A common problem with subsidizing socially beneficial goods is that many subsidies flow to inframarginal agents. In this paper, I describe how the problem of subsidizing multiple goods (or actions) is similar to the problem facing a multi-product monopolist. Bundling can allow multiproduct monopolists to capture consumer surplus above the optimal individual-good prices, especially when the demand for products is negatively correlated across individuals. Applying a similar argument to the government's problem, I characterize conditions under which pure or mixed bundles of subsidies can improve the cost-effectiveness of incentive programs. To conclude, I use simulations to compare the performance of bundled versus unbundled subsidies in two settings: (i) green durable good adoption in the United States, and (ii) a conditional cash transfer program in Indonesia.
Misperceptions About Air Pollution: Implications for Willingness to Pay and Environmental Inequality (with Reed Walker)
[abstract]
This paper explores whether misperceptions about air pollution contribute to environmental inequality in the United States. We use a two-part survey experiment to elicit respondents' beliefs about local air quality and pollution's effects on life expectancy. We document how misperception differs across demographic groups and then how this misperception affects willingness to pay (WTP) for cleaner air. Since misperception or beliefs may be correlated with other unobservable determinants of WTP, we randomly show selected participants customized information about their actual air pollution. This allows us to trace out how experimentally induced changes in beliefs affect WTP for air quality. Our results suggest significant misperceptions about air pollution in the US. Respondents, on average, overestimate both their air pollution exposure and its impact on life expectancy. Beliefs about relative air pollution are not systematically biased but are noisy. Despite some differences in misperceptions between Black and White respondents, counterfactual exercises do not suggest that rectifying these misperceptions would meaningfully close the observed gap in WTP and/or pollution exposure.
For Whom the Bridge Tolls: Congestion, Air Pollution, and Second-Best Road Pricing
Revise and Resubmit, Journal of Political Economy Microeconomics
Student prize finalist, 11th European Meeting of the Urban Economics Association. [abstract]
Real-world congestion zones are imperfect because they charge heterogeneous road users uniform prices, and invite externality spillovers in space and time. I show that given these imperfections, calculating optimal prices requires (i) individual-level externalities, (ii) individual elasticities, and (iii) cross-price elasticities between priced and unpriced trips. Using bridge toll microdata and a natural experiment where peak-hour pricing was imposed on one of the San Francisco Bay Area's 4 trans-bay bridges, I estimate a discrete choice model of driving demand that yields these parameters. I then use this model to estimate optimal prices for proposed congestion zones in three U.S. cities. I find that leakage pushes second-best prices below triple-level externalities, and that optimal peak pricing recovers just 10-41% of the welfare gains of a first-best policy.
Road Pricing with Green Vehicle Exemptions: Theory and Evidence (with Peter Nilsson and Sebastian Tebbe)
CESifo Working Paper No. 11038. Conditionally accepted, American Economic Journal: Economic Policy [abstract]
We provide a framework for setting congestion charges that reflect emission and congestion externalities and policy responses, such as vehicle ownership, driving, and residential sorting. Using Swedish administrative microdata, we identify these responses by exploiting a temporary exemption for alternative fuel vehicles and variation in individuals' exposure to congestion charges. We find that commuters respond by adopting exempted alternative fuel vehicles, shifting trips away from fossil fuel toward alternative fuel vehicles, and changing where they live and work. We combine the estimated responses with the framework to recover an optimal congestion charge of €9.46 per crossing in Stockholm.
What Drives Support for Inefficient Environmental Policies?
Berkeley Law, Economics, and Politics Center Working Paper. [abstract]
I use an information provision experiment conducted around a vote on Nevada's renewable portfolio standard (RPS) to study voter preferences for externality-correcting policies. I leverage exogenous variation in respondent beliefs induced by the experiment to model policy support as a function of voter perceptions of policy attributes (cost, effectiveness, and regressivity). I find that voting behavior is relatively unresponsive to perceived cost and perceived regressivity, but relatively responsive to perceived policy effectiveness. Using this model, I decompose differences in support for a performance-based policy (Nevada's RPS) and a hypothetical price-based policy (a carbon tax). Oaxaca-Blinder decompositions imply that differences in perceptions of policy attributes explain just 23% of the gap in support between RPS policies and carbon taxes, suggesting a significant role for "tax aversion." To the extent that misperceptions of policy attributes do explain differences in support for these two policies, the explained gap results from overly optimistic beliefs about RPS attributes. To conclude, I predict voting behavior under several counterfactual scenarios. I find that in this setting, targeting revenue toward "swing" voters is unlikely to significantly improve support for carbon taxes. Instead, the results of this pilot experiment highlight the importance of communicating to voters the efficacy of price-based policies.
Elasticities and Tax Incidence in Urban Ridesharing Markets: Evidence from Chicago
Journal of Urban Economics, 2025
This paper answers three questions about ridesharing taxes: (i) How elastic is ridesharing with respect to taxation? (ii) How effective are ridesharing taxes at addressing traffic-related externalities? And (iii), who bears the burden of ridesharing taxes? Using data from Chicago, I show that ridesharing demand is inelastic in gross terms, and relative to supply. Accordingly, 85% of the city's tax falls on passengers. Consistent with inelastic demand, I find little evidence of changes in congestion or air pollution in US cities that recently imposed ridesharing taxes. Finally, ridesharing taxes are roughly as progressive as the federal income tax schedule.
The Congestion Costs of Uber and Lyft
Journal of Urban Economics, 2021
[ungated] [abstract] [Axios] [Podcast]
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, Texas. 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 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.
Equity Neutral Policy (with James Sallee)
Can Targeted Rebates Foster Equity in Congestion Pricing Schemes? (with Jim Sallee)