Université Paris-Dauphine, PSL Research University, LEDa (CGEMP) UMR CNRS, 8007, France.
Risk Management Directorate, European Chemicals Agency (ECHA), Finland.
J Health Econ. 2022 Jul;84:102627. doi: 10.1016/j.jhealeco.2022.102627. Epub 2022 May 13.
Many stated-preference studies that seek to estimate the marginal willingness-to-pay (WTP) for reductions in mortality or morbidity risk suffer from inadequate scope sensitivity. One possible reason is that the risk reductions presented to respondents are too small to be meaningful. Survey responses may thus not accurately reflect respondents preferences for health and safety. In this paper we propose a novel approach to estimating the value per statistical life (VSL) or the value per statistical case (VSC) based on larger risk reductions measurable as percent changes. While such non-marginal risk reductions are easier to understand, they introduce well known biases. We propose a methodology to de-bias VSL and VSC estimates derived from the evaluation of non-marginal risk reductions and present a proof of concept using simulated stated preference data.
许多旨在估计降低死亡率或发病率风险的边际意愿支付(WTP)的陈述偏好研究都存在范围敏感性不足的问题。一个可能的原因是,向受访者提供的风险降低幅度太小,没有意义。因此,调查结果可能无法准确反映受访者对健康和安全的偏好。本文提出了一种基于可衡量的百分比变化的较大非边际风险降低来估计每统计生命价值(VSL)或每统计病例价值(VSC)的新方法。虽然这种非边际风险降低更容易理解,但它们会引入众所周知的偏差。我们提出了一种从非边际风险降低评估中消除 VSL 和 VSC 估计偏差的方法,并使用模拟陈述偏好数据进行了概念验证。