Spatial Competition in the Airbnb Market: The Effect of Entry on Incumbent Revenues in New York City

Abstract

How competitive is the Airbnb market? One way to understand competition is through an examination of how new entrants affect incumbent property outcomes. In this paper, I use New York City Airbnb data to estimate the effect of entry on incumbent revenues. Existing literature about Airbnb generally focuses on its effect on other markets, such as the hotel industry and the housing market; instead, this paper contributes to past research by understanding competition within the Airbnb market. This is relevant for two reasons. First, regulation of Airbnb can potentially consider the effect of additional Airbnb properties not only on external competitors but also within the market. Second, modeling competition spatially contributes more empirical evidence about competition at a more granular level. Building off previous entry games literature (Mazzeo, 2002; Seim, 2006), this paper leverages the granular data structure by modeling competition at the census tract and neighborhood levels. Furthermore, this paper measures competition by distance and by type, based off Seim (2006) and Mazzeo (2002), respectively. The OLS specifications that use census tract level competition shows that a 1% increase in new competitors in the previous quarter is related to a change in incumbent revenues bounded between approximately -0.07% and -0.147%. Estimates are sensitive to the modeling assumptions used, though most results suggest that locating in an area with fewer competitors is beneficial for a property's revenues. This paper also provides some insight about how incumbents revenues are affected, through an analysis of the effect of entry on average price and reserved days.