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Forecasting the Covid Surge in Inflation

Author

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  • Mark W. Watson

Abstract

The persistent surge in U.S. inflation that began in 2021 caught forecasters and policymakers by surprise. The 2021 inflation shocks were viewed as transitory, not persistent, leading to large forecast errors in late 2021 and 2022. This paper asks whether time series models – using only data on current and past inflation, but incorporating stochastic volatility and exhibiting time-varying persistence – performed better. Univariate models, using real-time data, did not. Multivariate models, incorporating sectoral inflation measures, did.

Suggested Citation

  • Mark W. Watson, 2026. "Forecasting the Covid Surge in Inflation," NBER Working Papers 35435, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:35435
    Note: EFG ME
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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