Heterogeneous responses and differentiated taxes: evidence from the heavy-duty trucking industry in the U.S. (Job Market Paper)

Author: Jen Z. He (University of Maryland, College Park)

Abstract:

In this paper, I exploit a rich vehicle-level micro dataset of the U.S. heavy-duty trucking fleet to examine how truckers differentially respond to changes in per-mile fuel cost. The empirical results show that the medium-run elasticities of vehicle-miles-traveled are -0.23 for combination trucks and -0.27 for vocational vehicles. Within each of the two groups, the estimated elasticities vary significantly among different truck weight classes and business sectors. The heterogeneity in truckers' responsiveness calls for differentiated policies, in particular, fuel taxes. I derive the optimal fuel taxes in a general equilibrium model that includes the externalities of truck operation (such as air pollution, road damage, accidents, and noise pollution), measures shipping demand in terms of payload distance and allows truckers to choose their routes based on shipping demand. In the second-best setting, most of the optimally differentiated diesel taxes are about twice or three times of the actual rate. Compared to the optimal uniform tax, implementing differentiated taxes based on vehicle weight classes reduces the existing distortion and generates an overall welfare gain of about 17.5 billion US dollars per annum.

Key words

  • Heavy-duty trucks
  • Price elasticity
  • Fuel cost
  • Differentiated tax
  • General equilibrium

The potential for improvement in on-road truck fuel economy

Authors: Jen Z. He (University of Maryland, College Park); Virginia McConnell (Resources for the Future); Benjamin Leard (Resources for the Future)

Abstract:

In this study, I look at the evidence about fuel economy and other truck attributes from the U.S. Inventory and Use Survey (VIUS). I estimate the trade-off effects between fuel economy and truck attributes, providing implications for a dynamic baseline of improvements in fuel economy. My estimation results show that the annual rates of fuel economy improvement from 1973 to 2002 are about 0.93% for combination trucks and 0.83% for vocational vehicles. In other words, in the absence of regulations, we can expect reductions in fuel consumption by 8.01% for combination trucks and 7.15% for vocational vehicles in ten years, just under half of the targets. The difference in technological progress among fleets with various sizes suggests that incentivizing trucking fleets to update their vehicles more frequently can be an effective channel to improve overall on-road in-use trucks’ fuel economy.

Key words

  • Heavy-duty trucks
  • Fuel economy
  • Technological progress
  • Trade-off effect

Environmental regulations and fleet composition: evidence from the heavy-duty truck industry in California

Authors: Jen Z. He (University of Maryland, College Park); William Leung (University of California, Davis; California Air and Resource Board)

Abstract:

I examine the factors affecting changes in trucking fleets’ composition in California using the disaggregated registration data from the California Department of Motor Vehicles. In particular, I am interested in identifying the effect of engine emission standards on trucks’ vintage distribution. The 2002 Consent Decrees required some engine manufacturers – Caterpillar, Cummins, Detroit Diesel, Volvo, Mack Trucks/Renault and Navistar to comply with the 2004 model year standards by October 2002. The policy is expected to raise the price of new trucks and thus has the potential to induce truck owners to hold on to their old and inefficient trucks. This is exactly the opposite effect than that intended by the regulators, and thus it is important to look at the empirical evidence. The remaining manufacturers that are not subject to the policy serve as the baseline control group. Using a difference-in-difference approach, I examine how truck registrations change differently among manufacturers and identify the effect of emission standards on truckers’ purchase decisions.

Key words

  • Environmental regulation
  • Fleet composition
  • Emission standards
  • Difference-in-difference