The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs.
This paper introduces an economic agent-based model of an urban housing market. Our Risks and Hedonics in Empirical Agent-based land market (RHEA) model captures natural hazard risks and environmental amenities through hedonic analysis, facilitating empirical agent-based land market modeling.
Property prices are affected by changing market conditions, incomes and preferences of people. Price trends in natural hazard zones may shift significantly and abruptly after a disaster signalling structural systemic changes in property markets.
The price of risk is an important indicator that can facilitate decisions in any risk mitigation policy, which demands for methods to value the social costs of risk as accurately as possible. In particular, in flood risk management the central number that influences the balance between costs and benefits is the price of flood risk.
We first start from the theory to isolate the cause-effect relationships and to formulate hypotheses. We then collect a set of very different data, ranging from market transactions to GIS, Lab experiments and surveys to test alternative behavioral theories and compare to observed macro data.
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders into formal simulation models...