Conference Agenda

Economic losses from European winter storms impose a significant burden on society and are expected to increase due to exposure growth and climate change. Vulnerability functions play a key role in estimating such losses as they describe the relationship between a natural hazard’s intensity and damage to the exposed asset. This study fills an important gap in the literature by providing a vulnerability function for residential buildings which, for the first time, is able to account for damage from both the wind and the precipitation that winter storms produce. This compound vulnerability function is estimated using truncated beta regressions, and based on a large number of object-level insurance claims from The Netherlands and ultra-high resolution meteorological observations. Comparing our vulnerability function to the conventional specification, which only considers damage from wind, shows that the latter underestimates the damage by 5% [21%] {57%} for winter storms with 24-hour cumulative precipitation levels of 50 mm [75 mm] {100 mm}. Given that climate change is projected to further increase the frequency and intensity of such precipitation extremes in Europe, our study provides evidence in favor of using compound vulnerability functions to estimate future winter storm losses more accurately. Our vulnerability function can be used in natural catastrophe models to accurately estimate damage to residential buildings from European winter storms.

Agri-food systems account for one third of global anthropogenic greenhouse gas (GHG) emissions, making agricultural mitigation and adaptation strategies critical in addressing climate change. Cover cropping, a climate-smart agricultural (CSA) practice, offers several environmental benefits, including enhanced soil health, reduced nutrient runoff, and increased crop resiliency. However, adoption rates remain low due to economic and agronomic barriers. This study explores the impact of financial incentives on cover crop adoption using a discrete choice experiment (DCE) with 1,581 U.S. farmers. Three incentive attributes were tested: government grants, crop insurance premium discounts, and contract length. Results indicate that government grants are the primary driver of adoption, with significant utility gains at higher grant levels, while crop insurance discounts play a secondary role with diminishing marginal utility. Contract length had minimal influence, reflecting farmers’ aversion to long term commitments. Regional, demographic and farm variables were also measured, revealing nuanced incentive preferences for various groups. The findings highlight the importance of tailoring incentives to demographic and regional variations. The study provides actionable policy recommendations for optimising large-scale agricultural programs like the Common Agricultural Policy (CAP) in the E.U. and the Farm Bill in the U.S. to promote CSA, contributing to broader goals of emissions reduction, climate resilience, and agricultural sustainability.

When consumers prefer to buy goods with high environmental quality and firms differ in their environmental qualities, firms have incentives to fight over environmental salience and thereby influence consumers' attention to the environmental dimension of the goods. A green firm prefers environmental quality to be salient, while a brown firm prefers environmental quality to remain shrouded. We model the firms' fight over salience as an advertising contest. We show that such a contest increases social welfare if firms are sufficiently environmentally differentiated and marginal damages from emissions are sufficiently large. In addition, we analyze the impact of emission taxes and subsidies for clean production on social welfare. We show that full internalization of the external effects is not always optimal; a range of situation exists where partial or no internalization is optimal.

We assess how changes in the scientific consensus around equilibrium climate sensitivity (ECS), as captured by the IPCC’s Fifth (AR5) and Sixth (AR6) Assessment Reports, impact policymakers’ willingness to take climate action, including through increasing subsidies to investments that will help to deliver the clean energy transition. Taking the IPCC’s reports at face value, the ECS estimates in AR6 would have lowered a policymaker’s willingness to act on climate relative to AR5 due to a narrower “likely” range. However, Bayesian updating may reverse this conclusion. An accuracy-motivated policymaker who was not convinced to take greater climate action by the evidence in AR5 may be more likely to increase their investment in clean energy by the evidence in AR6.

The residential sector stands out as the main sector where energy consumption directly hinges on individual household decisions which are said to be wildly influenced by climate conditions, particularly temperature. This study focuses on aggregated electricity demand as the sum of these parts: given the occurrence of an increase in the use of cooling devices to adapt to the hotter weather, especially by residential users, what is explored is the effect of temperature on electricity demand. The analysis investigates the existence of a specific shape of the daily load curve suspected to verify as a lagged response to daily temperatures: persistence. While the link between temperature and electricity consumption is broadly established, this analysis focuses on hourly electricity load data in Italy from 2015 to 2020, incorporating distributed lag structures to capture the delayed impact of temperatures. Specifically, the econometric analysis firstly confirms the extant literature by finding evidence of a U-shaped relationship, with temperatures associated with the cooling state having a stronger impact on aggregate electricity demand. But more notably, a persistence effect is identified, wherein electricity consumption remains prolonged for several hours after the occurrence of (high)

temperatures. Not only a contemporaneous effect is found to be significant - with decreasing magnitude the more a lag is far in time - but the cumulative effect of past temperature is supported to be stronger than the pooled effect, the current temperature effect on the current electricity demand. This result supports how much an external stimuli received in the past, even more the sum of all of them, may influence the current aggregated load trend; in that, it carries significant implications for energy policy and grid stability. Recognizing and accounting for lagged electricity demand responses in energy planning can improve power system balance through demand-side management and can also guide investments in energy-efficient cooling solutions. Indeed, even though this study is not intended at uncovering the reasons underlying this particular load shape, the analysis suggests that to the increasing ownership of air conditioning units cannot be attributable the persistence effect, rather to their intensive use. Indeed, while electricity demand is found to be sensitive to moderate temperature changes with high air conditioning penetration, at extreme heat levels a low marginal increase in demand due to ownership is experienced.

Reducing dietary emissions is critical for climate mitigation. Replacing beef with alternative proteins can align diets with sustainability goals, ensure nutritional adequacy, and yield health co-benefits. However, as food choices are intertwined with identity, cultural traditions, and social norms, understanding their influence on beef consumption is essential. Using survey data from six European countries, we investigate drivers of beef consumption and identify barriers and enablers to its reduction. Our analysis reveals a significant gap between perceived social norms and actual beef consumption levels, indicating the potential for reductions through correcting norm misperceptions. The findings highlight the need for food demand policies sensitive to institutional and cultural contexts to maximize their effectiveness in promoting sustainable diets.