scholarly journals The Income Elasticity of Global Values of a Statistical Life: Stated Preference Evidence

2018 ◽  
Author(s):  
Clayton Masterman ◽  
W. Kip Viscusi
Keyword(s):  
Income Elasticity ◽  
Stated Preference ◽  
Statistical Life ◽  
Global Values

scholarly journals The Income Elasticity of Global Values of a Statistical Life: Stated Preference Evidence

2018 ◽  
Vol 9 (3) ◽  
pp. 407-434 ◽  
Author(s):  
Clayton J. Masterman ◽  
W. Kip Viscusi
Keyword(s):  
Income Elasticity ◽  
Stated Preference ◽  
Sample Selection ◽  
Revealed Preference ◽  
Sample Selection Bias ◽  
Lower Income ◽  
Income Levels ◽  
Statistical Life ◽  
Per Capita ◽  
Global Values

Examination of estimates of the income elasticity of the value of a statistical life based on international stated preference studies yields an average between 0.94 and 1.05 overall and 0.65 and 0.80 after controlling for covariates. Quantile regression estimates indicate that the income elasticity is about 0.55 for more affluent countries and 1.0 for lower income nations, i.e., those countries that have estimates of the value of a statistical life below $2 million or per capita income levels below $3212. The estimates distinguish the values of the income elasticity across country either by income level or by the value of a statistical life. These elasticities are similar to those found in revealed preference labor market studies. The estimates are robust, controlling for possible sample selection bias and the influence of covariates, such as the type of risk.

Publication selection and the income elasticity of the value of a statistical life

2014 ◽  
Vol 33 ◽  
pp. 67-75 ◽  
Author(s):  
Hristos Doucouliagos ◽  
T.D. Stanley ◽  
W. Kip Viscusi
Keyword(s):  
Income Elasticity ◽  
Statistical Life

scholarly journals Valuing Mortality Risk Reductions in Global Benefit-Cost Analysis

2019 ◽  
Vol 10 (S1) ◽  
pp. 15-50 ◽  
Author(s):  
Lisa A. Robinson ◽  
James K. Hammitt ◽  
Lucy O’Keeffe
Keyword(s):  
Mortality Risk ◽  
Income Elasticity ◽  
Lower Income ◽  
Middle Income ◽  
Income Differences ◽  
Benefit Cost Analysis ◽  
Middle Income Countries ◽  
Statistical Life ◽  
The Past ◽  
Benefit Cost

The estimates used to value mortality risk reductions are a major determinant of the benefits of many public health and environmental policies. These estimates (typically expressed as the value per statistical life, VSL) describe the willingness of those affected by a policy to exchange their own income for the risk reductions they experience. While these values are relatively well studied in high-income countries, less is known about the values held by lower-income populations. We identify 26 studies conducted in the 172 countries considered low- or middle-income in any of the past 20 years; several have significant limitations. Thus there are few or no direct estimates of VSL for most such countries. Instead, analysts typically extrapolate values from wealthier countries, adjusting only for income differences. This extrapolation requires selecting a base value and an income elasticity that summarizes the rate at which VSL changes with income. Because any such approach depends on assumptions of uncertain validity, we recommend that analysts conduct a standardized sensitivity analysis to assess the extent to which their conclusions change depending on these estimates. In the longer term, more research on the value of mortality risk reductions in low- and middle-income countries is essential.

VP95 The Monetary Value Of A Statistical Life Year: A Systematic Review

2017 ◽  
Vol 33 (S1) ◽  
pp. 192-193
Author(s):  
Michael Schlander ◽  
Oliver Schwarz ◽  
Ramon Schaefer
Keyword(s):  
Systematic Review ◽  
Discount Rate ◽  
Stated Preference ◽  
Economic Value ◽  
Revealed Preference ◽  
Cost Benefit ◽  
Original Research ◽  
Statistical Life ◽  
Empirical Estimates ◽  
Widespread Agreement

INTRODUCTION:Among economists, there is widespread agreement that the monetary valuation of health gains should reflect the preferences of those who will be affected by resource allocation decisions. In the context of Health Technology Assessments (HTAs), this view implies a need for reliable empirical estimates of the value of statistical life year (VSLY), which should provide a useful point of reference for cost benefit analyses.METHODS:We conducted a systematic review of the literature on the economic value of a statistical life (VSL). We searched in the EconBiz and EconLit databases for studies, which reported VSL estimates based on original research and were published between 1995 and 2015. We classified studies by methodology, that is, revealed preference (RP) or stated preference (SP; that is, CV, contingent valuation, or DCE (discrete choice experiment) approach, and by regional origin of data. We transformed VSL estimates into VSLY expressed in year 2014 Euros, using life expectancy tables for the populations studied, a real discount rate of 3 percent, national Consumer Price Indices for inflating, and purchasing power parities for currency conversion. In addition, we calculated ratios of VSLY to gross domestic product (GDP) per capita.RESULTS:Our search yielded 120 studies appropriate for inclusion. From these, we extracted a total of 132 VSL estimates (RP, n = 60; SP, n = 72). The median VSLY was 6.4 times GDP/capita. Transformed into Euro (2014), the median VSLY was EUR165,000 (mean, EUR217,000). We found significant differences by regional source of data (North American, median EUR272,000; European, EUR158,000) and by method (RP, EUR241,000; SP: CV, EUR117,000; DCE, EUR187,000). VSLY estimates were sensitive to discount rate.CONCLUSIONS:Our data indicate that VSLY estimates based on empirical data exceed benchmarks commonly used in the context of HTAs. However, inter-study variability, methodological limitations, and normative considerations, all suggest to exercise caution before translating this observation into actual policy.

Valuing lives and life years: anomalies, implications, and an alternative

2008 ◽  
Vol 3 (3) ◽  
pp. 277-300 ◽  
Author(s):  
PAUL DOLAN ◽  
ROBERT METCALFE ◽  
VICKI MUNRO ◽  
MICHAEL C. CHRISTENSEN
Keyword(s):  
Stated Preference ◽  
Well Being ◽  
Quality Adjusted Life Year ◽  
Revealed Preferences ◽  
Subjective Well Being ◽  
Government Interventions ◽  
Statistical Life ◽  
Risk Of Death ◽  
Life Years ◽  
Starting Point

AbstractMany government interventions seek to reduce the risk of death. The value of preventing a fatality (VPF) is the monetary amount associated with each statistical death that an intervention can be expected to prevent. The VPF has been estimated using a preference-based approach, either by observing market behaviour (revealed preferences) or by asking hypothetical questions that seek to replicate the market (stated preferences). The VPF has been shown to differ across and within these methods. In theory, the VPF should vary according to factors such as baseline and background risk, but, in practice, the estimates vary more by theoretically irrelevant factors, such as the starting point in stated preference studies. This variation makes it difficult to choose one unique VPF. The theoretically irrelevant factors also affect the estimates of the monetary value of a statistical life year and the value of a quality-adjusted life year. In light of such problems, it may be fruitful to focus more research efforts on generating the VPF using an approach based on the subjective well-being associated with different states of the world.

scholarly journals The Income Elasticity of the Value per Statistical Life: Transferring Estimates between High and Low Income Populations

2011 ◽  
Vol 2 (1) ◽  
pp. 1-29 ◽  
Author(s):  
James K. Hammitt ◽  
Lisa A. Robinson
Keyword(s):  
Low Income ◽  
Income Elasticity ◽  
Real Income ◽  
Future Earnings ◽  
Statistical Life ◽  
Percent Change ◽  
New Research ◽  
Bounded Below ◽  
Lower Income Countries ◽  
Value Per Statistical Life

The income elasticity of the value per statistical life (VSL) is an important parameter for policy analysis. Mortality risk reductions often dominate the quantified benefits of environmental and other policies, and estimates of their value are frequently transferred across countries with significantly different income levels. U.S. regulatory agencies typically assume that a 1.0 percent change in real income over time will lead to a 0.4 to 0.6 percent change in the VSL. While elasticities within this range are supported by substantial research, they appear nonsensical if applied to populations with significantly smaller incomes. When transferring values between high and lower income countries, analysts often instead assume an elasticity of 1.0, but the resulting VSL estimates appear large in comparison to income. Elasticities greater than 1.0 are supported by research on the relationship between long-term economic growth and the VSL, by cross-country comparisons, and by new research that estimates the VSL by income quantile. Caution is needed when applying these higher elasticities, however, because the resulting VSLs appear smaller than expected future earnings or consumption in some cases, contrary to theory. In addition to indicating the need for more research, this comparison suggests that, in the interim, VSL estimates should be bounded below by estimates of future income or consumption.

The Value of a Statistical Life

2019 ◽  
Author(s):  
Thomas J. Kniesner ◽  
W. Kip Viscusi
Keyword(s):  
United States ◽  
Income Elasticity ◽  
Health And Safety ◽  
The United States ◽  
Economic Role ◽  
Statistical Life ◽  
Crucial Component ◽  
Policy Analysts ◽  
Benefit Cost ◽  
Correct Measure

The value of a statistical life (VSL) is the local tradeoff rate between fatality risk and money. When the tradeoff values are derived from choices in market contexts the VSL serves as both a measure of the population’s willingness to pay for risk reduction and the marginal cost of enhancing safety. Given its fundamental economic role, policy analysts have adopted the VSL as the economically correct measure of the benefit individuals receive from enhancements to their health and safety. Estimates of the VSL for the United States are around $10 million ($2017), and estimates for other countries are generally lower given the positive income elasticity of the VSL. Because of the prominence of mortality risk reductions as the justification for government policies the VSL is a crucial component of the benefit-cost analyses that are part of the regulatory process in the United States and other countries. The VSL is also foundationally related to the concepts of value of a statistical life year (VSLY) and value of a statistical injury (VSI), which also permeate the labor and health economics literatures. Thus, the same types of valuation approaches can be used to monetize non-fatal injuries and mortality risks that pose very small effects on life expectancy. In addition to formalizing the concept and measurement of the VSL and presenting representative estimates for the United States and other countries our Encyclopedia selection addresses the most important questions concerning the nuances that are of interest to researchers and policymakers.

The Value of the Risk to Life in the Context of Crime

2019 ◽  
Vol 10 (2) ◽  
pp. 178-205 ◽  
Author(s):  
Emilio Picasso ◽  
Mariana Conte Grand
Keyword(s):  
Negative Impact ◽  
Stated Preference ◽  
Positive Influence ◽  
Income Risk ◽  
Benefit Cost Analysis ◽  
Developed Economies ◽  
Statistical Life ◽  
Victimization Experience ◽  
Public Policy Decisions ◽  
Benefit Cost

AbstractThe value of the risk to life is a key element for benefit-cost analysis, enabling more rational public policy decisions in diverse areas as environmental, health, and crime. We value the risk to life in the context of crime using a discrete choice experiment (CE). The method has clear advantages in that it applies to the whole population and does not require vast data from labor markets, for example. Such data are not always available even in developed economies. Combining the stated preference approach with contingent valuation (CV), CE offer advantages yet to be explored in the context of crime. We demonstrate the application in a developing economy, where similar valuations are not available. The best estimate obtained for Argentina is an average of 1.5 million in 2015 US dollars per statistical life with a confidence interval ($1.1–$2.3). This result is consistent with estimates for the developed world, after appropriate transfer. We also analyze demographic factors in the risk to life, finding a positive influence of income, risk aversion, previous victimization experience and family size on the value of a statistical life, as well as a negative impact of individualism.

Publication Selection Biases in Stated Preference Estimates of the Value of a Statistical Life

2020 ◽  
Vol 11 (3) ◽  
pp. 357-379
Author(s):  
Clayton J. Masterman ◽  
W. Kip Viscusi
Keyword(s):  
Labor Market ◽  
Occupational Injuries ◽  
Stated Preference ◽  
Meta Analysis ◽  
Mean Value ◽  
Benefit Cost Analysis ◽  
Statistical Life ◽  
The Usa ◽  
Benefit Cost ◽  
Lower Income Countries

AbstractThis article presents the first meta-analysis documenting the extent of publication selection biases in stated preference estimates of the value of a statistical life (VSL). Stated preference studies fail to overcome the publication biases that affect much of the VSL literature. Such biases account for approximately 90% of the mean value of published VSL estimates in this subset of the literature. The bias is greatest for the largest estimates, possibly because the high-income labor market and stated preference estimates from the USA serve as an anchor for the VSL in other higher income countries. Estimates from lower-income countries exhibit less bias but remain unreliable for benefit-cost analysis. Unlike labor market estimates of the VSL, there is no evidence that any subsample of VSL estimates is free of significant publication selection biases. Although stated preference studies often provide the most readily accessible country-specific VSL estimates, a preferable approach to monetizing mortality risk benefits is to draw on income-adjusted estimates from labor market studies in the USA that use Census of Fatal Occupational Injuries risk data. These estimates lack publication selection effects as well as the limitations that are endemic to stated preference methods.

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