The New Urban Enclosures: Algorithmic Rent-Seeking, Corporate Landlordism, and the Financialization of Global Housing

Abstract

The global housing affordability crisis is conventionally diagnosed by orthodox economists and policymakers as a simple friction of supply and demand—a failure to build enough units to accommodate growing urban populations. This comprehensive paper rejects this neoclassical consensus, offering a critical political economy analysis that reframes the housing crisis as a deliberate, structural crisis of financialization. We argue that over the past two decades, residential real estate has been systematically enclosed by transnational capital, transitioning from a localized site of social reproduction into the world’s most lucrative and heavily traded financial asset class. By tracking the acquisition strategies of private equity firms, Real Estate Investment Trusts (REITs), and sovereign wealth funds between 2008 and 2025, we map the aggressive consolidation of the global housing stock. Furthermore, this study investigates the novel integration of algorithmic yield-management software into the rental market, demonstrating how property-technology (PropTech) platforms facilitate digitized cartel behavior, allowing corporate landlords to artificially inflate rents and enforce structural scarcity. The paper examines the complicity of the state—through quantitative easing, favorable tax regimes, and the violent enforcement of evictions—in guaranteeing the yields of this rentier class. We evaluate the devastating socio-economic consequences of this enclosure, including the acceleration of class-based displacement, the exacerbation of wealth inequality, and the deepening crisis of social reproduction. The study concludes by exploring emerging forms of tenant resistance and outlining a radical policy framework dedicated to the absolute decommodification of shelter, advocating for robust rent controls, the mass expropriation of corporate-owned housing, and the revitalization of public, non-market housing models.