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

2019 ◽  
Author(s):  
Clayton Masterman ◽  
W. Kip Viscusi
Keyword(s):  
Stated Preference ◽  
Statistical Life

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.

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.

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.

scholarly journals Building a Set of Internationally Comparable Value of Statistical Life Studies: Estimates of Chinese Willingness to Pay to Reduce Mortality Risk

2017 ◽  
Vol 8 (2) ◽  
pp. 251-289 ◽  
Author(s):  
Sandra Hoffmann ◽  
Alan Krupnick ◽  
Ping Qin
Keyword(s):  
United States ◽  
Willingness To Pay ◽  
Mortality Risk ◽  
Stated Preference ◽  
The United States ◽  
Value Of Statistical Life ◽  
Middle Income ◽  
Payment Card ◽  
Statistical Life ◽  
Chinese Study

This study is the eighth in a series of stated-preference studies designed to enhance the basis for international benefits transfer of value of statistical life (VSL) estimates. The series has fielded essentially similar stated-preference surveys in Canada, China, France, Italy, Japan, Mongolia, the United Kingdom, and the United States. This Chinese study estimates the willingness to pay for contemporaneous and future mortality risk reductions of residents of Shanghai, Jiujiang, and Nanning, China using a stated-preference payment-card survey. The pooled VSL for a contemporaneous reduction in annual mortality risk reduction of 5 in 10,000 is about 1.47 million 2009 yuan ($614,805 U.S. $2016), with income elasticities of 0.2 to 0.25. This VSL estimate is at the lower end of estimates from the eight countries, between those from Mongolia and Japan, and in the mid-range of estimates of willingness to pay (WTP) for mortality risk reductions as a percentage of household income. We find lower discount rates in the Mongolia, Japan, and China studies than in those fielded in North America or Europe. The study also explores the relative performance of dichotomous choice and stated-preference card elicitation methods in a middle income country setting and develops a computerized “payment card” that allows testing for anchoring. Implicit transfer elasticities across countries, calculated using the VSLs we estimate and each country’s income, relative to those of the United States, yields estimates of 0.88–0.95 for the lower income countries. These compare with the default assumption of 1.0 or assumed elasticities of 1.2 for developing countries.

scholarly journals Value of statistical life year in extreme poverty: a randomized experiment of measurement methods in rural Burkina Faso

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Stefan T. Trautmann ◽  
Yilong Xu ◽  
Christian König-Kersting ◽  
Bryan N. Patenaude ◽  
Guy Harling ◽  
...  
Keyword(s):  
Low Income ◽  
Stated Preference ◽  
World Health ◽  
Randomized Experiment ◽  
Low Literacy ◽  
Extreme Poverty ◽  
Statistical Life ◽  
Literacy Communities ◽  
Parameter Measuring ◽  
Health Organization

Abstract Background Value of a Statistical Life Year (VSLY) provides an important economic measure of an individual’s trade-off between health risks and other consumption, and is a widely used policy parameter. Measuring VSLY is complex though, especially in low-income and low-literacy communities. Methods Using a large randomized experiment (N = 3027), we study methodological aspects of stated-preference elicitation with payment cards (price lists) in an extreme poverty context. In a 2 × 2 design, we systematically vary whether buying or selling prices are measured, crossed with the range of the payment card. Results We find substantial effects of both the pricing method and the list range on elicited VSLY. Estimates of the gross domestic product per capita multiplier for VSLY range from 3.5 to 33.5 depending on the study design. Importantly, all estimates are economically and statistically significantly larger than the current World Health Organization threshold of 3.0 for cost-effectiveness analyses. Conclusions Our results inform design choice in VSLY measurements, and provide insight into the potential variability of these measurements and possibly robustness checks.

OP95 An Update On The Economic Value Of A Statistical Life Year In Europe

2017 ◽  
Vol 33 (S1) ◽  
pp. 44-44
Author(s):  
Michael Schlander ◽  
Ramon Schaefer ◽  
Oliver Schwarz
Keyword(s):  
Stated Preference ◽  
Statistical Significance ◽  
Economic Value ◽  
Consumer Price Index ◽  
Revealed Preference ◽  
Reference Value ◽  
Original Data ◽  
Quality Adjusted Life Year ◽  
Statistical Life ◽  
Data Capturing

INTRODUCTION:Evaluation of “value for money” is an important component of Health Technology Assessments (HTAs). It is often conceptualized as “cost effectiveness” or cost per (quality-adjusted) life year gained. Whether used in isolation or alongside further drivers of social value (such as priority for younger or more severely impaired patient groups, or for access to effective treatment, even if costly), for example within a multi-criteria decision analysis framework, any reference “value of a statistical life year” (VSLY) should be supported by empirical data capturing the preferences of the population(s) in question. Here we report results based on a systematic review of relevant European economic studies, which were published during the last two decades, that is, from 1995 to 2015.METHODS:Our literature search (using the EconBiz and EconLit databases, supplemented by an analysis of relevant reviews) identified fourty-one European studies providing original data, yielding a total of fourty-eight average estimates for the value of a statistical life (VSL, or fatality prevented). We classified studies by methodology, for example, revealed preference (RP) or stated preference (contingent valuation, CV; discrete choice experiment, DCE) approach. We transformed VSL estimates into VSLY expressed in year 2014 Euros, using the life expectancy of the populations studied, a real discount rate of 3 percent, the national Consumer Price Index (CPI) for inflating, and purchasing power parities for currency conversion. We calculated confidence intervals by means of nonparametric bootstrapping.RESULTS:The median VSLY was EUR158,000 (for RP studies, EUR218,000; DCE, EUR188,000; CV, EUR143,000); we did not identify studies using the human capital approach. Our VSLY estimates showed large heterogeneity, both by methodology and regional origin; thus the differences that we observed did not reach statistical significance.CONCLUSIONS:Our results suggest that the empirical willingness-to-pay for a statistical life year might be substantially higher than benchmarks currently used by the international HTA community.

Analisa Pemilihan Moda Transportasi Umum Rute Tanjung Karang – Bandara Radin Inten II Dengan Stated Preference dan Uji Crame’s V

2018 ◽  
Vol 2 (2) ◽  
pp. 137
Author(s):  
Muhammad Abi Berkah Nadi
Keyword(s):  
Regression Analysis ◽  
Utility Function ◽  
Stated Preference ◽  
Technical Analysis ◽  
Chi Square ◽  
Time Headway ◽  
Independent Variable ◽  
The Relationship ◽  
Selection Of

Radin Inten II Airport is a national flight in Lampung Province. In this study using the technical analysis stated preference which is the approach by conveying the choice statement in the form of hypotheses to be assessed by the respondent. By using these techniques the researcher can fully control the hypothesized factors. To determine utility function for model forecasting in fulfilling request of traveler is used regression analysis with SPSS program. The analysis results obtained that the passengers of the dominant airport in the selection of modes of cost attributes than on other attributes. From the result of regression analysis, the influence of independent variable to the highest dependent variable is when the five attributes are used together with the R square value of 8.8%. The relationship between cost, time, headway, time acces and service with the selection of modes, the provision that states whether or not there is a decision. The significance of α = 0.05 with chi-square. And the result of Crame's V test average of 0.298 is around the middle, then the relationship is moderate enough.

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