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Building holistic computational models of the housing market.

This project examined the UKÌýhousing market, creating a holistic computational model of the London housingÌýmarket to understand how its dynamics drive inequality. To do so, the project integrated actual housing data and spatial considerations, so as to be able to test experiments regarding London infrastructure and its effects on prices.

In order to address housingÌýinequality, policymakers often debate policies such as rent controls, inheritance taxesÌýand social housing. However, evidence about the effectiveness of policies is scant. Partly, this is due to a lack of adequate methods.

Thus, this project sought to fill a key evidence gap to develop a spatially awareÌýagent-computing model, where individual agents make realistic economicÌýdecisions within a particular geography. By combining AI, spatial analysis andÌýeconomic computational modelling, the project provided novel analytic tools forÌýbespoke policy designs.

The policy recommendations that it produced are pertinent not only to urbanÌýplanners and housing regulators, but to a broader community of policymakersÌýto understand how housing ownership underpins wealth distribution in the UKÌýand to design evidence-based policy instruments.ÌýResults about estimating the impact of infrastructure in the housing marketÌýwere produced and have formed the basis for policy papers.Ìý

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