Conference Agenda

In November 2022 we surveyed 1,500 adults in the UK, asking them about their willingness to pay (WTP) to avoid the symptoms of depression and lower back pain using a two-way payment ladder approach. An important feature of that study was that respondents appeared to value mental and physical health outcomes differently, even as their WTP appeared to be proportional to variations in the severity and duration of the condition. Analysis of motivation appeared to suggest that perceived lack of access to effective treatment for mental health conditions may explain in part this variation.

In July 2025 we conducted a second wave of this survey with a larger sample of 4,000 UK adults, but extended the methodology to add more health outcomes (obesity and anxiety) and to test WTP using an alternative, dichotomous choice elicitation method. Results from this second wave indicate the same responsiveness to the scope and duration of disease, and again appear to rate the quality of life impact of depression as larger than lower back pain. Overall WTP values per case are slightly higher than those found in our earlier study. Obesity is valued similarly to depression, whereas anxiety is valued the lowest of the four conditions. Overall mental health conditions are valued similarly to physical health conditions, but this is not consistent with the magnitude of the impact on quality of life. Responses suggest that preferences are influenced by perceptions of some conditions as only treatable through personal agency.

Empirical evidence on whether individuals are willing to pay more for private or public measures to reduce mortality risk is mixed. We extend the standard value of a statistical life (VSL) model by incorporating (i) altruistic preferences for others and (ii) perceived effectiveness of a measure. We use an online survey experiment with 824 Japanese adults to investigate the difference between private and public measures. We obtain five main results: (1) the mean VSL is 46% higher in the private frame; (2) altruism increases willingness to pay only for public risk reductions, partially narrowing the public–private gap; (3) respondents in smaller households value the public intervention less; (4) a model-based calibration indicates that respondents view the public program to deliver only about two-thirds of the personal benefit provided by the private intervention; (5) marriage, education, patience, and loss tolerance are positively associated with VSL. These findings show that both altruistic spillovers and perceived effectiveness are essential to understanding context-dependent VSL and inform better policymaking.

Valuing climate-related mortality in Benefit-Cost Analysis is both controversial and central to the social cost of carbon. This paper examines the ethical and theoretical foundations of alternative BCA approaches applied to climate change. We show that the pure Kaldor–Hicks approach – unadjusted for diminishing marginal utility and valuing premature deaths in rich areas more than poor areas – rests on assumptions that do not hold globally and is equivalent to a Negishi-weighted social welfare function. Moreover, when costs are measured in purchasing-power-adjusted terms, the potential compensation criterion may fail. We argue that welfare-weighted BCA is the first-best approach, as it accounts for diminishing marginal utility across all costs and better reflects social welfare considerations.

I examine the causal effect of fire-induced air pollution on children’s health in India, where agricultural burning is both widespread and seasonal. Standard ap- proaches instrument air pollution exposure using wind direction and fire proximity. However, in agrarian settings like India, both fire activity and prevailing winds are highly predictable, potentially enabling behavioral avoidance and biasing causal es- timates downward. To address this, I develop a refined instrument, NetFires, which captures deviations from historical fire-wind patterns, to represent unexpected up- wind fire exposure that is less subject to anticipatory behavior.

Using geocoded data from NFHS-5 (2019–21), NASA FIRMS fire detections, ERA5 reanalysis wind fields, and high-resolution PM2.5 concentration maps, I find that one additional upwind NetFire in the final trimester leads to a 0.14-gram re- duction in birth weight (95% CI: –0.26g, –0.02g). This effect is strongest in the third trimester and is robust across alternative exposure definitions, fixed effect structures, and control specifications. Heterogeneity analysis reveals that the ad- verse effects are concentrated among rural households, poorer wealth quintiles, and female infants, highlighting environmental inequality.

Compared to conventional fire counts, the NetFires instrument yields consis- tently larger and more robust estimates, underscoring the importance of modeling exposure uncertainty. Additional robustness checks using alternative IV setups, non-upwind reclassifications, and falsification tests support the internal validity of the findings.

These results demonstrate the importance of integrating behavioral predictabil- ity into exposure modeling. NetFires offers a scalable and policy-relevant tool to identify high-risk pollution shocks in agrarian economies. The findings hold direct implications for climate-health policy, especially the design of early warning systems and protective interventions targeting pregnant women in fire-prone regions.