Testimony of Geoffrey Manne & Eric Fruits to Portland City Council on Algorithmic Pricing Tools
Re: Opposition to Proposed Ordinance Amending the Affordable Housing Code to Prohibit Algorithmic Pricing Tools
Thank you for the opportunity to provide testimony on the proposed ordinance prohibiting the use of algorithmic pricing tools in Portland’s rental housing market. Geoffrey Manne is the President and Founder of the International Center for Law & Economics (ICLE), a nonpartisan nonprofit research organization based in Portland. Eric Fruits is a Senior Scholar and Economist at ICLE. He is also an adjunct professor at Portland State University, where he has taught courses in real estate finance and investments and edited the PSU Center for Real Estate’s Quarterly Report on Oregon’s real estate markets for a decade. Dr. Fruits was a peer reviewer and authored the back-of-chapter exercises and test bank for the 14th edition of the widely used textbook Real Estate Finance and Investments by W.B. Brueggeman and J. D. Fisher.
Our opposition is grounded in economic principles, antitrust law, and an understanding of how algorithmic tools function in competitive markets. We recently wrote on the competitive effects of algorithmic pricing tools and submitted amicus briefs in Gibson v. Cendyn and Adebiyi v. Caesars Entertainment (attached) regarding algorithmic pricing in hotels, where we note:
[S]ubscribing to the same software does not imply an agreement among competitors to do anything, much less fix prices. The revenue management functions that [the software] automates are lawful. And automating lawful commercial activity does not make that activity unlawful.
This Policy Will Increase Rents and Reduce Housing Access
The ordinance misunderstands how modern rental markets function. Algorithmic pricing tools are not collusion—they are data-driven efficiency tools that help property owners:
- Prevent vacancies (reducing turnover costs passed to tenants);
- Adjust rents to match demand in specific neighborhoods;
- Identify units that can be priced below market rate to meet affordability
Research published by the Wharton School finds that property owners using algorithmic pricing software adjust rents more effectively based on market conditions. During economic downturns (e.g., 2008–2010), property owners using the software lowered rents and increased occupancy compared to those who didn’t use the software. Conversely, during economic recoveries (e.g., 2014–2016), property owners using the software raised rents and tolerated lower occupancy relative to those who didn’t use the software. This indicates the software helps property owners respond to changing demand, improving efficiency.
By banning these tools:
- Small property owners (who lack pricing expertise) will default to overpricing units to hedge against risk;
- Corporate property owners with dedicated pricing teams gain a substantial advantage;
- Vacancies will rise as prices become less responsive to demand shifts, reducing tax revenue for affordable housing programs
Key Flaws in the Text
- 30.01.088.A’s exemption favors large corporate property owners over small or “mom-and-pop” property owners. The ordinance exempts “any tool that aggregates, analyzes, or compiles information exclusively from properties or entities with the same majority owner or beneficial owner.” Only large corporate property owners would have the scale to bring such tools in-house, thus providing them a distinct competitive advantage over smaller property owners.
- 30.01.088.B.6 allows corporate property managers to continue using pricing tools while blocking small property owners from accessing them. The ordinance distinguishes between entities that solely provide pricing tools (e.g., software developers like RealPage) and property management companies that offer a suite of services, including pricing decisions.
While this exemption may be intended to preserve the ability of traditional property managers to operate without disruption, it could inadvertently create a loophole for property owners or large corporations to bypass restrictions by contracting with property management firms that use similar algorithmic tools under the guise of broader services.
This provision disproportionately favors large property owners who can afford full-service property management firms. In contrast, smaller property owners—who often rely on third-party pricing tools—may lose access to efficient pricing mechanisms.
- 30.01.088.C.1.b’s statutory damages of $10,000 per lease will force small property owners to exit the market over liability fears. The statute defines violations broadly, including:
- Technical non-compliance with data-sharing prohibitions (e.g., accidentally using a spreadsheet that aggregates public rental data);
- Unintentional errors in pricing decisions (e.g., adjusting rent based on market trends without realizing it could be construed as algorithmic coordination); or
- Administrative oversights (e.g., failing to document compliance with pricing tool bans).
The statutory damages of $10,000 per lease are enormous and far more than any actual damages a tenant might incur from allegedly being “overcharged” for rent.
More importantly, the statutory damages will likely trigger numerous nuisance lawsuits because the cost of even a “bare bones” legal defense would be much more than the statutory damages. Property owners charged in such a suit would face an extraordinary incentive to settle—even if they are innocent of the allegations.
The award of attorney’s fees (§30.01.088.C.1.a) compounds the likelihood of nuisance suits, turning the ordinance into a shakedown scheme that will encourage smaller property owners to exit the market.
- 30.01.088.A’s vague definitions could criminalize using basic Excel spreadsheets, ChatGPT, or popular websites such as RentCafe. The proposed ordinance explicitly lists “spreadsheets” alongside advanced technologies like artificial intelligence programs and algorithmic devices. The definition does not distinguish between simple tools used for basic calculations (e.g., Excel formulas) and sophisticated software designed for dynamic pricing or market analysis.
Under the ordinance’s expansive definition, property owners who use basic spreadsheets to track historical rent data, consult RentCafe for comparable properties, and calculate or adjust rents based on the spreadsheet could be in violation of the ordinance.
For example:
- A property owner tracking occupancy rates and rent changes around their properties might be accused of compiling “competitively sensitive ”
- Sharing a spreadsheet with a property manager or accountant could be considered unlawful data sharing under §30.01.088.B.4.
As noted above, larger property owners with in-house teams may avoid scrutiny by using proprietary systems not explicitly covered by the ordinance. In contrast, smaller property owners face heightened enforcement risks due to reliance on simpler methods.
By failing to narrowly define “competitively sensitive information” and “price setting tool,” the ordinance risks criminalizing routine practices essential to small-scale property management. This ambiguity disproportionately harms small property owners who rely on simple tools like Excel spreadsheets for basic calculations and compliance with rental laws.
Recommendations
Proponents of this ordinance point to the numerous algorithmic pricing lawsuits pending in the courts. The courts are precisely the correct venue for dealing with allegations of collusive price-setting.
At the federal level, the U.S. Department of Justice and Federal Trade Commission (FTC) have the expertise and authority to investigate and prosecute price-fixing claims. In addition, the FTC has the authority to investigate allegations of consumer harm and unfair methods of competition. Under state law, the Oregon Department of Justice has similar authority. Not only is this proposed ordinance harmful—as discussed above—it’s also unnecessary and duplicative.
We urge City Council to reject this ordinance and instead pursue policies that tackle Portland’s housing challenges at their core—by increasing supply and fostering competition.