Overview of the Study
This research, published in the Journal of Urban Economics (Volume 119, September 2020), investigates how shortâterm rental platforms, specifically Airbnb, influence housing markets in Barcelona. The authorsâMiquelâĂngel GarciaâLĂłpez, Jordi JofreâMonseny, Rodrigo MartĂnezâMazza, and Mariona SegĂșâare scholars with expertise in urban economics and housing policy. Their analysis combines detailed microâdata on Airbnb listings, transaction prices, and posted rents, offering a comprehensive view of market dynamics in a major European tourist city.
Data Sources and Scope
The study uses multiple highâquality datasets: (1) Airbnb listings scraped from InsideAirbnb covering 2009â2017, (2) transaction price records from the Catalan Tax Authority (2009â2017), and (3) posted rent and price ads from Idealista (December of each year 2007â2017). The geographic unit of analysis is the Basic Statistical Area (BSA), of which 221 BSAs are retained after data restrictions, each averaging about 7 000 inhabitants. Airbnb activity is measured by the number of listings receiving at least one review per quarter, yielding an average of 54 listings per BSA by 2016 and 178 listings in the top decile.
Main Empirical Findings
Baseline regressions show that an increase of 100 Airbnb listings raises rents by 1.9 %, transaction prices by 4.6 %, and posted prices by 3.7 % on average. In highâAirbnb neighborhoods (top decile), rents rise by roughly 7 %, transaction prices by 17 %, and posted prices by 14 %. The impact on prices consistently exceeds that on rents, reflecting higher returns from shortâterm rentals. Eventâstudy analyses confirm that these effects emerge after 2013, when Airbnb activity expands, while preâ2013 trends are parallel across neighborhoods.
Mechanisms Behind Price Increases
The authorsâ theoretical model predicts that Airbnb reduces the supply of longâterm rentals, pushing up rents. Empirical tests on household counts support this mechanism: a 100âlisting increase lowers the number of households by about 2.4 % and modestly reduces household size and population, indicating displacement of longâterm residents. Instrumentalâvariable estimationsâusing a shiftâshare instrument that combines proximity to tourist amenities with Google Trends for âAirbnb Barcelonaââproduce similar positive effects, reinforcing causal interpretation.
Implications for Sustainable Housing
The findings suggest that shortâterm rental platforms can exacerbate housing affordability challenges in dense urban areas, especially where tourism demand is high. Barcelonaâs case illustrates how a 5 % share of housing units listed on Airbnb (2.06 % of total units, 6.84 % of rented units) can translate into measurable rent and price pressures. Policymakers aiming for sustainable housing must consider regulatory tools that balance tourism benefits with the need to preserve longâterm rental stock, such as licensing requirements, caps on rental periods, or taxation of shortâterm rentals.
Key Statistics at a Glance
- Average Airbnb listings per BSA (2016): 56 (overall), 179 (top decile)
- Share of housing units listed on Airbnb: 2.06 % of total, 6.84 % of rented units
- Average rent increase per 100 listings: 1.9 % (overall), 7 % (top decile)
- Average transaction price increase per 100 listings: 4.6 % (overall), 17 % (top decile)
- Average posted price increase per 100 listings: 3.7 % (overall), 14 % (top decile)
Policy Context and Future Research
Barcelona has implemented measures to curb unlicensed shortâterm rentals, reflecting broader European concerns about âtouristification.â The studyâs robust methodologiesâincluding fixedâeffects, BSAâspecific trends, detrending, IV, and eventâstudy designsâprovide a template for evaluating similar dynamics in other cities. Further research could explore longâterm welfare effects on residents, the role of platform regulation, and comparative analyses across European housing markets.
