Survival First: How Citizens Prioritize Competing Climate-Health Risk Countermeasures Under Fiscal Constraints.

When governments must allocate limited resources among competing climate-health countermeasures, citizen risk priorities determine political feasibility-yet whether those priorities translate into fiscal support remains poorly understood. This study develops a hybrid best-worst scaling and contingent valuation framework that integrates individual-level priority parameters into an acceptance model, enabling direct testing of whether preference intensity predicts willingness to pay. Applied to a large-sample survey of residents in Yokohama, Japan-a rapidly aging metropolis facing escalating heat emergencies-the analysis reveals three findings. First, citizens exhibit a survival-first hierarchy, decisively prioritizing immediate protective measures over long-term structural interventions, with consensus varying sharply across countermeasure types. Second, a systematic priority-WTP disconnect emerges: The priority parameters for the most valued measures show no statistically detectable association with acceptance of the proposed payment, consistent with a possible entitlement interpretation in which life-saving services are perceived as government obligations rather than goods warranting additional taxation, while a group of lower-ranked supplementary measures is jointly associated with greater fiscal support. Third, chronic quality-of-life burdens-particularly sleep disruption-are more consistently associated with willingness to pay than are acute health symptoms, while private cooling costs are negatively associated with support for public adaptation, consistent with a crowding-out mechanism that may pose a regressive barrier to equitable financing. These findings suggest that preference intensity and fiscal support may operate through partially distinct evaluative pathways, implying that standard valuation methods relying on willingness to pay alone can systematically misrepresent the structure of public risk priorities.