Conference Agenda

This paper examines the effect of early flood warning alerts on evacuation behavior. We exploit a 2022 flood event in Hamamatsu, Japan, where a novel high-urgency alert was issued for the first time to a major metropolitan area under the revised Basic Act on Disaster Management. Using three complementary datasets (Twitter (X) posts, mobile phone-based population data, and traffic volume data), we find that the population in alerted areas increased by 8% within 30 minutes of the first evacuation order, while vehicle traffic declined by 11% within two hours. Following the issuance of a more urgent alert, however, vehicle traffic increased sharply by 16% within 30 minutes. These findings suggest that escalating alert levels can trigger distinct behavioral responses, with implications for emergency communication strategies.

Large-scale infrastructure, such as flood-control dams, is a central strategy for climate adaptation. However, while these projects are engineered to protect downstream assets, the distributional consequences of their adaptation costs remain poorly understood. Using a spatial regression discontinuity design (RDD) on geocoded manufacturing firms across China, I document a stark asymmetry in adaptation outcomes. First, I confirm the physical efficacy of this infrastructure: dams successfully decouple downstream production from upstream rainfall shocks, effectively mitigating the hydrological propagation of extreme weather. However, this protection generates unequal economic returns. Firms immediately upstream exhibit 27–36% lower total factor productivity (TFP) growth compared to their downstream counterparts. I show that this gap is driven by the unequal burden of defensive adaptation. Lacking physical protection, upstream firms are incentivized to divert resources into non-productive buffers—specifically, excessive inventory and flood insurance—which decouple input intensification from output growth. Furthermore, these efficiency losses are amplified by cross-sectoral spillovers from agriculture-dependent supply chains. These findings highlight the hidden costs of adaptation borne by unprotected regions, suggesting that infrastructure-based solutions, while physically effective, can exacerbate spatial inequality by distorting firm-level resource allocation.

As countries and populations become increasingly vulnerable to rising climate risks and catastrophes, building adaptive capacity and resilience is essential to sustaining long-run welfare. Climate-related hazards, such as floods, droughts, cyclones and heat waves, threaten progress on socio-economic development in low and middle-income countries (LMICs). This paper assesses and compares whether LMICs are making progress towards key social and economic development goals while at the same time building sufficient capacity for climate change adaptation and resilience. By developing and employing a compensating surplus welfare framework, we estimate the net per capita welfare gains (in dollars) for 108 LMICs from 2000 to 2024 associated with Sustainable Development Goals (SDGs) 1-7 and with a country’s economic, social and governance “readiness” to adapt to climate change. We also examine the rate of convergence of welfare among LMICs over this period. The results show that deteriorating climate readiness impacted significantly the net overall per capita welfare of developing countries over 2000-24. Poorer LMICs generally experienced declining readiness, which not only affected their welfare but also slowed their rate of convergence toward the per capita welfare levels of richer LMICs. Our analysis helps identify effective and efficient ways to channel adaptation funding to boost the climate readiness and economic development of LMICs, making an important contribution to policies on climate change adaptation and resilience.

Flooding is a persistent threat, especially to communities along the coast of the United States. Due to rising sea levels and intensifying storms, these communities face elevated risks of property damage and economic instability. The impact of flood risks on price capitalization in the real estate industry has been a focus of climate risk research studies. However, such studies often overlook the impact on housing market liquidity. This study

investigates the relationship between coastal flooding and days-on-market (DOM), a key measure of housing market liquidity. We use National Oceanic and Atmospheric Administration (NOAA) tidal records with real estate market data for East U.S. coastal zip codes from July 2017 to July 2024. DOM and tidal flooding can be simultaneously affected by factors such as precipitation and flood mitigation policies. To estimate causal effects, we employ a two-stage least squares (2SLS) approach, using onshore wind speed as an instrument. Findings show that 1% increase in flood exposure extends the DOM by 1.78 days; a 2.26% increase relative to the average. The effect is more than three times larger in areas with lower Special Flood Hazard Area (SFHA) coverage, where flood insurance and disclosure requirements are less uniformly applied. This pattern indicates that tidal flooding generates meaningful housing market liquidity frictions, particularly in moderate-risk coastal markets. Scaled across all active listings, these

delays lock up an estimated $1.05–$2.11 billion in housing capital annually, slowing market turnover and affecting local tax bases. Results underscore the growing economic footprint of tidal flooding and highlight the need for policy tools that address liquidity risks both inside and beyond officially mapped flood zones.