Forecasting retail food prices changes from highly pathogenic avian influenza

Shifting seasonal patterns have arisen in food markets due to changing supply chains, consumer preferences, and infectious disease prevalence. Persistent infections of H5N1 avian influenza among U.S. poultry and egg-laying bird populations have altered the seasonal patterns in corresponding market dynamics, particularly prices. While the geographic distribution of the precise timing of cases remains difficult, the broad pattern of higher prevalence in Winter and lower prevalence in summer typically leads to price spikes early each year. This pattern represents a shift from historical seasonality, which typically saw mild price spikes around the winter holidays and Easter. At the same time, the imposition of desirable model features may enhance forecast performance when historical data do not yet capture these phenomena. However, such ad hoc modifications should be done carefully, as the addition, potentially intuitively appealing, of a model structure often increases forecast errors. We find that simpler forecasting models typically yield the lowest forecast error if they are allowed to adapt over time. More accurate predictions facilitate better planning among producers, consumers, and entities providing food assistance to low-income households.