Agent-Based Modelling of House Price Evolution

Housing price growth is a complex mixture of external factors such as the growth of the economy, unemployment rates and the supply of land. It is also strongly dependent upon buyer and seller perceptions and attitudes, particularly during a boom period. External factors may be captured by a variety of methods, but the emergent price and sale volume resulting from human interactions is a problem in the dynamics of multiple cognitive agents. We describe a RePast model for house price growth using real-world GIS data with a fuzzy logic framework for modelling agent behaviour