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We propose a novel multi-layered nonlinear model that is able to capture andpredict the housing-demographic dynamics of the real-state market by simulatingthe transitions of owners among price-based house layers. This model allows usto determine which parameters are most effective to smoothen the severity of apotential market crisis. The International Monetary Fund (IMF) has issuedsevere warnings about the current real-state bubble in the United States, theUnited Kingdom, Ireland, the Netherlands, Australia and Spain in the lastyears. Madrid (Spain), in particular, is an extreme case of this bubble. It is,therefore, an excellent test case to analyze housing dynamics in the context ofthe empirical data provided by the Spanish National Institute of Statistics andother sources of data. The model is able to predict the mean house occupancy,and shows that i) the house market conditions in Madrid are unstable but notcritical; and ii) the regulation of the construction rate is more effectivethan interest rate changes. Our results indicate that to accommodate theconstruction rate to the total population of first-time buyers is the mosteffective way to maintain the system near equilibrium conditions. In addition,we show that to raise interest rates will heavily affect the poorest housingbands of the population while the middle class layers remain nearly unaffected.

A housing-demographic multi-layered nonlinear model to test regulation strategies