Dynamically optimized sequential WTP elicitation: Application to the age and VSL relationship

Large-scale experiments and surveys have become powerful tools for economists, measuring individual economic preferences that help explain economic behavior. However, willingness-to-pay (WTP) for public goods, derived from best-practice stated preference methods, typically relies on response variations to estimate population average preferences. We develop a new WTP elicitation method based on information theory and Bayesian updating that dynamically optimizes bids for a series of binary choices and independently elicits each participant’s WTP while collecting responses. We conduct an online survey experiment with over 1400 adults aged 20 to 79 in Japan to explore the relationship between age and the value of a statistical life (VSL) in a pandemic context at the individual level. First, Monte Carlo simulations demonstrate that our adaptive method can provide accurate individual-level estimates of WTP with fewer questions than traditional non-adaptive methods. These estimates are highly correlated with “true” values, even at the extremes of WTP. Second, the VSL estimate among adults does not decrease with age, as sometimes seen in the literature; instead, it hits its lowest point in their 30s and 40s, then increases with age, even after controlling for a comprehensive set of covariates. Third, economic preferences are strongly associated with VSL. Participants who are loss tolerant, present biased, and prosocial tend to have a higher VSL on the intensive margin. Risk-averse, impatient, and selfish participants are more likely to have zero WTP on the extensive margin.