Abstract
In this paper, we assess the impact of Airbnb on housing rents and prices in the city of Barcelona. Examining very detailed data on rents and both transaction and posted prices, we use several econometric approaches that exploit the exact timing and geography of Airbnb activity in the city. These include i) panel fixed-effects models, where we run multiple specifications that allow for different forms of heterogeneous time trends across neighborhoods, ii) an instrumental variables shift-share approach in which tourist amenities predict where Airbnb listings will locate and Google searches predict when listings appear, iii) event-study designs, and iv) finally, we present evidence from Sagrada Familia, a major tourist amenity that is not found in the city centre. Our main results imply that for the average neighborhood, Airbnb activity has increased rents by 1.9%, transaction prices by 4.6% and posted prices by 3.7%. The estimated impact in neighborhoods with high Airbnb activity is substantial. For neighborhoods in the top decile of Airbnb activity distribution, rents are estimated to have increased by 7%, while increases in transaction (posted) prices are estimated at 17% (14%).
Highlights
Tourism has grown enormously in recent decades
Between 1990 and 2017, the worldwide number of international tourist arrivals increased from about 400 million to 1300 million (WTO, 2018). This pattern is true for urban tourism; the number of visitors to the 132 most popular world cities increased by 45% between 2009 and 2015.1 Peer-to-peer platforms such as Airbnb have recently entered the market through partly accommodating the increased demand for tourism in cities
There, we show that owners benefit from Airbnb either because they obtain the short-term rental rate or because Airbnb increases the long-term rental rates
Summary
Tourism has grown enormously in recent decades. Between 1990 and 2017, the worldwide number of international tourist arrivals increased from about 400 million to 1300 million (WTO, 2018). They look at the impact of Airbnb on rents and house prices for all cities in the US.8 Their main strategy consists of using a ‘shift-share’ instrument, where the time variation comes from Google Trends of ‘Airbnb’ searches, while the cross-sectional variation is a neighborhood ‘touristiness’ index based on the location of restaurants. They find that a 1% increase in Airbnb listings increases rents by 0.018% and housing prices by 0.026%.
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