OECD Green Talks LIVE - Evaluating the economic benefits of environmental policies that save lives.pdf

Every potential policy measure affecting human health – from seat belt laws to chemicals regulations – involves both economic costs and benefits. Stricter vehicle fuel efficiency standards may lead to higher costs for consumers and businesses, but they also save lives through improved air quality. Policymakers need reliable data to assess the economic benefits of health improvements of policies. The Value of Statistical Life concept (also known as the Value of a Prevented Fatality) has become a cornerstone in policy assessments to gain a better measure of the expected benefits in terms of lives saved of any policy that involves changes in mortality risk.

How can Value of Statistical Life estimates be used in policy analysis? How does the Value of Statistical Life differ across world regions? What considerations should policymakers take when transferring these estimates across countries and over time?

This OECD Green Talks LIVE took place 1 October 2025 from 15:00 to 16:00 CEST to launch the OECD report Mortality Risk Valuation in Policy Assessment: A Global Meta-analysis of Value of Statistical Life Studies. The report includes the largest meta-analysis of Value of Statistical Life studies ever attempted. Following a presentation of the key findings, panellists discuss how they can be leveraged to support cost-benefit analyses and other economic assessments. The webinar is moderated by Shardul Agrawala, Head of the Environment and Economy Integration Division in the OECD Environment Directorate.

Read the report: https://www.oecd.org/en/events/2025/10/evaluating-the-economic-benefits-of-environmental-policies-that-save-lives.html

1. Evaluating the economic
benefits of environmental
policies that save lives
Olof Byström
OECD Environment Directorate
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OECD Environment on LinkedIn
@OECD_ENV on X 1 October 2025
Launch of the OECD report Mortality Risk
Valuation in Policy Assessment
Henrik Lindhjem
Menon Economics
Ståle Navrud
Norwegian University of Life Sciences

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2How to place a value on mortalityrisk
Surveys
(Stated preference)
What if?
Observed behaviour
(Revealed preference)
Small payment for small change in mortality risk, aggregated to a probability of 1
Value of Statistical Life (VSL) or Value of a Prevented Fatality
Related concepts:
VSLY, QALY, DALY

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3OECD’s work previous on the VSL
›Published in 2012
›Stated preference studies only
›1970 – 2008 time frame
›405 VSL estimates

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Nearly all academic and grey
literature in English between
1970 to 2023
4 000 estimates from 49
countries

Updating the OECD’s valuations of mortality risk
EXPANDED LITERATURE GREATER POOL
OF STUDIES
IMPROVED
METHODOLOGY
Both stated preference and
revealed preference
approaches
Replicable systematic meta
data collection and improved
meta-analysis techniques
VSL by country groups and updated guidance on benefit transfer
Supported by advisory group
of leading academic experts

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5Geographical distribution of studies (1970 – 2023)
Stated preference studies Revealed preference studies

6. METHODOLOGY

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7Three steps of the study
VSL database with
information coded
as variables
Recommended VSL
estimates for policy
VSL estimates from primary
studies
Base estimates and ranges
for country groups
Factors considered:
•Methods used
•Risk characteristics
•Other (e.g. Country, year)
Adjustment factor for
specific uses:
•Income differences
across countries and over
time
Meta-analysis
&
regressions
Value
transfer
principles
&
methods
Meta-data Analysis Recommendations

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8The study used meta-data on VSL from 2009-2023
Stated preference estimates Revealed preference estimates
›The most important health
endpoints for the VSL
estimates are:
•Cancer
•Respiratory diseases
•Cardiovascular diseases

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9Data conversion, coding and screening
Variables extracted and coded into meta-database from primary studies
Extreme outliers excluded (aka “far-outs”)
No adjustment for income growth
Estimates adjusted to 2022 local currency values and converted to USD

10. KEY FINDINGS

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Mean preliminary unweighted VSL estimates* by country group
* Estimated means based on analysis of meta-data for the 2009-2023 period by country group using a 4-level random-effects model
All countries (N=156)
OECD (N=108)
High-incomecountries (N=113)
United States (N=38)
EuropeanUnion (N=37)
Low-and middle-income
countries (N=43)
PUVSL (2022 USD million)
0 1 2 3 4 5 6 7 8 9 10
5.5
7.1
7.6
7.2
7.1
0.9

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12Meta-regression results and sensitivity
›Mean VSL is not very sensitive to the estimation approach (Revealed vs Stated preferences) and
is instead more impacted by elicitation method within each approach:
•Consumer market studies give lower estimates, hedonic wage studies are higher, and stated preference
methodologies (CV and CE) are in the middle
›Income elasticity of VSL is robust and most estimates suggest a number around 1
(between 0.5 and 1.5)

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13Summary of evidence on adjustment factors
CHILDREN AGE
CANCER
PANDEMICS/
OTHER CAUSES
Uncertain/ limited evidence of
higher VSL
Mostly inverted U-shape, but
hard to operationalise
Regression results suggest a 2X factor for
VSL based on cancer risk
However, cancers are very heterogenous
and hard to generalise
Limited evidence for any
deviations from base
Except for GDP per capita, no other factors are suggested for adjusting base VSL

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Base VSL values and range
(based on population-weighted GDP per capita)
0
2
4
6
8
10
12
Global OECD EU United States High-income
countries
Low-middle
income countries
8.4 8.5
7.9
1.1
2.7
7.1
Calculated Median VSL
95% Confidence Band
Base VSL (Mean)
USD 2022 Million

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15Using the numbers in practice
›Very heterogenous data and contexts for use of VSL estimates
→Advantages of adopting simple, general guidelines that are widely applicable
›Many countries do not have VSL guidance and could use the following formula to derive national VSL
estimate :
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•Use base VSL estimates from the smallest group to which the country belongs
•Assume income elasticity of VSL of 1
›Adjust over time with real income growth and appropriate discount rate
›Adjusting base VSL with age, risk types/ causes or other factors is not recommended
› Different VSLs across countries? Generally yes
Country j in country group i

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16Summary
›Most comprehensive review and meta-analysis of the global VSL literature to date
›Robust «base» VSL estimates derived for use in policy assessment internationally and for
individual countries
›Data allows for testing alternative assumptions such as type of valuation method and income
elasticity
›Benefit Transfer to non-surveyed country using GDP per capita and income elasticity of 1

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Scan the QR code to
download the full report
Visit: oe.cd/VSL