In this thesis, an economic-engineering model of the ripple effect in the housing market is put forward. The ripple effect in the housing market is modeled by integrating into one model the local price dynamics of the rental market, the spatial price dynamics between local rental markets, and the valuation of real estate. Such a model is lacking in current housing-market literature.

The economic-engineering model design has two main aspects. First, economic-engineering model design uses analogs between mechanical systems and the housing market, ensuring that the model contains only economically and mechanically interpretable parameters. In this way input optimization and parameter optimization have a direct implementation in the real world. Second, economic-engineering model design relies on classical-mechanical modeling techniques that make the model suitable for optimally and robustly determining governmental policy using control formalism.

This thesis takes the perspective of the housing market as a heterogeneous economic space, where the dimensions are geographic proximity and economic influence. The model put forward in this thesis spatially discretizes this heterogeneous economic space into homogeneous local markets, such that local price dynamics govern the local markets and inter-local differences add spatial price dynamics.

The model put forward in this thesis is designed to predict where shortages will arise due to the introduction of rent control. Such a model guides policymakers in where to build for effectively relieving shortages in the housing market. Finally, such a model informs investors about the value change to expect due to policy changes and migration trends.