Speakers
Description
Platform economy has enabled new business models for rental housing worldwide, such as short term rent. Among the most successful cases is Airbnb, a global platform that offers intermediation for hosts, as a place where they can easily offer and administer short-term rental agreements, and guests. Such easiness comes from the platform framework, which facilitates the connection of previously unreachable parts (hosts and guests), and the ability to deflect from public regulations through opaque, usually short-term, rental contracts. The informal nature of this business model, and its impact on housing citywide, has issued efforts from cities around the world - especially those where tourism (and thus short term rent) is a major feature, such as New York (USA) and Barcelona (Cataluña, Spain).
In this paper, we measure the effects of Airbnb in São Paulo with newly collected data, by comparing (i) its growth between 2017 and 2024 and (ii) the consumption of privately-produced new housing units by this business model.
An early issue while assessing the impacts of Airbnb is the availability of data. Most of the data shown on the platform is not publicly open for aggregation and summarization, and the access to databases is controlled and coerced by data privacy policies. For this paper, we employed a web scraping based methodology to obtain Airbnb data for the municipality of São Paulo, and then compared it to previously scraped data from 2017 (Slee, 2017). The scraped datasets from 2017 and 2024 were mapped and aggregated in order to avoid identification.
Ads in the region available on the platform grew from 10,377 to 27,906 (269%) in this timespan. The overall sum of ads in Airbnb represents 0,56% of all households in the region for 2022. But such a small share is highly concentrated in the city central districts, rendering a localized impact on housing supply (fig. 1). Furthermore, when grouped by room count, there is a disproportionate growth in the number of ads with one room or less, also concentrated in the central districts.
Data: Airbnb (2024), Census data from the Brazilian Institute of Geography and Statistics (2022).
Since 2014, the municipality of São Paulo has reconcentrated new developments along high and medium capacity transit infrastructure. Such developments were regulated to produce smaller apartments, and benefited from reduced building grants if sold below a price threshold. We compared the growth of Airbnb with the private production of new apartments (2017 to 2022), grouping both by bedroom count of each unit (fig. 2).
Data: Airbnb (2024), Brazilian Enterprise for Real Estate Studies (Embraesp) (2023).
Once more, the comparison shows a greater impact in central districts. República and Consolação had more than 100% of its new one-bedroom-or-less units consumed by Airbnb. It does not mean that all new units have been absorbed by the platform, but that Airbnb consumption of housing units grows as fast or even faster than the private supply rate, and that there is a tight relation between small housing units and the Airbnb business model in São Paulo.
The results show that the rise of Airbnb coincides geographically with hotspots of such new, incentivised and subsidised housing, signaling a negative impact on housing supply and a digression from urban regulation original purposes. For a methodological contribution, our results show that neighborhood-scale locations matter when assessing the impacts of Airbnb.
References
Slee, Tom (2017) Airbnb data collection. Available at: https://tomslee.net/category/airbnb-data (Accessed: 2025-01-14).
| Keywords | Short-term rent, Airbnb, web scraping, São Paulo |
|---|---|
| Best Congress Paper Award | No |
