Abstract
Energy efficiency improvements can create rebound effects that increase energy use. We have studied rebound in US freight transportation and found that substitution across transportation modes can be an important rebound mechanism. The sign of the rebound effect depends on whether the improved efficiency induces substitution with more or less fuel-efficient modes. We used detailed US microdata to model shippers’ freight mode choices and simulate how these choices change under energy efficiency standards. Under a policy approximating US heavy-duty truck fuel economy standards, we found that rebound can be positive or negative in individual market segments. However, the overall effect substantially reduces the gains from improved truck fuel efficiency. Energy savings are reduced by around 20% because shipments switch from rail service to the improved, but still less fuel-efficient, truck service. Similar substitution rebound effects could occur in other settings where producers choose between technologies with different energy efficiencies.
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Data availability
The Commodity Flow Survey Public Use Microdata are publicly available from the US Census Bureau (https://www.census.gov/programs-surveys/cfs/data/datasets.html). Fuel price data are publicly available from the US Energy Information Administration (https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=pet&s=emd_epd2d_pte_nus_dpg&f=m and https://www.eia.gov/dnav/pet/hist/eer_epjk_pf4_rgc_dpgD.htm). Replication data for this paper are available via Zenodo at https://doi.org/10.5281/zenodo.11264966 (ref. 51).
Code availability
All code used to conduct the study is available at https://github.com/jehdukeegr/Freight-Mode-Rebound.
References
-
Greening, L. A. & Difiglio, C. Energy efficiency and consumption—the rebound effect—a survey. Energy Policy 28, 389–401 (2000).
-
Gillingham, K., Rapson, D. & Wagner, G. The rebound effect and energy efficiency policy. Rev. Environ. Econ. Policy 10, 68–88 (2016).
-
Jenkins, J., Nordhaus, T. & Schellenberger, M. Energy Emergence—Backfire and Rebound as Emergent Phenomena (Breakthrough Institute, 2011); https://s3.us-east-2.amazonaws.com/uploads.thebreakthrough.org/legacy/blog/Energy_Emergence.pdf
-
Gillingham, K., Kotchen, M. J., Rapson, D. S. & Wagner, G. The rebound effect is overplayed. Nature 493, 475–476 (2013).
-
Exadaktylos, F. & van den Bergh, J. Energy-related behaviour and rebound when rationality, self-interest and willpower are limited. Nat. Energy 6, 1104–1113 (2021).
-
Use of energy explained: energy use for transportation. US Energy Information Administration https://www.eia.gov/energyexplained/use-of-energy/transportation.php (accessed 9 June 2015).
-
Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles—Phase 2. Regulatory Impact Analysis (Office of Transportation and Air Quality, US Environmental Projection Agency, 2016).
-
Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles—Phase 2. Proposed Rules Federal Register Technical Report No. 133 (US Environmental Projection Agency, 2015).
-
Small, K. A. & Van Dender, K. Fuel efficiency and motor vehicle travel: the declining rebound effect. Energy J. 28, 25–52 (2007).
-
Frondel, M. & Vance, C. Re-identifying the rebound: what about asymmetry? Energy J. 34, 43–54 (2013).
-
Linn, J. The rebound effect for passenger vehicles. Energy J. 37, 257–288 (2016).
-
2012 CFS Public Use Microdata File (United States Census Bureau, accessed 9 June 2015); https://www.census.gov/data/datasets/2012/econ/cfs/historical-datasets.html
-
Matos, F. J. F. & Silva, F. J. F. The rebound effect on road freight transport: empirical evidence from Portugal. Energy Policy 39, 2833–2841 (2011).
-
Leard, B., Linn, J., McConnell, V. & Raich, W. Fuel Costs, Economic Activity, and the Rebound Effect for Heavy-Duty Trucks Discussion Paper 14–43 (Resources for the Future, 2015).
-
Sorrell, S. & Stapleton, L. Rebound effects in UK road freight transport. Transp. Res. D 63, 156–174 (2018).
-
Transportation satellite accounts 2018. Bureau of Transportation Statistics https://www.bts.gov/satellite-accounts (accessed 24 January 2019).
-
2017 CFS Preliminary Data. U.S. Department of Transportation (Bureau of Transportation Statistics, 2018); https://www.bts.gov/surveys/commodity-flow-survey/2017-cfs-preliminary-data
-
Meyer, J. R., Peck, M. J., Stenason, J. & Zwick, C.The Economics of Competition in the Transportation Industries (Harvard Univ. Press, 1959).
-
Oum, T. H. A cross sectional study of freight transport demand and rail–truck competition in Canada. Bell J. Econ. 10, 463–482 (1979).
-
Lloret-Batlle, R. & Combes, F. Estimation of an inventory theoretical model of mode choice in freight transport. Transp. Res. Rec. 2378, 13–21 (2013).
-
Holguín-Veras, J., Kalahasthi, L., Campbell, S., Gonzalez-Calderon, C. A. & Wang, X. C. Freight mode choice: results from a nationwide qualitative and quantitative research effort. Transp. Res. A 143, 78–120 (2021).
-
Winebrake, J. J. et al. Fuel price elasticities in the US combination trucking sector. Transp. Res. D 38, 166–177 (2015).
-
Nealer, R., Matthews, H. S. & Hendrickson, C. Assessing the energy and greenhouse gas emissions mitigation effectiveness of potential US modal freight policies. Transp. Res. A 46, 588–601 (2012).
-
Austin, D. Pricing overland freight transport to account for external costs. J. Transp. Econ. Policy 52, 45–67 (2018).
-
Cristea, A., Hummels, D., Puzzello, L. & Avetisyan, M. Trade and the greenhouse gas emissions from international freight transport. J. Environ. Econ. Manage. 65, 153–173 (2013).
-
Winston, C. Conceptual developments in the economics of transportation: an interpretive survey. J. Econ. Lit. 23, 57–94 (1985).
-
Friedlaender, A. F. & Spady, R. H. A derived demand function for freight transportation. Rev. Econ. Stat. 62, 432–441 (1980).
-
Winston, C. A disaggregate model of the demand for intercity freight transportation. Econometrica 42, 981–1006 (1981).
-
Abdelwahab, W. & Sargious, M. Modelling the demand for freight transport: a new approach. J. Transp. Econ. Policy 26, 49–70 (1992).
-
Shinghal, N. & Fowkes, T. Freight mode choice and adaptive stated preferences. Transp. Res. E. 38, 367–378 (2002).
-
García-Menéndez, L., Martínez-Zarzoso, I. & De Miguel, D. P. Determinants of mode choice between road and shipping for freight transport: evidence for four spanish exporting sectors. J. Transp. Econ. Policy 38, 447–466 (2004).
-
Train, K. & Wilson, W. W. Estimation on stated-preference experiments constructed from revealed-preference choices. Transp. Res. B 42, 191–203 (2008).
-
Kang, K., Strauss-Wieder, A. & Eom, J. K. New approach to appraisal of rail freight projects in South Korea: using the value of freight transit time savings. Transp. Res. Rec. 2159, 52–58 (2010).
-
De Jong, G. et al. New SP-values of time and reliability for freight transport in the Netherlands. Transp. Res. E 64, 71–87 (2014).
-
Regmi, M. B. & Hanaoka, S. Assessment of modal shift and emissions along a freight transport corridor between Laos and Thailand. Int. J. Sustain. Transp. 9, 192–202 (2015).
-
Feo-Valero, M., Arencibia, A. I. & Román, C. Analyzing discrepancies between willingness to pay and willingness to accept for freight transport attributes. Transp. Res. E 89, 151–164 (2016).
-
Román, C., Arencibia, A. I. & Feo-Valero, M. A latent class model with attribute cut-offs to analyze modal choice for freight transport. Transp. Res. A 102, 212–227 (2017).
-
Ravibabu, M. A nested logit model of mode choice for inland movement of export shipments: a case study of containerised export cargo from India. Res. Transp. Econ. 38, 91–100 (2013).
-
Jiang, F., Johnson, P. & Calzada, C. Freight demand characteristics and mode choice: an analysis of the results of modeling with disaggregate revealed preference data. J. Transp. Stat. 2, 149–158 (1999).
-
Greene, W. H. & Hensher, D. A. A latent class model for discrete choice analysis: contrasts with mixed logit. Transp. Res. B 37, 681–698 (2003).
-
Arunotayanun, K. & Polak, J. W. Taste heterogeneity and market segmentation in freight shippers mode choice behaviour. Transp. Res. E 47, 138–148 (2011).
-
Arencibia, A. I., Feo-Valero, M., García-Menéndez, L. & Román, C. Modelling mode choice for freight transport using advanced choice experiments. Transp. Res. A 75, 252–267 (2015).
-
Tao, X. & Zhu, L. Meta-analysis of value of time in freight transportation: a comprehensive review based on discrete choice models. Transp. Res. A 138, 213–233 (2020).
-
Friedlaender, A. F. & Spady, R. H. Freight Transport Regulation (MIT Press, 1981).
-
Levin, R. C. Allocation in surface freight transportation: does rate regulation matter?. Bell J. Econ. 9, 18–45 (1978).
-
US no. 2 diesel retail prices 2017. US Energy Information Administration https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=EMD_EPD2D_PTE_NUS_DPG&f=M (accessed 9 November 2017).
-
US Gulf Coast kerosene-type jet fuel spot price 2017. US Energy Information Administration https://www.eia.gov/dnav/pet/hist/eer_epjk_pf4_rgc_dpgD.htm (accessed 15 November 2017).
-
Transportation Energy Data Book 2018 (Oak Ridge National Laboratory, accessed 24 January 2019); https://cta.ornl.gov/data/download36.shtml
-
Freight rail: miles ahead on sustainability 2023. Association of American Railroads https://www.aar.org/article/freight-rail-moving-miles-ahead-on-sustainability/ (accessed 3 August 2023).
-
Kruse, J., Warner, J. E. & Olson, L. E. A Modal Comparison of Domestic Freight Transportation Effects on the General Public: 2001–2014 (National Waterways Foundation, Texas A&M Transportation Institute, 2017).
-
Hughes, J. E. & Bushnell, J. B. Replication data for “The role of modal substitution in rebound effects within US freight transportation”. Zenodo https://doi.org/10.5281/zenodo.11264966 (2024).
Acknowledgements
We thank the Alfred P. Sloan Foundation for supporting this work. We also thank A. Jha and seminar participants at the UC Berkeley Energy Institute at Haas and the National Bureau of Economic Research conference on Transporting Energy for helpful comments.
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J.B.B. and J.E.H conceptualized the study and acquired the funding. J.E.H. developed the software. J.B.B. and J.E.H conducted the formal analysis and wrote and edited the paper.
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Bushnell, J.B., Hughes, J.E. The role of modal substitution in rebound effects within US freight transportation.
Nat Energy (2024). https://doi.org/10.1038/s41560-024-01568-w
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DOI: https://doi.org/10.1038/s41560-024-01568-w