High Rises and Housing Stress

Problem, research strategy, and findings The financialization of housing is a rapidly growing concern for planning researchers policymakers, but the opacity property ownership in most cities has hampered efforts to rigorously measure phenomenon. Here we introduce new approach based on big data methods. By combining web scraping assessment, business registry, rental advertisement data, reliably identified networks lurking behind anonymous numbered companies established extent financialized ownership. We demonstrate effectiveness this with quantitative case study Montreal (Canada). Using spatial regression clustering analyses, found that there are two distinct types Montreal: one characterized by precarious student tenants another affluent tenants. In general, high proportions associated higher levels stress dense typologies.Takeaway practice demonstrating meaningful differences market outcomes across status—which not usually been readily accessible either renters or planners—our show importance information asymmetry. Planners should treat landlord as component necessary properly regulate market. Municipalities make publicly facilitate public scrutiny residential land use more effective protection tenant rights.