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Tier 4 — Narrative / commentaryGrey literature

Health-motivated taxes on red and processed meat: a modelling study on optimal tax levels and health and climate-change co-benefits

Marco Springmann, Daniel Mason-D’Croz, Sherman Robinson, Keith Wiebe, H. Charles J. Godfray, Mike Rayner, Peter Scarborough

International Food Policy Research Institute (International Food Policy Research Institute) · 2017

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Summary

This 2017 modelling study by Springmann and colleagues examines market-based taxation as a policy lever to reduce consumption of red and processed meat, addressing both chronic disease burden and food-system greenhouse-gas emissions. Using integrated assessment and computable general equilibrium approaches, the authors estimate optimal tax levels and quantify potential health and climate co-benefits. The work suggests that health-motivated taxation could achieve significant public health and environmental gains, though actual outcomes would depend on policy design and implementation context.

UK applicability

The study's global modelling framework and focus on red and processed meat—major consumption items in the United Kingdom—make the findings relevant to UK policymakers considering fiscal interventions. However, UK-specific elasticities, dietary baselines and distributional impacts would require adapted analysis for direct policy application.

Key measures

Optimal tax rates; mortality reduction; greenhouse-gas emission reductions; economic and health co-benefits

Outcomes reported

The study modelled optimal tax levels on red and processed meat using health impact and greenhouse-gas emission data. It estimated the health gains (mortality reduction) and climate-change co-benefits achievable through different tax scenarios.

Theme
Policy, governance & rights
Subject
Food & agricultural policy
Study type
Policy
Study design
Policy report
Source type
Grey literature
Status
Published
Geography
Global
System type
Intensive livestock
DOI
10.1371/journal.pone.0204139
Catalogue ID
BFmor3ggd1-jy6wbi

Topic tags

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