Environmental policy, decision making, and rebound effects in the U.S. trucking sector

Outline

• Abstract
• Keywords
• 1. Introduction
• 2. Background and Literature Review
• 2.1. Firm Decision Making in the U.s. Trucking Sector
• 2.2. Understanding the Rebound Effect in the Context of Firm Decision Making
• 3. Methods
• 4. Results and Discussion
• 4.1. Fuel Prices and Vehicle Efficiency – Exploring Direct Rebound Effects
• 4.2. Use of Fuel Savings—indirect Rebound Effect
• 4.3. Capital Costs of Vehicles
• 4.4. the Role of Drivers and Driver Behavior
• 5. Conclusion and Policy Implications
• Acknowledgements
• Appendix A. Sample Semi-Structured Interview Questions
• References

Conclusions

This paper presents the results of in-depth interviews with eight trucking firms of different types. Our goal was to better understand the way firms think about and react to fuel prices and vehicle efficiency, which is an important area of study given new federal regulations that mandate cleaner, more efficient vehicles for the US trucking sector. These regulations have the potential to create both direct and indirect rebound effects, and the interviews attempted to better understand the size of these potential effects from the perspective of trucking firms.

We find little evidence from our interviews of direct rebound effects with respect to vehicle miles traveled in response to improved efficiency. Firms, for the most part, operate to minimize costs while meeting service expectations no matter how efficient their vehicles are. Adding extra miles simply doesn’t make sense for a firm operating in a competitive environment. In contrast to the light-duty (passenger) vehicle market, the HDV driver does not derive additional utility from traveling more miles. These results help validate recent quantitative, empirical work that shows negligible fuel price elasticity with respect to VMT.

However, our interviews do suggest the potential for direct rebound effects in the HDV sector in other respects. Respondents indicate that in seeking to better serve the customer, reduced fuel costs may induce increased energy use per mile or per ton-mile, resulting from increased travel speed or other operational inefficiencies such as less emphasis on driver performance or maximally efficient loading—which in turn can lead indirectly to increased VMT. As for indirect and economy-wide rebound effects, we find mixed results that are a function of the particular firm and how it manages any savings resulting from improved vehicle efficiency. For example, for publicly traded firms, some of these savings go to shareholders; for retailers with their own transportation operations, savings can go to end customers who are purchasing the retail product; for a small trucking firm, savings may go to increase driver pay or take-home pay; and for all firms, some savings will be set aside to meet the anticipated increase in maintenance costs for the new vehicles and technologies. In any event, the interview responses indicate that not all of the savings are shared with customers through reduced freight or service rates, suggesting that increased demand for trucking in response to lower freight costs may not occur. We again note that firms recognize the potential for lower fuel costs to lead to increased speed of service, directly through higher speed limits, but also indirectly through reduced emphasis on efficient loading. In seeking to understand the potential for indirect and economy-wide effects, future research may seek to explore and incorporate into future analyses: a) how fuel price and fuel economy influence speed and other operational efficiencies, and b) demand elasticities for HDV services (in terms of VMT or ton-miles) based on speed of service versus price.

Fuel surcharges make evaluating the indirect rebound effect even more complicated. The structure of fuel surcharges indicates that while fuel price changes are always incorporated and passed onto customers, actual fuel efficiency of the fleet in MPG may not always trigger such pass-throughs. Therefore, while fuel price changes may be associated with more or less demand for trucking, changes in fuel economy may not have the same effect. This structure implies that firms may profit when their fleet meets an efficiency level that is better than that used in federal DOE surcharge calculations. Firms in this position may not be passing these savings along to customers, but may be taking these additional revenues as profit. As many firms use the DOE MPG index baseline in their fuel surcharge calculations—as opposed to the actual fleet MPG—the effect of efficiency improvements on fuel surcharges may depend more upon whether or not the DOE modifies the MPG baseline in response to new efficiency regulations, versus the actual efficiencies of the fleets using the DOE index and MPG baseline. This in turn will have implications for whether or not rebound effects would more likely be indirect through increased demand by freight customers, or economy-wide rebound through spending of profits throughout the economy.

A key result from our work that warrants future examination is the potential difference in responses of HDV firms to changes in fuel prices versus changes in vehicle fuel economy. Fuel prices have often been used as a proxy for fuel economy changes in transportation rebound effect research, as fuel prices and fuel economy together determine cost per mile. However, responses to fuel prices and fuel economy may differ, as has been shown in research in the light-duty vehicle market (Greene, 2012). Several of the interviewee comments suggest this to be the case for the HDV sector as well. For instance, our preliminary findings included: a) fuel price savings are passed onto customers, while fuel economy savings are allocated to driver pay; b) lower fuel prices can result in reduced emphasis on efficient loading or driver performance, while improved fuel economy does not induce such changes; and c) fuel prices are reflected in fuel surcharges, while fuel economy improvements may not be. Additionally, it was noted that increased capital costs are incorporated into rates, suggesting that while fuel price changes are passed onto the customer entirely, cost savings from fuel economy improvements are offset to a potentially large degree by the increased cost of the vehicle to the trucking firm—in both the primary and secondary market. Each of these distinctions has potentially important implications in terms of the extent to which the rebound effect occurs, and/or the way in which it will manifest—direct, indirect or economy-wide effects. Our findings—albeit preliminary—suggest that rebound effects in the HDV sector may manifest more in the form of indirect or economy-wide effects. Future research may explore further a) how firms’ responses to fuel economy improvements differ from responses to fuel prices, changes in particular; and, how these responses may contribute to HDV VMT and energy use, both by HDVs and economy-wide. In terms of policy implications, our results indicate that the energy savings and emissions reduction impacts of new policies aimed at improving the efficiency of HDVs are not likely to be diminished by immediate direct rebound effects in the form of increased VMT. Indirect demand effects are less certain and other factors (such as global economic growth) will have much more influence on energy consumption and emissions than freight rate effects. The percentage of fuel savings that are passed along to customers can range anywhere from 0 to 100%, depending on a variety of factors; although current empirical work indicates these values are low or not statistically significant (Winebrake et al., 2015a, b). Therefore, any analysis that incorporates an indirect rebound effect by adjusting freight rates by an amount equal to fuel savings would be highly conservative.

Further research, both qualitative and quantitative, is needed in this important area. As HDVs continue to gain an increasing share of energy use and emissions from the transportation sector, further understanding of the direct and indirect rebound effects of all types is required to facilitate appropriate decision-making by firms and policy-makers alike.