California’s all-in price rule for short-term rentals made travelers more price-sensitive but was linked to higher average nightly rates and market churn, with consumer surplus rising overall.
California’s new price-transparency rule for short-term rentals is changing how travelers shop on platforms like Airbnb—and the market’s response is more complicated than classic economic intuition would suggest.
A recent study examines Assembly Bill 537, a statewide law that took effect July 1, 2024. The measure requires short-term lodging providers to display prices that already include mandatory fees, rather than advertising a low nightly rate and adding charges such as cleaning fees later in the booking process. The researchers focus on Airbnb listings in two California cities—San Diego and San Francisco—where the policy applied, and compare outcomes to listings in Seattle and Chicago, which serve as “control” markets without the same requirement.
To make the comparison as apples-to-apples as possible, the team uses a technique called Coarsened Exact Matching, designed to align treated and control listings on key characteristics before estimating the law’s impact.
One clear finding: when consumers see the full price up front, they react more strongly to price differences. In the treated California cities, guests became more price-sensitive relative to travelers in the control cities. That result fits the basic theory behind transparency rules—clearer pricing should sharpen competition by making it easier to compare options.
But the next result runs against a common prediction. Instead of pulling prices down, the study finds that average daily rates increased. The estimated rise is 4.8% in the cities subject to AB 537, compared with the control cities over the same period.
The authors argue that the policy also triggered substantial “market churn”—a reshuffling of which properties remain available and which ones enter or exit. Relative to Seattle and Chicago, the treated California markets experienced more listing exits and more new entries. The exits were not random: listings that depended heavily on cleaning-fee revenue were more likely to leave the platform after all-in pricing became mandatory. In contrast, properties categorized as higher quality were more likely to stay.
New entrants looked different from the incumbents. The study finds that incoming listings tended to offer lower fees but also lower quality than the properties already in the market. In other words, transparency did not simply alter how existing listings priced; it appears to have changed who chose to participate in the market at all.
To connect these market shifts to consumer outcomes, the researchers conduct a discrete-choice welfare analysis. They conclude that the law reduced a “welfare illusion” created when fees are hidden until later in the transaction—an illusion that can make options seem cheaper than they really are and distort choice. After accounting for the rise in posted daily rates, the analysis indicates that realized consumer surplus increased on average, with market churn playing a major role in producing those gains.
The benefits, however, were not uniform. The net effects varied considerably across ZIP codes in the treated cities, suggesting that some neighborhoods saw larger welfare improvements than others.
The researchers note that their data acquisition was supported by funding from the University of Maryland and acknowledge feedback from multiple academic and policy audiences. They also emphasize that the findings represent the authors’ views, not those of the National Bureau of Economic Research.
Why it matters
Price transparency rules are spreading across consumer markets, from lodging to ticketing, because hidden fees can mislead buyers and weaken competition. This study suggests that revealing the full price can improve consumer welfare even if headline rates rise—partly by changing which sellers stay in the market. Policymakers and platforms will likely watch whether these churn-driven gains persist, and which communities benefit or lose as hosts adjust their business models.
