Nefarious Algorithms: Rent-Fixing via Algorithmic Collusion and the Role of Intentionality in the Pursuit of Class Monopoly Rent (Zimmerman & Anderson, 2025)
RealPage's rent-setting software pools competitor pricing data from landlord clients to recommend coordinated rent levels — achieving class monopoly rent extraction without the explicit collusion antitrust law requires.
Summary
"Nefarious Algorithms: Rent-Fixing via Algorithmic Collusion and the Role of Intentionality in the Pursuit of Class Monopoly Rent," by Allison J. Zimmerman and Matthew B. Anderson, appeared in Urban Science, 2025 (open access). It is the fourth entry the wiki now covers in Anderson's "class monopoly rent" series — after Kyoto, Copenhagen, and Oregon rent-control politics — examining a distinctly 21st-century mechanism: algorithmic rent-setting software.
The RealPage Mechanism
RealPage's "revenue management" platform pools its landlord clients' real-time competitor pricing, occupancy, and lease-term data, then recommends specific rent levels and staggers lease renewals to avoid local oversupply. The paper quotes client admissions from litigation records: one describes the software as helping landlords "work together... to work with a community in pricing strategies, not to work separately"; a Greystar representative wanted pricing decisions taken "off-site," reducing individual landlords' empathetic reluctance to raise rents on occupied units. RealPage is the subject of real, ongoing US antitrust litigation — a federal suit filed in the Western District of Washington in November 2022, with follow-on multistate class actions consolidated in 2023, drawing heavily on a 2022 ProPublica investigation.
Geographic concentration evidence: in Seattle's Belltown/South Lake Union neighborhoods, 70% of apartments were run by just 10 property managers, all RealPage clients; in Washington, DC, RealPage-priced units make up roughly 90% of large multifamily buildings.
The Intentionality Argument
The paper's core legal contribution addresses a gap in antitrust doctrine: existing law requires provable explicit agreement among competitors to establish price-fixing, but algorithmic intermediation lets landlords achieve coordinated pricing outcomes without ever explicitly agreeing with each other — each landlord individually "just" follows a software recommendation built from pooled competitor data. The authors argue RealPage's market share looks modest at the national scale but is heavily concentrated at the neighborhood (submarket) level, where its pricing power is actually exercised — a "scale problem" existing antitrust frameworks are not built to see. The authors cite FTC Commissioner Maureen Ohlhausen's "guy named Bob" analogy for the doctrinal gap algorithmic collusion opens.
Relation to the Georgist Case
This extends class monopoly rent theory into a technologically new but conceptually familiar arena: a scarce, controlled position (the local rental submarket) is exploited by coordinated actors to extract rent above what genuinely competitive pricing would produce — the same underlying logic the wiki's three other Anderson-series pages document in heritage tourism, state land development, and political rhetoric. The paper's proposed remedies extend beyond antitrust reform: rent control, integrated social housing, anti-speculation taxes on vacant units, restrictions on corporate-landlord mergers, and court-approval requirements for rent increases — explicitly citing Vienna's model (44% social housing stock, 77% of private rentals under some form of control) as a case where pursuing class monopoly rent becomes structurally unprofitable.
Nuances and Limits
- US-specific, RealPage-specific case. The mechanism (algorithmic revenue-management software) is spreading to other vendors and sectors, but this paper's evidence base is specifically about RealPage and the litigation it has generated.
- Draws on Marxian rent theory (class monopoly rent), the same broader tradition as the wiki's other Anderson-series pages, distinct from core Georgist land-rent economics though conceptually adjacent.
- Full text read directly (A-claim). The complete open-access article was obtained (via a reader-proxy route after the standard MDPI URL was unexpectedly blocked to this session) and read in full.
Bears On
- Concept: Ground Rent — the underlying "class monopoly rent" concept this paper, and the wiki's three other Anderson-series pages, apply to a new technological mechanism.
- Concept: Rentier — a concrete, litigated case of rent extraction via coordinated pricing power rather than land ownership concentration per se.
- Research: Anderson: Kyoto Cultural Monopoly Rent · Anderson & Dascher: Copenhagen Land Rent · Anderson, Zickefoose, Andrie & Newton: Landlord Opposition to Rent Control — the three other entries in the same "class monopoly rent" series now covered on the wiki.
See Also
- Anderson: The Commodification Gap and Cultural Monopoly Rent — Insights from Kyoto
- Anderson & Dascher: The Land Rent Dynamics of Public Land Development in Copenhagen
- Anderson, Zickefoose, Andrie & Newton: Landlord Opposition to Rent Control
- Ground Rent
- Karp: Private Government at Home — Landlord Power and Rental Residential Domination
Sources
- Allison J. Zimmerman & Matthew B. Anderson (2025), "Nefarious Algorithms: Rent-Fixing via Algorithmic Collusion and the Role of Intentionality in the Pursuit of Class Monopoly Rent," Urban Science 9(8): 315, DOI 10.3390/urbansci9080315, CC-BY 4.0. mdpi.com — full text read directly 2026-08-31 (via a reader-proxy route after the standard MDPI URL was blocked to this session) — used for the RealPage mechanism, the client-admission quotations, the Belltown/South Lake Union and DC concentration figures, the intentionality/antitrust argument, and the proposed remedies including the Vienna comparison (A-claim; full text).