Airbnb and crime in Barcelona (Spain): testing the relationship using a geographically weighted regression

ABSTRACT

The existence of works proving the possible relationship empirically that Airbnb lodgings could have with crime in Spain is not known. This research analyzes the relationship between Airbnb lodgings and crimes against the properties and people in Barcelona’s neighbourhoods. To achieve this, we use an ordinary least squares regression model and a geographically weighted regression model. The results show a significant and positive relationship between the higher density of Airbnb lodgings and the higher crime rates in the neighbourhoods, especially of patrimonial nature. Divided by type of leased space, the Airbnb homes, in which the guest shares a room with other guests, show a higher relationship with crimes against property and people. The results of the local model show a spatial heterogeneity in all variables used, indicating the need to address non-stationary spatial processes that reveal hidden patterns. However, the only variable that shows statistically significant local variability is the total Airbnb lodgings variable. Finally, we discussed some unexpected results, proposing some future lines of research.

KEYWORDS:

• Shared economy
• crime
• geographically weighted regression
• tourism
• Spain

Acknowledgements

I would like to thank Mossos d’Esquadra (the Regional Police Office of Catalonia, Spain) for sharing the crime data used in this paper. This dataset is rarely available in Spain so the development of this paper would not be possible without the collaboration of that police Office.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Data can be gathered from http://insideairbnb.com/barcelona/.

2. petty theft, theft, theft with force, robbery with violence and/or intimidation and carjacking.

3. The category ‘crime against people’ contains the following three offences: rape, homicide and injury.

4. This index is a general indicator of concentration or heterogeneity, whose values range from zero (maximum heterogeneity) to one (maximum homogeneity).