Airbnb and neighborhood crime: The incursion of tourists or the erosion of local social dynamics?

Shihe Fu,Laiyang Ke,Daniel T. O’Brien,Babak Heydari

doi:10.1371/journal.pone.0253315

Shihe Fu, Laiyang Ke + Show 2 more

Open Access

https://doi.org/10.1371/journal.pone.0253315

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Journal: PloS one	Publication Date: Jul 14, 2021
Citations: 12	License type: CC BY 4.0

Affiliation: Northeastern University, Boston Area Research Initiative

Abstract

The proliferation of internet-based home-sharing platforms like Airbnb has raised heated debates, with many in the general public believing that the presence of Airbnb listings can lead to an increase in crime and disorder in residential neighborhoods. Despite the importance of this debate to residents, policymakers, and other stakeholders, few studies have examined the causal linkage between Airbnb listings and crime in neighborhoods. We conduct the first such empirical test in Boston neighborhoods, focusing on two potential mechanisms: (1) the inflow of tourists might generate or attract crime; and (2) the creation of transient properties undermines local social dynamics. Corresponding to these mechanisms, we examine whether the number of tourists (approximated with reviews) or the prevalence of listings predict more incidents of private conflict, social disorder, and violence both concurrently and in the following year. We find evidence that increases in Airbnb listings–but not reviews–led to more violence in neighborhoods in later years. This result supports the notion that the prevalence of Airbnb listings erodes the natural ability of a neighborhood to prevent crime, but does not support the interpretation that elevated numbers of tourists bring crime with them.

Highlights

The expansion of internet-based short-term rental platforms like Airbnb has raised heated debates in recent years
We examine the relationships between the measures of Airbnb usage, penetration, and density and three types of social disorder and crime: public social disorder, private conflict, and violence, all per 1,000 persons in a neighborhood
Yi,t is the crime level measured by the number of private conflict, social disorder, and violence events per 1,000 people, Xi,t is a vector of time-variant neighborhood-level controls, and γ is the estimated causal effect of Airbnb presence. η and β are the neighborhood and year fixed effects, respectively, capturing both time-invariant characteristics of tracts and spatially-invariant characteristics of years

Summary

Introduction

The expansion of internet-based short-term rental platforms like Airbnb has raised heated debates in recent years. We note a second mechanism by which short-term rentals might impact neighborhood crime, one that is less prevalent in public discussions.

Results

Conclusion