Valuing reductions in the risk of death in benefit–cost analyses of environment- and climate-health actions

Frank Pega, Natalie C. Momen, Samuel A. Agyemang, Laura Bojke, Joan Costa-Font, Laure de Preux, Eli P. Fenichel, Bruce Gordon, Martin C. Hensher, Richard Johnston, Yuvaraj Krishnamoorthy, Antonios Kolimenakis, Ashar Muhammad Malik, Hiroaki Matsuura, Nhung Nghiem, O’Hare, Bernadette, Megha Rathi, Lisa A. Robinson and Diarmid Campbell-Lendrum

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Economic evaluation is key for efficient allocation of resources in health and related sectors. Actions addressing environmental risk factors and climate change can avert millions of deaths annually, yet valuing reductions in the risk of dying is challenging in benefit–cost analyses. We developed an interim statistical protocol to estimate the value per statistical life for World Health Organization (WHO) Member States, building on the 2019 benefit–cost analysis reference case and latest evidence. Using gross national income per capita based on purchasing power parity, we calculated national estimates for 2024 and projected values to 2100. We aggregated these estimates to produce global, regional and country income group averages, and additional sets for sensitivity and scenario analyses, including for alternative climate change scenarios. Our estimates cover 93.8% (182/194) of Member States, representing 98.4% (7.99 billion/8.12 billion) of the global population. The global average value per statistical life in 2024 was 3.76 million international dollars. By 2100, the global average is projected to increase by 159.8% to 9.77 million international dollars. These estimates provide a basis for valuing expected deaths averted by environment- and climate-health interventions, promoting comparability across analyses. Limitations include reliance on extrapolated values and uncertainty in income projections. More research, especially in low- and middle-income countries, is needed. Because value per statistical life estimates depend on income, analysts must supplement benefit–cost analysis with distributional analyses of benefits and costs across populations. Until WHO updates its recommended methods, these interim estimates offer a pragmatic tool for policy analysis.

JEL-codes: J1 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2026-04-01
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Published in Bulletin of the World Health Organization, 1, April, 2026, 104(4), pp. 246-258. ISSN: 0042-9686

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