Conference Agenda

Publicly available fast charging capacity along highways is needed for electric vehicles to provide a similar long-distance travel service as combustion engine cars currently do. We use household-level data on battery electric vehicle adoption and long-distance routes that households are likely to regularly travel, and examine the effect of fast public charging along long-distance routes on EV adoption. We find that charging station density, measured by clusters of stations or a maximum distance between stations, is a strong driver of EV adoption. Introducing one additional charging station cluster, defined as stations within 10 kilometers of each other, or decreasing the maximum distance between stations by 10 kilometers both increase EV adoption by around 9 percent relative to the average adoption rate in the sample.

This paper examines how wildfire smoke exposure affects road safety in Alberta. Combining satellite-based smoke plume data with municipality-day accident records from 2016 to 2022, I find that accident incidents rise on low- and medium-smoke days but fall sharply on heavy-smoke days. Traffic volume data show that vehicle counts remain unchanged when smoke is light yet decline substantially under heavy smoke, indicating that people avoid driving only when conditions are visibly severe. These patterns suggest that on low-smoke days, drivers continue their usual travel but may experience reduced cognitive performance, leading to more accidents even though they do not perceive a risk. The results highlight an overlooked behavioral cost of wildfire smoke exposure and underscore the need for public awareness that smoke can impair cognition and driving safety even when it is not readily perceptible.

"Can development be decoupled from carbon emissions where investments actually land? To address this question, I use development-finance portfolios as a laboratory: projects arrive at different times, intensities, and sectors across locations, generating variation in local exposure. I compile a global ADM2-year panel (2000–2023) linking geocoded development projects to local CO2 emissions and night-time lights. To measure climate finance consistently across donors, I classify project description using natural language processing techniques into mitigation, adaptation/environment, and non-climate flows. Exploiting staggered project arrival with not-yet-treated difference-in-differences and a dose–response design, I find that climate portfolios generate modest average emissions reductions, with effects becoming meaningfully more negative only at higher cumulative exposure. In contrast, non-climate development finance raises local emissions in the medium run. Night-time lights indicate visible expansion in mid-brightness regions, while lights are muted in already bright places even as emissions rise, consistent with compositional shifts and lighting/land-use changes. Disaggregating climate finance highlights solar and environment protection as “win–win” investments where lights increase while emissions fall, implying that decarbonization requires both scaling effective climate finance and greening mainstream development spending."

Public investments in disaster mitigation may crowd out demand for insurance. We measure the extent of substitution between flood-mitigating infrastructure and public flood insurance. Using a novel dataset of U.S. levee provision, we find that levee construction lowers flood risk and reduces insurance take-up by 61%, removing $300 million in coverage. Levee accreditation, which reduces premiums and lifts mandatory purchase requirements, offsets part of this decline, recovering $160 million in coverage. The net positive effect of accreditation indicates that premium reductions affect insurance take-up more than the removal of the mandate. Through a back-of-the-envelope calculation, we estimate that each levee-mile reduces household financial exposure by over $1 million, which could only otherwise be achieved by a much higher insurance take-up rate.

While fertility decline’s climate implications spark considerable discussion, causal evidence on the fundamental relationship between fertility and emissions remains limited. I examine how household composition, an underexplored aspect in environmental economics, affects carbon footprint through consumption pattern changes. I document a concave relationship between household carbon footprint and the number of children using the U.S. Consumer Expenditure Survey. Using instrumental variables based on twin births and same-sex sibling composition, I find that an additional child increases household carbon emissions by only 10-20% of average per-capita emissions. This small effect emerges from economies of scale through two channels. First, while carbon-intensive expenditures rise with additional children, household consumption sharing makes proportional scaling inappropriate. Second, families with more children substitute away from some carbon-intensive expenditures such as air travel. I formalize the carbon footprint impact of household composition through a household consumption model. Back-of-the-envelope calculations using empirical estimates suggest that ignoring household composition

leads to a 23% overestimation of lifetime emission reductions resulting from fertility decline. Meanwhile, decarbonization can achieve far larger reductions (36-61%) in lifetime emissions compared to the household composition effect. These results underscore the importance of considering household composition in climate policy design, particularly for carbon pricing and fertility-related interventions.

Public support for climate policies is key to ensuring their successful implementation. However, there is a trade-off between implementing an early, ambitious policy that can deliver rapid results, and gradual scaling up to ensure initial acceptance. This is particularly true for urban policies, which can generate visible co-benefits but also uneven welfare impacts across spatial and income groups. We examine this dynamic process for an urban toll in Barcelona. To this end, we combine a spatially-explicit policy-impact model and a public-support model calibrated using original survey data. We find that, despite high initial resistance, inhabitants strongly value the policy's benefits in terms of reduced emissions and improved quality of life. This enables gradual strengthening of the toll and a reinforcing cycle between stringency and acceptability. In our baseline scenario, the toll converges to €3.6, reducing transport emissions by 12.7% and pollution inside and outside the zone by 16.7% and 8.3%, respectively. We also explore alternative policy designs, notably exemptions and revenue recycling.

Like other large lakes in the Alps and around the world, lake Geneva’s socio ecological system faces increasing pressures as climate change reduces the frequency of full lake mixing, heightening the release of sediment bound phosphorus and the risk of harmful algal blooms. These blooms threaten biodiversity and essential ecosystem services, including bathing, drinking water, and fisheries. Managing bloom risk therefore requires navigating difficult trade offs between competing services. We implement a discrete choice experiment in France and Switzerland to assess how individuals value these trade offs. The results show that most respondents prioritise the protection of fishing activity, but others place greater emphasis on maintaining recreational access. Preferences are heterogeneous across groups, reflecting diverse valuations of the lake’s ecosystems-services. Cost remains insignificant, preventing reliable willingness to pay estimation. By revealing these differentiated priorities, this working paper provides early insights to support the development of sustainable and socially acceptable management strategies for Lake Geneva under increasing bloom risk in a changing climate.