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  5. New Development in the Transportation Economics
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New Development in the Transportation Economics

Paper Session

Saturday, Jan. 7, 2023 10:15 AM - 12:15 PM (CST)

Hilton Riverside, Kabacoff
Hosted By: American Economic Association
  • Chair: Panle Barwick, University of Wisconsin-Madison

Entry and Coordination in the U.S. Electric Vehicle Charging Industry

Jing Li
,
Massachusetts Institute of Technology
Katalin Springel
,
HEC Montreal

Abstract

In the transition toward a low-carbon transportation system, refueling infrastructure is crucial for the viability of any alternative fuel vehicle. However, refueling infrastructure for any alternative fuel currently receives heavy support from government and other industry players. We investigate the profitability and social welfare implications of different location and pricing strategies for electric vehicle charging networks. We combine data on travel patterns, electric vehicle adoption, and charging demand to estimate a model of consumer vehicle and travel choices and charging network location and pricing decisions. First, we test for evidence of spillovers across charging locations. Positive spillovers would suggest that a charging location provides more social value than may be privately appropriable, which may imply a need for support from the charging network or the public. Second, we compute social welfare, electric vehicle adoption, and profits for different location and pricing strategies of charging networks.

Public Transit Potential

Milena Almagro
,
University of Chicago
Felipe Barbieri
,
University of Pennsylvania
Juan Camilo Castillo
,
University of Pennsylvania
Nathaniel Hickok
,
Massachusetts Institute of Technology
Tobias Salz
,
Massachusetts Institute of Technology

Abstract

Building on the literature of two-sided market pricing, we show how a budget-constrained government would set optimal public transit prices and capacities across modes, accounting for externalities and returns to scale. We then explore how far current prices for different modes are from the social optimum. To that end, we assemble a dataset of all trips in Chicago where large economic disparities make public transit essential for many citizens. We also explore the effect of on-demand public transit, which exhibits large network effects.

Optimal Charging Infrastructure for Electric Vehicles

Panle Barwick
,
University of Wisconsin-Madison
Christopher R. Knittel
,
Massachusetts Institute of Technology
Shanjun Li
,
Cornell University
Youming Liu
,
Cornell University
James Stock
,
Harvard University

Abstract

The US is lagging behind in EV adoption and charging infrastructure among major economies. In 2020, the share of EV among new vehicle sales was only about 2%, compared to over 5% in China and 70% in Norway. The EV market is a two-sided market with the classical indirect network effect: the demand for EV’s depends on the availability of publicly-accessible charging stations and the supply of charging stations depends on the installed base of EV’s. Hence ‘market’ solutions are unlikely to be efficient in the presence of these externalities. As the US and countries across the world deploy policies to accelerate the pace to electrify transportation, a central question in effective policy design is the role of charging infrastructure. Despite both the political interest in and economic importance of supporting national charging infrastructure, to date there has been very little study of the most basic questions that would shape the details of charger cost-share programs. What would the optimal charging network look like in terms of the number of stations and the spatial pattern from the perspective of EV adoption? How can a given charger subsidy budget be used most effectively to promote EVs? To answer these questions, we collect extensive data on EV penetration, charging station locations, and consumer foot traffic for all zipcodes in this country. We develop and estimate an equilibrium model of a two-sided market with a focus on charging station locations at the granular level. The model specifies the EV purchase decisions and charging investment decisions. We then conduct counterfactual simulations to compare the cost-effectiveness of different policy designs in implementing the $7.5 billion Bipartisan Infrastructure Deal and consumer EV subsidies discussed in the $3.5 trillion reconciliation packages.
JEL Classifications
  • R4 - Transportation Economics