Conference Agenda

Why do some local economies rebound from destructive shocks while others fall into persistent decline? We study how large-scale physical destruction reshapes spatial economic dynamics by linking over one thousand wildfires across the United States to parcel-level transactions and tax assessments. On average, disasters reduce both land and building values in the long run, but impacts vary systematically with pre-disaster local productivity. Low-productivity areas suffer enduring losses, middle-ranked areas recover quickly, and high-productivity areas experience “creative destruction,” realizing sustained gains. Nearby unburned parcels follow similar trajectories through long-lived spillovers, revealing strong spatial interdependence in recovery. These patterns show that localized destruction can either hinder, restore, or accelerate growth depending on pre-existing productivity levels. These results underscore the importance of spillovers and coordinated investment in shaping urban resilience.

The economic value of weather forecasts depends critically on how risk-averse agents incorporate forecast uncertainty relative to realized weather shocks into their decision-making. This paper investigates the safety–efficiency trade-off in air traffic control (ATC) decisions under tropical cyclones in China. Using high-frequency hourly flight trajectory data merged with real-time hourly typhoon forecasts of China, we document that physical observations of wind limits explain only a modest share of capacity reductions. Instead, aviation operational decisions exhibit pronounced behavioral asymmetry: for identical wind conditions, throughput is significantly lower when storms are approaching than receding, and flight cancellations occur well before physical conditions deteriorate beyond safety thresholds. Estimation using structural dynamic choice modeling further reveals that forecast uncertainty substantially amplifies perceived risk in the aviation industry, generating preemptive capacity suppression under forthcoming tropical cyclones beyond what physical constraints require for flight safety. Counterfactual simulations demonstrate that while reducing tropical cyclone forecast uncertainty yields efficiency gains for the aviation industry, the magnitude is constrained by the inherently conservative nature of aviation safety standards.

Flood adaptation planning increasingly relies on high-resolution climate and impact modelling, yet the resulting indicators are rarely expressed in welfare terms that can guide public investment choices. We develop an integrated assessment framework that links convection-permitting climate projections and hydrological impact modelling with stated preference valuation to quantify the societal benefits of reducing future flood impacts in north-eastern Italy. Climate-conditioned flood exposure is simulated for mid-century and end-century horizons and translated into impact metrics across different elevation zones and multiple land use domains, including residential areas, productive areas, transport infrastructure, agricultural land and tourism assets. A large-scale discrete choice experiment was applied to estimate households’ willingness to pay for marginal reductions in flood impacts, with attribute levels calibrated to the hydro-climatic impact results. Individuals assign the highest marginal economic value to the protection of residential areas. Combining physical projections with economic evidence, we derived population-level estimates of the societal benefits of flood impact reduction. The resulting welfare indicators offer a transparent benchmark for evaluating the societal desirability of alternative adaptation strategies. This study is the first integration of hazard modelling and stated preference valuation. Our findings enhance the operational relevance of climate risk assessment and support the design of adaptation strategies that reflect both physical exposure and socially perceived value.

Wildfire smoke is increasing recognized as a major channel through which wildfire impacts society. Despite this, there is limited knowledge on how households value smoke exposure, particularly across time, sources, and severity levels. Additionally, a preferred wildlife mitigation method, prescribed burning, also generates smoke which creates a trade-off between smoke today for (potentially) less smoke in the future. This study estimates household willingness to pay (WTP) to reduce smoke exposure from wildfire and prescribed fire, distinguishing between moderate and severe smoke days. We used a stated-preference discrete choice experiment to examine the WTP for reductions in smoke exposure and estimate the marginal rate of substitution between wildfire and prescribed fire smoke days.

We find a WTP of $10.2 [95% CI: $5.4, $14.9] per year to avoid one additional day of moderate wildfire smoke and $15.8 [95% CI: $4.3, $27.4] to avoid one day of severe wildfire smoke. We also find that the WTP to reduce exposure to prescribed fire smoke is substantially lower at $4.4 [95% CI: $1.9, $6.9]. Using the marginal rate of substitution between wildfire and prescribed fire smoke days, we find that households are willing to accept 2.9 prescribed fire smoke days to avoid one moderate wildfire smoke day, and 3.9 prescribed fire smoke days to avoid one severe wildfire smoke day. These results provide new preference-based evidence relevant for quantifying the cost of wildfire smoke and evaluation prescribed burning as a wildfire mitigation strategy.