Download our ABM model on risk perception and housing prices

RHEA agent-based housing market model

RHEA simulates the aggregated impacts of households’ residential location choices and their changing risk perceptions in response to flooding. One can explore the effects of climate change on urban resilience under various assumptions on how people behave when facing risks.

Real housing transaction prices and the 2018 survey data among buyers and sellers from US flood flood-prone cities strengthen the rules of agents actions and interactions, which are grounded in behavioral theories. Adaptive behavior of agents, their learning about flood risks, and the formation of price expectations are supported with Bayesian learning based on real data.

Prices in flood-prone areas do not recover after 2 consecutive floods

We find that when floods intensify affecting large urban areas, prices do not recover after a flood as they usually do currently. These pure market-driven processes can cause shifts in demographics in climate-sensitive hotspots placing low-income households further at risk. Low-income households cannot always move away due to mortgage debts and get trapped in hazard zones, suggesting increasing climate gentrification as an outcome of market sorting

Number of people living beyond the poverty line grows in flood-prone parts of the city as they are outpriced from safe areas