Conference Agenda

Climate change has been identified as the largest threat to public health of the 21st century. Despite this evidence, the integrated assessment models (IAMs) used to quantify the global consequences of climate change seldom incorporate its long-term effects on public health and living conditions. This paper addresses this gap by employing an agent-based stock-flow consistent model that captures the long-run social impacts of climate change in terms of population health and well-being, within a framework that jointly analyses the co-evolution of health and economic dynamics. The model shows that climate change-induced health shocks increase mortality and hospitalization rates, leading to declines in both overall life expectancy and healthy life expectancy. The health effects, primarily via their impacts on labour supply, spill over to the economic sector, affecting GDP growth and amplifying the macroeconomic impacts of climate change. Importantly, our results reveal a vicious feedback-loop between economic and health dynamics, which amplifies the initial health impacts. Finally, the model provides a robust framework for evaluating the effects of alternative climate policies on economic growth and collective welfare, as well as for assessing different public health investment strategies aimed at mitigating the societal impacts of climate change.

Focusing on global annual averages of climatic variables can bias aggregate and distributional estimates of the economic impacts of climate change. We empirically identify dose-response functions of GDP growth rates to daily mean temperature levels and combine them with regional intra-annual climate projections of daily mean temperatures. We disentangle, for various shared socio-economic pathways (SSPs), how much of the missing impacts are due to heterogeneous warming patterns over space. Global damages in 2050 are 25% (21-28% across SSPs) higher when accounting for the shift in the shape of the entire intra-annual distribution of daily mean temperatures at the regional scale.

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.

We study the macroeconomic responses of Chilean regions to natural disasters—floods and wildfires—using local projections and both public and novel administrative data. We document persistent GDP losses, temporary declines in consumption, and a delayed recovery of investment, accompanied by rising employment but falling wages and effective hours. These dynamics contrast with U.S. county-level evidence and point to the importance of disaster size, as well as institutional and financial conditions, in shaping post-disaster recoveries in emerging economies. We interpret the evidence through four mechanisms: destruction of productive capital, tighter financial conditions that constrain rebuilding, reallocation of production, and household wealth losses that depress consumption while supporting low-wage reconstruction employment. Embedding these mechanisms into a real business cycle model with financial frictions, we show that financial constraints are quantitatively central: absent these frictions, post-disaster losses in economic activity during the first years would be reduced by about one half. Our findings highlight the role of financial and reconstruction policies in mitigating the long-run economic costs of climate-related disasters.