Research

Environmental regulations often cause a subset of a selected firms to reallocate production in space or time. Environmental regulations often cause a subset of affected firms to reallocate production in space or time. The resulting supply responses by rivals in the same market can raise costs even for those unconstrained by the regulation. Policy analysis, however, often fails to account for these spillover effects. This research considers an environmental policy forcing hydroelectric dams to inefficiently allocate electricity generation over time. Combining quasi-random variation in regulatory stringency and a regression discontinuity design, I estimate direct costs of regulation and spillovers to other producers in the same market. These regulations increase market-wide costs as much as 19.8% and generate millions of dollars per year in pollution externalities. Spillover effects are substantial, accounting for over 50% of the true policy costs. Decomposition of spillover channels show implications for optimal policy, including allowing flexibility in the timing of regulatory compliance, as climate change continues to exacerbate water scarcity.

Recent theoretical and empirical work characterizes attention as a limited resource that decision-makers strategically allocate. There has been less research on the dynamic interdependence of attention: how paying attention now may affect performance later. In this paper, we exploit high-frequency data on decision-making by Major League Baseball umpires to examine this. We find that umpires not only apply greater effort to higher-stakes decisions, but also that effort applied to earlier decisions increases errors later. These findings are consistent with the umpire having a depletable ‘budget’ of attention. There is no such dynamic interdependence after breaks during the game (at the end of each inning) suggesting that even short rest periods can replenish attention budgets. We also find that an expectation of higher stakes future decisions leads to reduced attention to current decisions, consistent with forward-looking behavior by umpires aware of attention scarcity.

This paper identifies and quantifies major determinants of future electric vehicle (EV) demand in order to inform widely-held aspirations for market growth. Our model compares three channels that will affect EV market share in the United States from 2020-2035: intrinsic (no-subsidy) EV demand growth, net-of-subsidy EV cost declines (e.g. batteries), and government subsidies. Geographic variation in preferences for sedans and light trucks highlights the importance of viable EV alternatives to conventional light trucks; belief in climate change is highly correlated with EV adoption patterns; and the first $500 billion in cumulative nationwide EV subsidies is associated a 7-10 percent increase in EV market share in 2035, an effect that diminishes as subsidies increase. The rate of intrinsic demand growth dwarfs the impact of demand-side subsidies and battery cost declines, highlighting the importance of non-monetary factors (e.g. charging infrastructure, product quality and/or cultural acceptance) on EV demand.

Roughly three quarters of vehicles are purchased into multi-car households. We study whether households are willing to substitute attributes, such as fuel economy, across vehicles within their portfolio. We develop a novel strategy to separately identify idiosyncratic preferences for an attribute from these within-portfolio effects. Using the universe of household vehicle registration records in California over a six-year period, we find that two-car households exhibit strong substitution across vehicles when faced with an exogenous change to fuel intensity of a kept vehicle. This effect can erode a substantial portion of the benefit from major policies, such as Cash-for-Clunkers.

We provide the first evidence that short-term exposure to air pollution affects the work performance of a group of highly-skilled, quality-focused employees. We repeatedly observe the decision-making of individual professional baseball umpires, quasi-randomly assigned to varying air quality across time and space. Unique characteristics of this setting combined with high-frequency data disentangle effects of multiple pollutants and identify previously under-explored acute effects. We find a 1 ppm increase in 3-hour CO causes an 11.5% increase in the propensity of umpires to make incorrect calls and a 10 μg/m³ increase in 12-hour PM_2.5 causes a 2.6% increase. We control carefully for a variety of potential confounders and results are supported by robustness and falsification checks. Our estimates imply a 3% reduction in productive output is associated with a change in CO concentrations equivalent to moving from the 25th to the 95th percentile of the CO-distribution in many of the largest US cities.

U.S. programs subsidize electric vehicles (EVs) in part to reduce greenhouse gas (GHG) emissions. We model a suite of life cycle GHG emissions considerations to estimate the GHG abatement potential from switching from an internal combustion engine vehicle (ICE) to an EV in the continental U.S. The GHG intensity of EVs hinges on the electricity and ambient temperature when charged and operated. Both have high spatial and temporal heterogeneity, yet are typically modeled inadequately or overlooked entirely. We calculate marginal emissions, including renewables, for electricity by region and test forecasted grid composition to estimate future performance. Location and timing of charging are important GHG determinants, but temperature effects on EV performance can be equally important. On average, EVs slightly reduce GHGs relative to ICEs, but there are many regions where EVs provide a decisive benefit and others where EVs are significantly worse. The forecasted grid shifts from coal towards renewables, improving EV performance; the GHG benefit per EV in western states is roughly $425 today and $2400 in 2040.