Tarduno, Matthew. For Whom the Bridge Tolls: Congestion, Air Pollution, and Second-Best Road Pricing.
Abstract: Cities are increasingly adopting road pricing policies to address the congestion and air pollution externalities associated with urban driving. A first-best road pricing scheme would charge road users according to the social damages associated with each trip. In practice, road pricing often takes the form of cordon zones — regions in the center of a city where road users are charged for entry. These pricing schemes deviate from the first-best policy in two important ways: First, feasible cordon systems cannot account for all of the heterogeneity in trip-level externalities. Second, cordon zones leave nearby roads unpriced, allowing for externality leakage. As a result, it is generally unclear how to optimally set cordon prices. In this paper, I adapt models from public finance to demonstrate how to optimally set cordon prices in the face of these policy imperfections. Calculating optimal prices requires information about (i) the heterogeneity in marginal trip-level externalities, (ii) the relationship between these externalities and individual price-responsiveness, and (iii) the elasticity of substitution between priced and unpriced trips. I then use administrative data from bridge tolls in the San Francisco Bay Area to back out each of these parameters. Armed with this model of urban driving demand, I calculate optimal prices for planned cordon zones in three cities ––– San Francisco, Los Angeles, and New York. In each city, I find that leakage drives optimal peak-hour prices ($2-7) well below average social damages ($4-12). As a result, optimal cordon policies are relatively ineffective at internalizing congestion and pollution externalities: In these three cities, second-best cordon prices recover 15 to 40% of the welfare gains that would be achieved under a first-best Pigouvian policy. To conclude, I discuss the prospects for improving the performance of cordon pricing through expanding spatial coverage or allowing for granular time-of-day pricing.
Tarduno, Matthew, 2021. The congestion costs of Uber and Lyft.
Journal of Urban Economics, Elsevier, vol. 122.
Abstract: I study the impact of transportation network companies (TNC) on traffic delays using a natural experiment created by the abrupt departure of Uber and Lyft from Austin, TX. Applying difference in differences and regression discontinuity specifications to high-frequency traffic data, I estimate that Uber and Lyft together decreased daytime traffic speeds in Austin by roughly 2.3%. Using Austin-specific measures of the value of travel time, I translate these slowdowns to estimates of citywide congestion costs that range from $33 to $52 million dollars annually. Back of the envelope calculations imply that these costs are similar in magnitude to the consumer surplus provided by TNCs in Austin. Together these results suggest that while TNCs may impose modest travel time externalities, restricting or taxing TNC activity is unlikely to generate large net welfare gains through reduced congestion.
Press: [Axios][Talking Headways Podcast]
Tarduno, Matthew, 2020. What drives support for inefficient environmental policies?
Berkeley Law, Economics, and Politics Center Working Paper.
Negative externalities are often regulated with performance standards (e.g., fuel economy standards) where economic theory suggests that price-based mechanisms (e.g., fuel taxes) offer a more efficient alternative. The relative popularity of performance-based policies is puzzling: Given the cost-effectiveness of Pigouvian taxation and the ability of governments to pair these policies with redistribution, it should be possible to construct a price-based regulation that dominates a performance-based alternative on at least one of the three dimensions of efficacy, fairness, or cost, holding fixed the others. In this paper, I use an information provision experiment to understand what drives differences in voter support for these two policy types. Specifically, this experiment allows me to answer two questions: How do voters' perceptions of policy cost, effectiveness, and regressivity influence policy support? And do misperceptions of policy attributes explain the relative popularity of nontax corrective policies? Preliminary results from a pilot experiment conducted around a 2020 energy ballot initiative suggest that voters overestimate the effectiveness of performance-based policies at reducing carbon emissions. Oaxaca-blinder decompositions, however, suggest that differences in beliefs about policy attributes explain only a quarter of the difference in support for performance vs. price-based policies. As a result, neither rectifying misperceptions about policy attributes, nor redesigning price-based policies to compensate swing voters appear likely to significantly bolster support for price-based corrective policies.
Can targeted rebates forster equity in congestion pricing schemes? (with James Sallee)
Understanding the role of information in the willingness to pay for clean air (with Reed Walker)