Conference Agenda

This study develops a multidimensional analysis of the impact of hundreds of hydrogeological disastrous events that occurred in Italy over the period 2013-2020. To address multiple and time-heterogeneous events, we develop a staggered diff-in-diff design, which allows us to identify an unbiased causal effect of such events on several socioeconomic dimensions, including firms’ activity, aggregated income and distribution, as well as measures of poverty and human development. We document that these effects persist despite the recovery funds allocated in the post-emergency phase from the central government to the affected areas as a consequence of the declaration of the state of emergency. Our analysis reveals that the intensity of these net adverse effects varies across the affected provinces depending on their institutional quality. We document a full economic recovery in the high-level institutions regions and a structural adverse economic effect in the low-quality institutional regions. This divergence concerns only economic indicators, while the negative impact of disasters on social indicators persist among regions independently on institutional quality heterogeneity.

How are financial markets responding to anticipated climate-driven wildfire risk increases? Combining high-resolution meteorological predictions and land use pattern maps with detailed US municipal bond data, this paper finds that municipalities facing higher future wildfire risk increases are already having to pay substantially higher borrowing costs as a result. A one standard deviation increase in future wildfire exposure is associated with a 23-basis point rise in school district bond spreads, corresponding to 42% of the sample mean. Borrowing cost impacts are significantly larger in areas with higher minority population shares and heavier reliance on local

revenue sources.

The impacts of natural disasters on firms are still not fully understood, as some

studies find that affected firms experience substantial asset losses, while there is

also evidence that affected firms ultimately perform better than non-affected ones.

This paper analyses the impact of flood events on European manufacturing firms

between 2008-2017. We employ a rigorous methodology to achieve a higher granularity in identifying flood-affected firms than previous studies. We use the recently proposed Local Projections Difference-in-Difference (LP-DiD) approach to estimate dynamic average treatment responses for staggered treatments. We find that floods negatively affect firms’ assets, in particular tangible fixed assets, firms’ ability to

raise debt, and their productivity and profitability. These effects persist over several

years after a flooding event, likely due firms’ reduced ability to raise debt, which

might impede recovery measures. Flood impacts further crucially depend on the

severity of a flood. In the case of severe floods, the negative impacts are more pronounced, likely due to extensive damage to production assets such as machinery,

plants, and buildings. In contrast, firms recover notably faster from minor flood

events.

Climate change threatens property markets by increased exposure to previously unrecognized risks. These risks are usually not internalized because of their rarity, potentially leading to overvaluation of at-risk properties. However, little is known about the extent to which rare and highly localized climate-induced disasters update risk perceptions in ways that influence property markets, essential to understand their broader economic and distributional effects. Using the catastrophic Gjerdrum quick clay landslide in 2020 as a natural experiment, we analyze its causal impact on sales value of quick clay exposed properties. We further explore volume effects. The landslide acted as a double information shock, first by revealing an underestimated risk, and second by highlighting its extent, as hazard maps were widely shared through the media. Leveraging detailed property transaction data from Eastern Norway, we apply a static and dynamic multi-way fixed effects difference-in-differences (DiD) design, supplemented by a bounded regression discontinuity analysis to strengthen identification. Our results reveal a statistically significant and negative impact on property values for homes exposed to quick clay, extending beyond the directly affected county. The decline in property values ranges from 2 to 5 percent. We find evidence of a positive effect on sales volume of quick clay exposed properties. From a back-of-the-envelope calculation, we estimate the total depreciation to be approximately 25 million USD.