Improving inflation forecasts using robust measures☆

Randal J. Verbrugge

doi:10.1016/j.ijforecast.2023.05.003

Improving inflation forecasts using robust measures☆

2024-04-01

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PRE

AI

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Randal J. Verbrugge *

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Saeed Zaman

DOI：10.1016/j.ijforecast.2023.05.003

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Theory and extant empirical evidence suggest that the cross-sectional asymmetry across disaggregated price indexes might be useful in forecasting aggregate inflation. Trimmedmean inflation estimators have been shown to be useful devices for forecasting headline PCE inflation. But is this because they signal the underlying trend or implicitly signal asymmetry in the underlying distribution? We address this question by augmenting a hard to beatbenchmark headline PCE inflation forecasting model with robust trimmed mean inflation measures and robust measures of the cross-sectional skewness, both computed using the 180+ components of the PCE price index. Our results indicate significant gains in the point and density accuracy of PCE inflation forecasts over medium- and long-term horizons, including the COVID-19 pandemic. Improvements in accuracy stem mainly from the trend information implicit in trimmed-mean estimators, but skewness information is also useful. Examining goods and services PCE inflation (using newly constructed trimmed mean and skewness measures of the same) provides similar inference. (c) 2023 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Keyword:

Disaggregate inflation

Skewness

Forecasting

Median PCE inflation

Trimmed-mean PCE

Improving inflation forecasts using robust measures☆

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