Agent-based modelling of purchasing, renting and investing behaviour in dynamic housing markets

Residential Location Choice (RLC) and Real Estate Price(REP) have been considered as highly correlated and therefore have been jointly studied. This paper develops an agent-based RLC-REP joint model as a key component of an integrated land use-transport model, SelfSim. RLC-REP is capable of simultaneously simulating purchasing, renting and investing behaviour, considering the interactions and competitions between different agent types in the housing market, including renter, landlord, purchaser, seller and investor agents, resulting in new residential locations and real estate prices. In addition, the demographic evolution model in SelfSim that is directly linked to the RLC-REP model is also introduced. Next, both global and local sensitivity analyses (SAs), which employ the Elementary Effect Method (EEM) and Once-At-A-Time (OAT) Method, respectively, are carried out to fully test RLC-REP in a numerical example set up based on a Chinese medium-sized city, Baoding. The EEM-based global SAs identify four influential parameters (among the thirty-four) that could significantly influence the outputs of interests. The OAT-based local SAs further explore how these four important parameters influence the outputs, suggesting that the interactions between parameters could heavily influence the model sensitivity. Finally, the potential applications of the SA results to calibrate the model and to set up “what-if” scenarios are discussed.