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Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning

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  • Xuemei Zhao
  • Simon Meister
  • Lucie Maruejols
  • Xiaohua Yu

Abstract

Eggs are an inexpensive and sustainable source of proteins, but volatility in the U.S. egg prices has intensified in recent years, raising concerns over food affordability and market stability. This study examines the drivers of U.S. egg price dynamics over 2004–2025 using a two‐stage framework that combines LASSO‐based variable selection with an ARIMAX forecasting model. The results reveal strong price persistence, together with significant impacts of energy, feed costs and seasonal demand. The influence of avian influenza is strongly time‐dependent, with limited effects in full‐sample averages but significant impacts during high‐intensity outbreak periods, particularly in the mid‐2010s and after 2022. Out‐of‐sample forecasts indicate that the LASSO‐ARIMAX model reduces forecast errors by more than 60% relative to a univariate ARIMA benchmark. These findings suggest that stabilizing key input costs, strengthening timely epidemiological surveillance, and proactively managing predictable seasonal demand pressures are more effective than relying on any single explanatory factor.

Suggested Citation

  • Xuemei Zhao & Simon Meister & Lucie Maruejols & Xiaohua Yu, 2026. "Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 48(4), pages 1146-1166, September.
  • Handle: RePEc:wly:apecpp:v:48:y:2026:i:4:p:1146-1166
    DOI: 10.1002/aepp.70082
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