Network industries with spatial data
OA Version
Citation
Abstract
This dissertation consists of three essays in empirical industrial organization covering topics related to network industries. The first chapter examines the geographical distribution of electric vehicle (EV) charging stations in the U.S., with a focus on public fast-speed charging stations. I provide descriptive evidence that Tesla and Electrify America charging stations have a more consistent geographical spread than the third category independent stations, whereas independent stations are clustered around densely populated areas. A high density of stations in urban areas and low geographical coverage of independent stations create spatial disparity in the availability of charging infrastructure, which may hinder EV adoption. The second chapter investigates the effect of the geographical distribution of public fast-speed charging stations on EV adoption in the U.S. from 2009 to 2019. I develop a dynamic model of station entry for independent stations that characterizes the interdependence between the growth of EV adoption and investment in charging stations. A novel component of the model is the way it captures features of a charging network such as its density at local regions and connectivity over long distances. I estimate the model using spatial data on charging stations and EV registration data. Assuming that independent station owners are motivated to strategically build charging stations at optimal locations to effectively promote the widespread adoption of EV, I simulate counterfactual industry outcomes, such as station entry and EV stock. The results indicate that optimizing the geographic distribution of independent charging stations could have resulted in a 32% increase in non-Tesla EV stock by 2019 while maintaining the same total number of stations. The third chapter studies the tradeoff concert promoters face when the promoters become more consolidated. Ownership consolidation of promoters in recent decades facilitates a geographical network of venues that an integrated promoter has control over across the country, which allows national promoters to internalize the potential coordination problem when scheduling touring routes for different artists. I analyze this source of efficiency gain and its tradeoff with cost savings from transportation under a merger of promoters. I construct a structural model of promoter oligopoly competition in which each promoter takes the ticket prices as exogenous and maximizes the aggregate profit over the course of a year across a portfolio of artists and makes decisions regarding the date and location of each concert. I take a revealed preference approach to estimate the structural model and then simulate a merger between the two largest US promoters. The results show that a merger can generate both efficiency gains from coordination and cost savings from transportation.
Description
2024
License
Attribution-NonCommercial-NoDerivatives 4.0 International