an hour of running statistically lengthens life expectancy by seven hours, the researchers report.
The Benefits of Avoiding Cancer (or Dying from Cancer): Evidence from a Four-Country Study by Anna Alberini, Milan Ščasný :: SSRNFebruary 12, 2017
We use stated-preference methods to estimate the cancer Value per Statistical Life (VSL) and Value per Statistical Case (VSCC) from a representative sample of 45-60-year olds in four countries in Europe. We ask respondents to report information about their willingness to pay for health risk reductions that are different from those used in earlier valuation work because they are comprised of two probabilities — that of getting cancer, and that of dying from it (conditional on getting it in the first place). The product of these two probabilities is the unconditional cancer mortality risk. Our hypothetical risk reductions also include two qualitative attributes — quality-of-life impacts and pain. The results show that respondents did appear to have an intuitive grasp of compound probabilities, and took into account each component of the unconditional cancer mortality risk when answering the valuation questions. We estimate the cancer VSL to be between € 1.9 and 5.7 million, depending on whether the (unconditional) mortality risk was reduced by lowering the chance of getting cancer, increasing the chance of surviving cancer, or both. The VSCC is estimated to be up to € 0.550 million euro, and its magnitude depends on the initial (conditional) cancer mortality and on the improvement in survival. We interpret these as “pure” mortality and cancer risk values, stripped of morbidity, pain or quality-of-life effects. The survey responses show that impacts on daily activities and pain have little or no effect on the WTP to reduce the adverse health risks.
Economists discount future benefit and cost flows for a variety of reasons, including time preference, diminishing marginal utility of consumption, opportunity cost of capital, and risk aversion. Many of these rationales for discounting can be explained using the Ramsey equation found in neoclassical growth theory. This paper argues that Ramsey approaches to discounting are problematic for use in regulatory benefit-cost analysis (BCA) because they are inconsistent with certain foundational principles of BCA. A more useful discounting framework is one that is based on the time value of money, where discounting is used as a way to compare investment projects to a baseline alternative investment. A social discount rate (SDR) used in this manner avoids many ethics controversies that arise in Ramsey discounting approaches with respect to giving preferential treatment to the present generation over future generations, but it still recognizes and accounts for the importance of economic growth. An SDR of about 7 percent appears to be reasonable and is consistent with current guidelines from the Office of Management and Budget.
Anchoring Biases in International Estimates of the Value of a Statistical Life by W. Kip Viscusi, Clayton J. Masterman :: SSRNJanuary 18, 2017
U.S. labor market estimates of the value of a statistical life (VSL) were the first revealed preference estimates of the VSL in the literature and continue to constitute the majority of such market estimates. The VSL estimates in U.S. studies consequently may have established a reference point for the estimates that researchers analyzing data from other countries are willing to report and that journals are willing to publish. This article presents the first comparison of the publication selection biases in U.S. and international estimates using a sample of 68 VSL studies with over 1,000 VSL estimates throughout the world. Publication selection biases vary across the VSL distribution and are greater for the larger VSL estimates. The estimates of publication selection biases distinguish between U.S. and international studies as well as between government and non-government data sources. Empirical estimates that correct for the impact of these biases reduce the VSL estimates, particularly for studies based on international data. This pattern of publication bias effects is consistent with international studies relying on U.S. estimates as an anchor for the levels of reasonable estimates. U.S. estimates based on the Census of Fatal Occupational Injuries constitute the only major set of VSL studies for which there is no evidence of statistically significant publication selection effects. Adjusting a baseline biasadjusted U.S. VSL estimate of $9.6 million using estimates of the income elasticity of the VSL may be a sounder approach to generating international estimates of the VSL than relying on direct estimates from international studies.
nd investigates its source. Compared to individuals with a college education, those with at most a high school diploma are more than four times as likely to die in a traffic accident, a gradient exceeding that for all-cause mortality. More educated individuals’ health behaviors, such as drinking or seat belt use, support this gradient. A panel analysis of data from the Fatality Analysis Reporting System indicates that this gradient is, to a small degree, causal, particularly for males, who cause most traffic accidents.
When an industry poses a risk of premature death to consumers, workers, or others, regulatory agencies employ a figure known as the “value of a statistical life” (VSL) to monetize the life-saving benefit of regulations designed to reduce that risk. Use of the VSL, which currently hovers around $9 million, has been highly controversial. While a number of prominent scholars have vigorously endorsed the VSL as necessary to the cost-benefit analysis of mortality risk regulations, other prominent scholars have vehemently rejected the very idea of attaching a monetary value to a statistical human life.
This article stakes out a more nuanced position based on a largely neglected aspect of mortality risk regulation: moral context. Whether and how the VSL is used to guide mortality risk regulation should depend on two morally significant features of the particular risk imposition in question: (i) the extent to which those exposed to the risk benefit from the industrial activity that gives rise to the risk and (ii) the extent to which those exposed to the risk bear the costs of compliance with the risk-reducing regulation. These two features vary in characteristic ways depending on the type of risk imposition at issue.
Consumption risks — risks of death associated with using or con-suming a particular product — typically fall on consumers who not only benefit meaningfully from the industry but who also bear all or sub-stantially all of the costs of risk-reducing regulations. Using a VSL to guide risk regulation in this moral context is defensible on the basis of the norm of personal autonomy. By contrast, workplace risks — risks of death associated with employment in a particular industry — typically fall on workers who benefit from the industry but who do not bear the costs of risk-reducing regulations. In this moral context, using a VSL to guide risk regulation is not normatively defensible. However, using the underlying economic concept of willingness-to-pay to guide the regulation of workplace mortality risks is defensible on the basis of the norm of equity.
A Cohort is Not Representative of Humanity: Review of ‘Evidence for a Limit to Human Lifespan’ by Ilya Kashnitsky :: SSRNNovember 8, 2016
In the freshly published research letter, Dong, Milholland, and Vijg (DMV) reported that they found strong evidence for a limit to human lifespan. Analyzing data from International Database on Longevity2, they found that the yearly maximum reported age at death (MRAD, i.e. age at death of the world’s oldest person died in a specific year) stopped increasing from the mid-1990-s reaching a plateau at around 115 years. Even though the authors acknowledge that the data on “the supercentenarians are still noisy and made of small samples”, they feel safe to conclude that “the results strongly suggest that the human lifespan has a natural limit”. I argue that the results and conclusions of the study are likely to be caused by just a data artifact, and that they are hardly generalizable for the humanity.