Abstract

Food consumption is a significant contributor to households’ carbon footprints. However, consumer heterogeneity in food-related carbon footprints remains underexplored, primarily due to limited data linking real-world consumption choices to environmental impacts. I address this gap by matching detailed purchase data with environmental impact estimates at the transaction level for a representative sample of 7,540 French households between 2017 and 2019. Using this unique dataset, I provide a comprehensive overview of the distribution of food carbon footprints and employ a structural demand model to estimate how price and expenditure changes influence food basket composition and carbon emissions. The analysis reveals three key insights. 1) There is heterogeneity in the distribution of food carbon footprints, with 20% of households accounting for 40% of total food emissions. 2) Households with higher carbon footprints are more price-sensitive, particularly regarding high-emission products like red meat. 3) Simulations indicate that a 44.60€/tCO2 eq. food carbon tax would reduce food-related emissions (8.5%), especially among high-emission households. While modest carbon tax levels appear effective at reducing emissions, they may also lead to a trade-off between lowering emissions and preserving diet quality.

Practical information