This paper offers new empirical evidence about actual Airbnb usage patterns and how they vary across neighborhoods in New York City. We combine unique, census-tract level data from Airbnb with neighborhood asking rent data from Zillow and administrative, census, and social media data on neighborhoods. We find that as usage has grown over time, Airbnb listings have become more geographically dispersed, although centrality remains an important predictor of listing location. Neighborhoods with more modest median household incomes have also grown in popularity, and disproportionately feature “private room” listings (compared to “entire home” listings). We find that compared to long-term rentals, short-term rentals do not appear to be as profitable as many assume, and they have become relatively less profitable over our time period. Additionally, short-term rentals appear most profitable relative to long-term rentals in outlying, middle-income neighborhoods. Our findings contribute to an ongoing regulatory conversation catalyzed by the rapid growth in the short-term rental market, and we conclude by bringing an economic lens to varying approaches proposed to target and address externalities that may arise in this market.
This paper considers the localized economic impacts of an extreme event, Hurricane Sandy, on a dense and diverse economy, New York City. It isolates establishments that are more dependent on local customers--retail establishments--to test whether or not they are more vulnerable to hurricane-induced flooding than other entities with geographically dispersed consumer bases. The paper exploits variation in micro-scale exposure to pre-storm risk and post-storm inundation to identify the impact of storm-induced flooding on establishment survival, employment and sales revenues. Results indicate that the neighborhood economic losses from Sandy were significant, persistent, and concentrated among retail businesses that tend to serve a more localized consumer base.