Conference Agenda

Constructed primarily to defend coastal economies from severe storms and sea surges, seawalls have served as an effective protective measure across the world for thousands of years. In the past decade, as climate change has intensified projections of stronger, more frequent cyclones as well as significantly rising sea levels, seawalls have become even more critical for sustaining coastal economies. Many countries are already planning expansions of seawall infrastructure in preparation for future sea level rise. This study examines the current role of seawalls in protecting China's coastal economies from typhoon impacts during 2015-2024. Our results have shown that increasing the share of coastlines protected by seawalls has significantly reduced the negative impacts of typhoons, high waves, and rising sea levels on coastal economies, as reflected by changes in nightlight intensity. These impacts mostly arise from reduced disruptions to industrial, residential, and transportation activities, and are concentrated in districts that are not directly coastal but are the most economically active within each coastal city, implying that the defensive effects of seawalls spillover beyond directly protected coastal districts. We also find that seawall maintenance significantly improves protective effectiveness, while co-location with offshore mangroves can reduce the protective benefits. Overall, our findings highlight the importance of seawalls in strengthening coastal resilience to extreme climate events and underscore their relevance under future climate change.

Tropical cyclones are among the most damaging weather extremes globally. Recently, it has been shown that they can affect income inequality within countries and that the vulnerability to tropical cyclones decreases with economic development on the country level. However, it is not yet clear whether vulnerability depends upon income inequality and how vulnerability varies with income and income inequality across subnational regions. Here, we study the dependence of vulnerability of economic assets to hurricane impacts upon income and income inequality across counties in the United States. To this end, we develop an event-based approach that blends a spatially and temporally resolved representation of individual hurricane wind fields with spatially resolved data on the distribution of economic assets. The vulnerability of affected regions is expressed through vulnerability curves that statistically link reported county-level damages to local wind speeds. Studying damages from 72 storms over the period 1996-2021, as reported by the National Oceanic and Atmospheric Administration’s Storm Events Database, we find that vulnerability is significantly lower in affected counties with higher average per capita income or lower income inequality. These vulnerability differences are large enough to have substantially shaped observed damages during the study period. If all counties had the reduced vulnerability of the top income quintile of affected counties, the annual average damage over the study period would have been nearly USD 2 bn lower, roughly a quarter of the annual average spendings of the Federal Emergency Management Agency Disaster Relief Fund over this period. Further, if the vulnerability had been as low as that of the least unequal quintile of counties, the annual average damage would have been lower by USD 3.9 bn. Our findings indicate that there are substantial adaptation potentials to hurricane damage in the United States. Vulnerability reduction could thus be an important co-benefit of policies aimed at the reduction of poverty and income inequality, which is important in the light of a likely intensification of tropical cyclones impacts under global warming and increasing socioeconomic disparities.

Understanding heterogeneity in the climate-economy relationship is crucial for gaining insight into potential adaptation mechanisms. We apply causal forests to panel data to identify variables that drive treatment effect heterogeneity in climatic conditions, focusing on temperature impacts on economic output. We systematically evaluate more than 260 socio-economic and geographic characteristics, measured as long-run averages, that could moderate the relationship and lead to heterogeneous vulnerability. To select relevant characteristics beyond baseline climate, we use three novel panel implementations of causal forests and employ the least absolute selection and shrinkage operator (Lasso) as a robustness check. Mean years of education emerges as a key determinant of heterogeneity: countries with lower years of education are the most vulnerable to temperature changes. We also find that the percentage of the cropland area equipped for irrigation, the mean share of the country area that is covered by mosaic natural vegetation, and the mean terrain ruggedness index, which measures elevation changes, are relevant factors in explaining cross-country differences in vulnerability. Incorporating the selected variables into a fixed-effects panel regression framework highlights that some countries, particularly in Africa, have been substantially more vulnerable to temperature changes than reported by past studies. These moderators help inform which cross-country characteristics could reflect adaptation.