Assessment of Fuel Tax Policies to Tackle Carbon Emissions from Road Transport—An Application of the Value-Based DEA Method Including Robustness Analysis

  • Maria do Castelo Gouveia
  • Isabel Clímaco
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 149)


The transport sector has increased GHG emissions making it the second largest emitter in the EU after the energy generation sector. Given its share in total GHG emissions, the transport sector plays a critical role in the mitigation efforts required by the Paris Agreement on Climate Change. Fuel taxation can be used to internalize externalities, including those linked to fuel use as GHG emissions and local air pollution. Road transport policies have relied on fuel efficiency standards. A major outcome of this option was the prevailing preferential tax treatment for diesel fuel. This paper aims to assess the potential of fuel tax reforms to deal with carbon emissions from road transport in some EU countries. For this purpose, the Value-Based Data Envelopment Analysis method is used to obtain robust conclusions in face of sources of uncertainty. The adjustment of diesel excise tax levels towards gasoline taxation levels as well as the potential effects of introducing a carbon content-based tax on both diesel and gasoline are studied. The performance evaluation identifies the countries exhibiting the best practices. This approach offers decision makers the possibility to incorporate their priorities in appraising fuel tax policies considering uncertain factors to obtain robust conclusions.



This work has been supported by FCT—the Portuguese Foundation for Science and Technology under project grant UID/MULTI/00308/2013.


  1. Ajanovic, A., & Haas, R. (2012). The role of efficiency improvements vs. price effects for modelling passenger car transport demand and energy demand—Lessons from European countries. Energy Policy, 41, 36–46.CrossRefGoogle Scholar
  2. Ali, A. I., Lerme, C. S., & Seiford, L. (1995). Components of efficiency evaluation in data envelopment analysis. European Journal of Operational Research, 80(3), 462–473.CrossRefzbMATHGoogle Scholar
  3. Almeida, P. N., & Dias, L. C. (2012). Value-based DEA models: application-driven developments. Journal of the Operational Research Society, 63(1), 16–27.CrossRefGoogle Scholar
  4. Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264.CrossRefzbMATHGoogle Scholar
  5. Arbolino, R., & Romano, O. (2014). A methodological approach for assessing policies: The case of the environmental tax reform at European level. Procedia Economics and Finance., 17, 202–210.CrossRefGoogle Scholar
  6. Bonilla, D. (2009). Fuel demand on UK roads and dieselisation of fuel economy. Energy Policy, 37(10), 3769–3778.CrossRefGoogle Scholar
  7. Carreno, M., Ge, Y. E., & Borthwick, S. (2014). Could green taxation measures help incentivise future Chinese car drivers to purchase low emission vehicles? Transport, 29(3), 260–268.CrossRefGoogle Scholar
  8. Charnes, A., Cooper, W. W., Golany, B., Seiford, L., & Stutz, J. (1985). Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of Econometrics, 30, 91–107.MathSciNetCrossRefzbMATHGoogle Scholar
  9. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.MathSciNetCrossRefzbMATHGoogle Scholar
  10. Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4.CrossRefGoogle Scholar
  11. Coria, J. (2012). Fuel taxation in Europe. In Cars and carbon (pp. 201–222). Netherlands: Springer.Google Scholar
  12. European Commission. (2003). Restructuring the community framework for the taxation of energy products and electricity. Council Directive 2003/96/EC.Google Scholar
  13. European Commission. (2007). Communication from the Commission to the Council and the European Parliament Results of the review of the Community Strategy to reduce CO2 emissions from passenger cars and light-commercial vehicles. COM/2007/0019 final. Brussels.Google Scholar
  14. European Commission. (2011). Road map to a single European Transport Area—towards a competitive and resource efficient transport system. White Paper.Google Scholar
  15. Filipović, S., & Golušin, M. (2015). Environmental taxation policy in the EU—New methodology approach. Journal of Cleaner Production, 88, 308–317.CrossRefGoogle Scholar
  16. Flues, F., & Thomas, A. (2015). The distributional effect of energy taxes. OECD.
  17. Gago, A., Labandeira, X., & López-Otero, X. (2014). A panorama on energy taxes and green tax reforms. Hacienda Pública Española, 208(1), 145–190.CrossRefGoogle Scholar
  18. González, R. M., & Marrero, G. A. (2012). The effect of dieselization in passenger cars emissions for Spanish regions: 1998–2006. Energy Policy, 51, 213–222.CrossRefGoogle Scholar
  19. Gouveia, M. C., Dias, L. C., & Antunes, C. H. (2008). Additive DEA based on MCDA with imprecise information. Journal of the Operational Research Society, 59(1), 54–63.CrossRefzbMATHGoogle Scholar
  20. Gouveia, M. C., Dias, L. C., & Antunes, C. H. (2013). Super-efficiency and stability intervals in additive DEA. Journal of the Operational Research Society, 64(1), 86–96.CrossRefGoogle Scholar
  21. Gouveia, M. C., Dias, L. C., Antunes, C. H., Boucinha, J., & Inácio, C. F. (2015). Benchmarking of maintenance and outage repair in an electricity distribution company using the Value-Based DEA method. Omega, 53, 104–114.CrossRefGoogle Scholar
  22. Gouveia, M. C., & Dias, L. C., Antunes, Mota, M. A., Duarte, E. M., & Tenreiro, E. M. (2016). An application of an additive DEA model to identify best practices in primary health care. OR Spectrum, 38(3), 743–767.Google Scholar
  23. Harding, M. (2014). The diesel differential—Differences in the tax treatment of gasoline and diesel for road use. OECD Taxation paper no. 21.Google Scholar
  24. Kloess, M., & Müller, A. (2011). Simulating the impact of policy. energy prices and technological progress on the passenger car fleet in Austria—A model based analysis 2010–2050. Energy Policy, 39(9), 5045–5062.CrossRefGoogle Scholar
  25. Mardani, A., Zavadskas, E. K., Streimikiene, D., Jusoh, A., & Khoshnoudi, M. (2017). A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency. Renewable and Sustainable Energy Reviews, 70, 1298–1322.CrossRefGoogle Scholar
  26. Newbery, D. M. (1992). Should carbon taxes be additional to other fuel transport taxes? The Energy Journal, 13(2), 49–60.CrossRefGoogle Scholar
  27. Newbery, D. M. (2001). Harmonizing energy taxes in the EU. In Tax Policy in the European Union Conference, Erasmus University, October 17–19, 2001.Google Scholar
  28. Newbery, D. M. (2005). Why tax energy? Towards a more rational energy policy. The Energy Journal, 26(3), 1–39.CrossRefGoogle Scholar
  29. Parry, I. W. H. (2007). Are the costs of reducing greenhouse gases from passenger vehicles negative? Journal of Urban Economics., 62(2), 273–293.CrossRefGoogle Scholar
  30. Parry, I. W. H., & Small, K. A. (2005). Does Britain or the United States have the right gasoline tax? American Economic Review, 95(4), 1276–1289.CrossRefGoogle Scholar
  31. Rodríguez-López, J., Marrero, G. A., & González-Marrero, R. M. (2015). Dieselization, CO2 emissions and fuel taxes in Europe. In Working Papers, November 15, 2015.Google Scholar
  32. Ryan, L., Ferreira, S., & Convery, F. (2009). The impact of fiscal and other measures on new passenger car sales and CO2 emissions intensity: evidence from Europe. Energy Economics, 31, 365–374.CrossRefGoogle Scholar
  33. Santos, G. (2017). Road fuel taxes in Europe: Do they internalize road transport externalities? Transport Policy, 53, 120–134.CrossRefGoogle Scholar
  34. Schipper, L., & Fulton, L. (2013). Dazzled by diesel? The impact on carbon dioxide emissions of the shift to diesels in Europe through 2009. Energy Policy, 54, 3–10.CrossRefGoogle Scholar
  35. Seiford, L. M., & Zhu, J. (1998a). Stability regions for maintaining efficiency in data envelopment analysis. European Journal of Operational Research, 108, 127–139.CrossRefzbMATHGoogle Scholar
  36. Seiford, L. M., & Zhu, J. (1998b). Sensitivity analysis of DEA models for simultaneous changes in all the data. Journal of the Operational Research Society, 49, 1060–1071.CrossRefzbMATHGoogle Scholar
  37. Sterner, T. (2007). Fuel taxes: An important instrument for climate policy. Energy Policy, 35(6), 3194–3202.CrossRefGoogle Scholar
  38. Sterner, T., & Köhlin, G. (2015). Pricing carbon: The challenges. In S. Barrett, C. Carraro, & J. de Melo (Eds.), Towards a workable and effective climate regime (p. 251).Google Scholar
  39. United States Environmental Protection Agency. (2011). Greenhouse gas emissions from a typical passenger vehicle.
  40. von Winterfeldt, D., & Edwards, W. (1986). Decision analysis behavioral research. New York: Cambridge University Press.Google Scholar
  41. Zhu, J. (1996). Robustness of the efficient DMUs in data envelopment analysis. European Journal of Operational Research, 90, 451–460.CrossRefzbMATHGoogle Scholar
  42. Zhu, J. (2001). Super-efficiency and DEA sensitivity analysis. European Journal of Operational Research, 129, 443–455.MathSciNetCrossRefzbMATHGoogle Scholar
  43. Zhu, J. (2003). Imprecise data envelopment analysis (IDEA): A review and improvement with an application. European Journal of Operational Research, 144, 513–529.MathSciNetCrossRefzbMATHGoogle Scholar
  44. Zimmer, A., & Koch, N. (2016). Fuel consumption dynamics in Europe—Implications of fuel tax reforms for air pollution and carbon emissions from road transport. Available at August 28, 2016.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.ISCA—Coimbra Business SchoolPolytechnic Institute of CoimbraCoimbraPortugal
  2. 2.INESC CoimbraCoimbraPortugal
  3. 3.Centre for Health Studies and ResearchUniversity of CoimbraCoimbraPortugal

Personalised recommendations