Demand for health risk reductions

Cameron, Trudy Ann; DeShazo, J.R.

doi:10.1016/j.jeem.2012.05.008

Cited by 90 publications

(58 citation statements)

References 57 publications

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“…More recent research by Cameron and DeShazo (2013) recognises the heterogeneity of fatality risk scenarios and explicitly addresses latency and morbidity in a choice experiment where the scenarios vary along these dimensions. Their results suggest that both latency and morbidity are important in explaining the VSL, with longer morbidity prior to fatality engendering higher WTP to avoid the risk than shorter morbidity, and that for older members of the sample, VSL for latent fatality is lower than for more immediate fatality risks.…”

Section: Context Latency and Cancer Risksmentioning

confidence: 99%

Dread and latency impacts on a VSL for cancer risk reductions

et al. 2016

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We propose a structural relationship between the value of preventing a statistical cancer fatality and the value of statistical life (VSL) for risks of an instantaneous road accident fatality. This relationship incorporates a context effect reflecting both the illness or 'morbidity' associated with cancer fatality and the 'dread' or horror associated with the prospect of eventual death from cancer, as well as a latency effect that captures the discounting likely to arise because the onset of the symptoms of cancer typically occurs after some delay. We use a Risk-Risk trade-off study to validate this model by directly estimating the influence of context and latency effects upon the relative size of the VSL for cancer and for road accidents, confirming that both effects are significant and estimating their size using regression analysis. We show that morbidity accounts for the majority of the context premium. We use the elicited coefficients to reconstruct VSL estimates for a range of cancers characterised by their latency and morbidity periods.

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Section: Context Latency and Cancer Risksmentioning

confidence: 99%

Dread and latency impacts on a VSL for cancer risk reductions

et al. 2016

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“…2 Costa and Kahn [2004] estimate an income elasticity for the VSL of about 1.5 and Kniesner et al [2010] estimate income elasticities greater than 1.0 from hedonic labor market analyses, although meta-analyses by Viscusi and Aldy [2003], Mrozek and Taylor [2002], and Liu and Liu [1997] produce income elasticities in the 0.4 and 0.6 range and Cameron and DeShazo [2013] estimate an income elasticity of about 0.7 based on a stated preference survcey. Viscusi [2004] and Leeth and Ruser [2003] estimate larger VSLs for whites than for blacks in the labor market.…”

Section: Introductionmentioning

confidence: 99%

“…1 In revealed preference and stated preference studies, Aldy and Viscusi [2008], Viscusi and , Kniesner et al [2006], Cameron and DeShazo [2013], and Krupnick [2007] nd that the VSL generally takes an inverted-U shape over the life cycle.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity in the Value of Life

Aldy¹,

Smyth²

2014

SSRN Journal

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We develop a numerical life-cycle model with choice over consumption and leisure, stochastic mortality and labor income processes, and calibrated to U.S. data to characterize willingness to pay (WTP) for mortality risk reduction. Our theoretical framework can explain many empirical ndings in this literature, including an inverted-U life-cycle WTP and an order of magnitude dierence in prime-aged adults WTP. By endogenizing leisure and employing multiple income measures, we reconcile the literature's large variation in estimated income elasticities. By accounting for gender-and race-specic stochastic mortality and income processes, we explain the literature's black-white and female-male dierences. JEL codes: J17, D91, Q51

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“…4 This suggests that there are two key metrics of interest for policy analysis purposes-the cancer VSL and the Value of a Statistical Case of Cancer (VSCC). Second, we wish to see if the quality-of-life and pain impacts of cancer affect risk valuation, as in Cameron and DeShazo (2013), Chilton et al (2016) and Hammitt and Haninger (2017), and, if so, what the magnitude of their effect is compared to that from cancer risk or mortality risk alone.…”

Section: Introductionmentioning

confidence: 99%

“…Policymakers cannot possibly have information about the course of illness, recovery, relapse, and duration and severity of symptoms as in Cameron and DeShazo (2013) or Chilton et al (2016), and for this reason they cannot use benefit-cost analysis metrics that rely on individual, ex-post outcomes and the associated values. Our results suggest that even if they did, conditioning on them would make little or no difference with respect to using more "stylized" ex ante values.…”

Section: Introductionmentioning

confidence: 99%

The benefits of avoiding cancer (or dying from cancer): Evidence from a four- country study

Alberini

Ščasný

2018

Journal of Health Economics

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Abstract. 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.

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Demand for health risk reductions

Cited by 90 publications

References 57 publications

Dread and latency impacts on a VSL for cancer risk reductions

Dread and latency impacts on a VSL for cancer risk reductions

Heterogeneity in the Value of Life

The benefits of avoiding cancer (or dying from cancer): Evidence from a four- country study

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