Abstract
Purpose
This study aims to investigate the relationship between Airbnb and long-term residential rents, using Santa Monica, California, as a case study. In 2015, Santa Monica adopted the home sharing ordinance (HSO), a stringent regulation aimed at restricting short-term rentals (STR). This research examines the implications of this ordinance on the local housing market.
Design/methodology/approach
The synthetic control method (SCM) is applied to a panel data set comprising Airbnb listings and residential rents from multiple cities in Los Angeles County. This approach is used to estimate the causal effects of Santa Monica’s HSO on two outcomes: Airbnb listings and residential rents.
Findings
The empirical results show a 60% reduction in Airbnb listings in Santa Monica within two years of implementing the ordinance. Despite this significant decrease, the effect of the regulation on rents was not significant. Suggestive evidence indicates that the ordinance’s ineffectiveness in increasing the number of houses allocated to long-term tenants may have contributed to its negligible impact on rental rates.
Originality/value
To the best of the author’s knowledge, this research is the first to use the SCM for evaluating the impact of STR regulations. It offers crucial insights to policymakers on regulating platforms like Airbnb. The study reveals a scenario where a marked decrease in Airbnb activity did not lower residential rents, highlighting the need for context-specific evaluations in understanding the housing market’s dynamics. Additionally, these findings are valuable for investors considering the implications of regulatory changes in the STR sector.
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