The Distributional Predictive Content of Measures of Inflation Expectations

James Mitchell and Saeed Zaman

No 23-31, Working Papers from Federal Reserve Bank of Cleveland

Abstract: This paper examines the predictive relationship between the distribution of realized inflation in the US and measures of inflation expectations from households, firms, financial markets, and professional forecasters. To allow for nonlinearities in the predictive relationship we use quantile regression methods. We find that the ability of households to predict future inflation, relative to that of professionals, firms, and the market, increases with inflation. While professional forecasters are more accurate in the middle of the inflation density, households’ expectations are more useful in the upper tail. The predictive ability of measures of inflation expectations is greatest when combined. We show that it is helpful to let the combination weights on different agents’ expectations of inflation vary by quantile when assessing inflationary pressures probabilistically.

Keywords: inflation expectations measures; inflation; density forecasts; quantile predictive regressions; non-Gaussian models; nonlinearities (search for similar items in EconPapers)
JEL-codes: C15 C53 E3 E37 (search for similar items in EconPapers)
Pages: 53
Date: 2023-11-30
New Economics Papers: this item is included in nep-ban, nep-mac and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.26509/frbc-wp-202331 Persistent Link (text/html)
https://www.clevelandfed.org/-/media/project/cleve ... pers/2023/wp2331.pdf Full Text (application/pdf)

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:fip:fedcwq:97395

Ordering information: This working paper can be ordered from

DOI: 10.26509/frbc-wp-202331

Access Statistics for this paper

More papers in Working Papers from Federal Reserve Bank of Cleveland Contact information at EDIRC.
Bibliographic data for series maintained by 4D Library ().