Complex Networks Model for Residential Real Estate Markets

To meet the challenges of the complexity of residential real estate markets and a dearth of large databases, we built a theoretical super-complex networks model, focusing on the statistical mechanics of network topology and dynamics. Nodes correspond to agents in the market (banks, house producers and house buyers). The directed edge represents the positive cash flow caused by any transaction between two agents. Power-law distributions consistent with Zipf's law characterize firm size and individual wealth. The probability function of a firm's death is given by a Pareto distribution. New links emerge by nodes reconnecting according to a preferential rule. We also simulated an evolving network in the Shanghai residential market during 2001-2005.