The spatial structure of housing affordability and the impact of public infrastructure

Building on my previous work on housing wealth inequality, I generalise my model to allow for property-specific characteristics. The aim of this paper is to endogenously produce the spatial price structure of London (from economic micro-level behaviour) to enable the impact of public infrastructure on housing affordability. The subtlety in this work is that housing affordability requires both matched data between properties and household characteristics, something unavailable in official statistical datasets, and that usually requires statistical matching techniques that ignore economic behaviours and incentives.

We develop a parsimonious agent-level model of the housing market that reproduces the spatial price structure of London at the level of each property. Prices emerge as agents make utility-driven choices on properties with specific attributes in decentralised market interactions. This specification facilitates matching individual households to specific properties, something not possible in most publicly available large-scale housing datasets. Because location is a feature of properties, we estimate the impact of the new Elizabeth Line that connects the city from east to west. Then, by combining household and property variables, we estimate its impact on affordability. Changes in affordability allow to foresee potential demographic changes across space. Such information is extremely valuable not only to households and developers, but also to planning authorities who wish to anticipate the future demand for services and test the viability of different local tax regimes.