Conference Agenda

Flood exposure in the United States continues to rise, yet household-level evidence on how individuals perceive these risks and choose among available adaptation measures remains limited. To address this gap, we utilize a Basket-Based Choice Experiment (BBCE) approach that captures a broad set of substitution and complementarity patterns across flood adaptation actions, integrating household perceptions and objective risk indicators. We find that most action pairs exhibit positive and statistically significant complementarities: adopting one measure increases the likelihood of adopting others, even after controlling for risk and perception factors. Marginal effects show that these complementarities are large relative to the low baseline adoption rates observed in the sample. Homeowners tend to favor measures they view as effective, feasible, and appropriate to their level of flood risk, with subjective and objective indicators varying in predictive relevance across behaviors. Overall, our results indicate that households commonly adopt adaptation measures as complementary bundles rather than as isolated actions.

Widely applied in empirical work, the hedonic approach offers a means of valuing public goods that otherwise have no explicit market price. These valuations become inaccurate when housing markets are too broadly defined, however. We introduce a novel approach that allows practitioners to empirically assess the severity of this issue in any hedonic application, without imposing significant data requirements. Our methodology provides insight not only into the number of markets but along which boundaries to define them. We find within our application, where the implicit price for seismic risk is causally identified using the Tohoku Earthquake as a natural experiment, that housing transactions are best categorized into three submarkets defined across commuting time to central Tokyo. More importantly, this specification is statistically preferred and yields aggregate valuations that are 21.6% ($650 million) less relative to the restrictive single-market approach.

Tropical cyclones increasingly pose severe threats to public health, with recent seasons producing storms that are more intense, persistent, and destructive than historical averages. These events contribute to a range of health impacts, including infectious and parasitic diseases, water- and vector-borne illnesses (e.g., cholera, typhoid, diarrhoea), etc. One of the most affected regions is the Sundarbans in Bangladesh, which has endured a series of devastating cyclones over the past decade. Based on original surveys conducted with 400 households in four upazilas in Khulna, this study employs a non-monetary risk-risk trade-off valuation method to assess individual preferences regarding reductions in cyclone-related morbidity risks. Results reveal a strong context premium: relative to preventing traffic-related injuries – a widely used benchmark in the risk-risk trade-off literature – respondents value preventing cholera from cyclone exposure 1.3 times more and typhoid prevention 1.5 times more. Based on these, we estimate the Value of Prevented Illness (VPI) at £2.7 million for cholera and £2.1 million for typhoid in the Bangladeshi context. Transferred values of VSLY (proxies for Disability Adjusted Life Years (DALYs)) for Bangladesh for cholera, typhoid and diarrhoea range around half of the VPI values, from £888,000 to £1.15 million. These findings underscore the urgency of targeted public health interventions in cyclone-prone regions.

Coastal zones, particularly in developing countries, are highly vulnerable to climate change impacts, including sea-level rise and flooding. Decisions on flood mitigation involve choices among grey infrastructure, green solutions, and hybrid approaches, each with different implications for livelihoods and land use. However, evidence on preferences for flood mitigation measures in developing countries is limited. This study uses a discrete choice experiment to investigate household preferences for flood mitigation in coastal communities of Bayelsa State, Nigeria, a region highly exposed to flooding and dependent on coastal resources. We examine preferences for flood infrastructure types (grey, green, or hybrid), land-use restrictions, and agencies responsible for flood management. Mixed logit and latent class models are used to analyse preferences and preference heterogeneity. In contrast to many studies in developed-country contexts, our results show a significant household preference for grey and hybrid infrastructure over green solutions. We also find support for basic coastal development restrictions and trust in regional institutions, rather than NGOs or a flood committee (comprising regional, local, and NGO representatives), to manage flood protection. We observe significant heterogeneity in preferences across respondents' cultural, occupational, and sociodemographic characteristics. The latent-class model identifies two distinct groups: one that strongly prioritizes flood protection and is less cost-sensitive, and another that is more cost-sensitive but resistant to extensive development restrictions. The findings suggest that public acceptance of flood-mitigation policies in vulnerable coastal regions depends not only on the type of protection provided but also on local livelihoods, cultural factors, and trust in the implementing institutions.