How Much Is a Life Worth? New Model Aims to Shape Global Road Safety Policies

In a bold move to support evidence-based road safety policies, researchers from W2Economics in the Netherlands and the World Bank Group in Washington, D.C., have developed an innovative method to estimate the value of a statistical life (VSL) tailored to different countries' income levels. Published in Traffic Injury Prevention, the study addresses a critical issue: while the VSL is a key metric in evaluating road safety interventions through cost-benefit analysis, many countries, especially in the low- and middle-income bracket, lack reliable, country-specific data. The new model offers a practical, updated approach for countries to estimate this value using publicly available income statistics, enabling more accurate and defensible policy decisions.

Traditionally, VSL is used to measure the economic value of avoiding a fatality, representing how much society is willing to pay to reduce the risk of death. While high-income countries often conduct extensive “willingness-to-pay” (WTP) studies to derive this figure, low-income nations face financial and technical barriers to doing the same. The new model from Wijnen, Dahdah, and Pkhikidze provides a solution: a modernized “value transfer” function that adapts existing VSL data from around the world to local conditions, using income as the main adjustment factor.

From Theory to Function: Building the New Model

The research team based their model on VSL estimates from 32 countries, 25 high-income and 7 middle-income, drawing from three main sources: official government statistics, the SafetyCube project funded by the European Union, and peer-reviewed academic studies. The values were standardized to 2020 US dollars using World Bank exchange rates and inflation data, and outliers such as Egypt and Ethiopia were excluded due to disproportionately high VSLs compared to national incomes. The result was a solid dataset from which the researchers could establish base VSLs of $3.21 million for high-income countries and $404,000 for LMICs.

Income elasticity, the degree to which VSL changes in response to changes in income, was central to the model’s design. Based on a broad literature review, the researchers applied an elasticity of 0.8 for high-income countries and 1.2 for LMICs. These values acknowledge that in poorer nations, a rise in income tends to lead to a disproportionately higher valuation of life, due to changes in risk perception and financial priorities.

The resulting transfer equations are elegantly simple. For LMICs, VSL = 0.404 × (Y/5,726)^1.2. For HICs, VSL = 3.206 × (Y/42,087)^0.8. In both cases, “Y” stands for a country’s gross national income (GNI) per capita. These formulas make it possible to generate country-specific VSL estimates using only income data, a major advance for nations lacking the resources for full WTP studies.

A More Accurate Global Picture Emerges

The results of the model bring new clarity to VSL estimates. In LMICs, the VSL ranges from as low as $22,000 to around $1.05 million, depending on income levels, while in HICs, values span from $1.23 million to $4.82 million. Unlike older methods, such as the McMahon and Dahdah “70x GDP” rule or OECD’s flat recommendations, the new model captures the nonlinear relationship between income and life value. In lower-income countries, the model generates more conservative figures than the legacy models, correcting for overestimations. At the same time, it delivers more nuanced outputs for wealthier nations without inflating values unrealistically.

The paper also introduces quick-reference VSL-to-income ratios that provide rough but useful estimates for countries without full data. For low-income countries, the ratio is 46; for lower-middle-income, 58; for upper-middle-income, 77; and for high-income countries, 76. These ratios offer a practical tool for decision-makers, though the authors recommend applying the full equations for precision.

Looking Beyond Fatalities: The Missing Link

While this paper focuses on fatalities, the authors underscore the need to extend valuation methods to non-fatal injuries, a domain that remains largely under-researched despite its massive economic impact. Studies suggest that injuries and property damage account for 70–80% of total road crash costs. Yet, most cost-benefit analyses use outdated or inconsistent figures when assigning value to serious injuries. Current guidelines range from 13% to 25% of VSL for non-fatal injuries, based on decades-old data. The authors call for renewed research in this area to update these figures and build a more comprehensive framework for road safety economics.

The study also confirms that VSL alone accounts for over 90% of the total value of a prevented fatality in most countries, reinforcing its central importance in crash cost analyses. Additional costs, such as medical care, property damage, and administrative fees, comprise a much smaller share of the total.

A Call to Action for Low-Income Countries

The study concludes with a call for increased research efforts in LMICs, especially in low-income countries where no current VSL estimates exist. While the new value transfer function is a major step forward, a local WTP study remains the ideal source for determining VSL, as it captures cultural, demographic, and behavioral nuances. Nevertheless, the presented model offers a practical and scientifically grounded interim solution. It empowers governments and international agencies to make better-informed decisions about road safety investments and fosters comparability across global initiatives.

By modernizing how the value of human life is quantified in transport policy, this research lays a foundation for more equitable and impactful road safety strategies worldwide. It bridges a critical data gap and provides the tools to ensure that every dollar spent on road safety has the greatest possible benefit, whether in Manhattan or Maputo.