The social value of a ridesharing platform: a hedonic pricing approach

Abstract Governments around the world have been facing challenges of regulating ever-increasing prevalence ridesharing platforms, leading to a proliferation academic and policy debates about social value such platforms. However, overall is still unclear because when analyzing net benefit provided by prior studies focused on either supply side (i.e., drivers) or demand passengers) users without considering nonusers. Conversely, some that considered spillover effect platform nonusers not simultaneously for users. In this study, we propose hedonic pricing model can be used as reasonably straightforward approach collectively quantify both Using approach, exploit plausibly exogenous variation in staggered entry Uber into different metropolitan areas between 2010 2016 find leads to, average, 2.8% increase median housing prices per square foot within area. We also there substantial spatial heterogeneity, with benefits concentrated greater dependence public transportation higher levels traffic delay. By quantitatively computing model, our study helps government regulators generate policies are more likely promote welfare become less susceptible political whims.