The distributional predictive content of measures of inflation expectations

Author:

Mitchell James1ORCID,Zaman Saeed1ORCID

Affiliation:

1. 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.

Publisher

Federal Reserve Bank of Cleveland

Reference44 articles.

1. 1. Aastveit, Knut Are, Saskia ter Ellen, and Giulia Mantoan (2022). "Quantile density combination: An application to US GDP forecasts." mimeo, Norges Bank. URL https://www.clevelandfed.org/-/media/project/clevelandfedtenant/clevelandfedsite/events/conference-on-real-time-data/knut-are-aastveit-paper.pdf.

2. 2. Adrian, Tobias, Nina Boyarchenko, and Domenico Giannone (2019). "Vulnerable growth." American Economic Review, 109(4), pp. 1263-89. doi:10.1257/aer.20161923.

3. 3. Ahn, Hie Joo and Chad Fulton (2021). "Research data series: Index of common inflation expectations." Technical report, FEDS Notes. Washington: Board of Governors of the Federal Reserve System. doi:10.17016/2380-7172.2873.

4. 4. Ang, Andrew, Geert Bekaert, and Min Wei (2007). "Do macro variables, asset markets, or surveys forecast inflation better?" Journal of Monetary Economics, 54(4), pp. 1163-1212. doi:10.1016/j.jmoneco.2006.04.006.

5. 5. Bauer, Michael D. and Erin McCarthy (2015). "Can we rely on market-based inflation forecasts?" FRBSF Economic Letter. URL https://ideas.repec.org/a/fip/fedfel/00070.html.

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1. Inflation's Last Half Mile: Higher for Longer?;Economic Commentary (Federal Reserve Bank of Cleveland);2024-05-30

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