Cost vector effects in discrete choice experiments: Implications for the value of statistical life

This study investigates how the design of the cost attribute shapes stated preference estimates of the value of a statistical life (VSL). Using a discrete choice experiment (DCE) on willingness to pay (WTP) for cardiovascular mortality risk reductions, we implement a randomized design that varies the cost vector across three treatments, allowing us to compare monetary vectors that differ jointly in their range and spacing. Complementary diagnostics examine scope sensitivity and potential anchoring effects induced by information disclosure and feedback mechanisms. Point estimates of VSL differ by up to roughly 25% across treatments, but the reported between-treatment comparisons are not statistically significant. These results establish neither a detectable VSL effect nor equivalence across treatments. This contrast carries direct policy implications, since cost-benefit analyses and health regulations typically rely on point estimates of VSL rather than full distributions. Secondary diagnostics indicate less-than-proportional WTP scaling over the tested risk increments, while anchoring stimuli (revealing all attribute levels upfront, ordering cost levels from extremes, or providing feedback on comprehension questions) exert no detectable influence on choices or WTP. Taken together, the results highlight the need for clearer methodological guidance on cost attribute selection in stated preference research and underscore that seemingly modest design choices can shift welfare estimates in ways that are consequential for policy appraisal, while accounting for estimation uncertainty.