Framing Flood Risk: How reference points shape housing market behaviour in the Limburg river area
W. Lubbersen (TU Delft - Technology, Policy and Management)
A. Mutlu – Mentor (TU Delft - Technology, Policy and Management)
T. Filatova – Graduation committee member (TU Delft - Technology, Policy and Management)
M.E. Warnier – Graduation committee member (TU Delft - Technology, Policy and Management)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Climate change is increasing the frequency and severity of flooding, posing growing challenges for housing markets and regional economies. Riverine regions are particularly exposed, as flood risk interacts with constrained housing supply, residential mobility and spatial inequality. In the Dutch province of Limburg, recent flooding has highlighted the need to understand how households respond to climate related risks when making housing decisions.
Although existing research examines the economic effects of flood risk, less attention has been given to the behavioural mechanisms underlying housing market responses. In particular, limited evidence exists on which reference points households use to evaluate flood losses and how these reference points affect property values, market activity and location choices.
This research applies prospect theory within an agent-based housing market model adapted to the Limburg river area. The model incorporates loss aversion and probability weighting alongside ten formulations based on objective risk perception, single and event-based flood losses, future market value, anticipated financial protection and flood experiences. These formulations are evaluated under medium and high housing demand and annual flood probabilities of 2%, 3% and 5%. Outcomes are assessed through transaction prices, housing utility, transaction frequency and household sorting by income and behavioural characteristics.
The results show that properties in flood-prone areas generally have lower transaction prices, lower utility and fewer transactions than properties outside the flood zone. Reference point selection meaningfully changes the magnitude of these differences, particularly at lower flood probabilities, while differences between formulations narrow at 5% risk. Only anticipated financial protection of 80% reduces flood related market differences below those produced by objective risk perception, while distant flood experience produces outcomes closest to the objective baseline. Higher demand strengthens spatial sorting, with lower income households becoming increasingly concentrated in flood-prone areas. Differences in probability weighting and loss aversion also contribute to sorting, although probability weighting has a stronger effect.
These findings indicate that flood risk policy should account for both behavioural responses and unequal purchasing power. Collective flood defences, clear risk communication and targeted financial protection may reduce both market disruption and unequal exposure. Future research should empirically identify the reference points used in housing decisions and test the model under lower flood probabilities and in different regional and cultural settings.