Adaptive food price forecasting improves public information in times of rapid economic change.

Publication date: Jul 08, 2025

The advent of COVID-19 ended an era of stable US retail food prices that followed the world food price crisis of 2010-2012. Pandemic-related disruptions, avian influenza outbreaks, and the Russia-Ukraine war drove 2022 food-at-home inflation to its highest rate since 1974 (11. 4%). In 2023, U. S. Department of Agriculture (USDA) economists responded to these changes by updating food price forecasts using statistical learning protocols to select time series models and prediction intervals to convey their uncertainty. We characterise the public good provided by these “adaptive” inflation forecasts and enhance them by incorporating exogenous variables to improve their precision and explanatory power. COVID-19’s arrival highlighted the value of adapting to the growing relevance of the all-items-less-food-and-energy (“core”) index, the money supply, and wages in predicting food prices. The strong relationships between food prices and core prices and the money supply indicate the sensitivity of food markets to macroeconomic forces and government policy decisions.

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Concepts Keywords
Economists Commerce
Food COVID-19
Influenza Food
Food Supply
Forecasting
Humans
Pandemics
SARS-CoV-2
United States

Semantics

Type Source Name
disease MESH COVID-19
disease MESH avian influenza
disease MESH uncertainty
drug DRUGBANK Trestolone
disease MESH African swine fever
disease MESH aids
drug DRUGBANK Coenzyme M
disease IDO algorithm
drug DRUGBANK Copper
disease MESH causality
disease IDO process

Original Article

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