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Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 ∘C

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  • J.-F. Mercure

    (Radboud University
    University of Cambridge
    Cambridge Econometrics Ltd)

  • A. Lam

    (University of Cambridge
    University of Macau)

  • S. Billington

    (Cambridge Econometrics Ltd)

  • H. Pollitt

    (Cambridge Econometrics Ltd)

Abstract

Transport generates a large and growing component of global greenhouse gas emissions contributing to climate change. Effective transport emissions reduction policies are needed in order to reach a climate target well below 2 ∘C. Representations of technology evolution in current integrated assessment models (IAM) make use of systems optimisations that may not always provide sufficient insight on consumer response to realistic policy packages for extensive use in policy-making. Here, we introduce FTT: transport, an evolutionary technology diffusion simulation model for road transport technology, as an IAM sub-component, which features sufficiently realistic features of consumers and of existing technological trajectories that enables to simulate the impact of detailed climate policies in private passenger road transport. Integrated to the simulation-based macroeconometric IAM E3ME-FTT, a plausible scenario of transport decarbonisation is given, defined by a detailed transport policy package, that reaches sufficient emissions reductions to achieve the 2 ∘C target of the Paris Agreement.

Suggested Citation

  • J.-F. Mercure & A. Lam & S. Billington & H. Pollitt, 2018. "Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 ∘C," Climatic Change, Springer, vol. 151(2), pages 109-129, November.
  • Handle: RePEc:spr:climat:v:151:y:2018:i:2:d:10.1007_s10584-018-2262-7
    DOI: 10.1007/s10584-018-2262-7
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    1. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    2. J. -F. Mercure & H. Pollitt & A. M. Bassi & J. E Vi~nuales & N. R. Edwards, 2015. "Modelling complex systems of heterogeneous agents to better design sustainability transitions policy," Papers 1506.07432, arXiv.org, revised Feb 2016.
    3. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    4. Jean-François Mercure, 2015. "An age structured demographic theory of technological change," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 787-820, September.
    5. Searchinger, Timothy & Heimlich, Ralph & Houghton, R. A. & Dong, Fengxia & Elobeid, Amani & Fabiosa, Jacinto F. & Tokgoz, Simla & Hayes, Dermot J. & Yu, Hun-Hsiang, 2008. "Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change," Staff General Research Papers Archive 12881, Iowa State University, Department of Economics.
    6. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    7. Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
    8. Aini, M.S. & Chan, S.C. & Syuhaily, O., 2013. "Predictors of technical adoption and behavioural change to transport energy-saving measures in response to climate change," Energy Policy, Elsevier, vol. 61(C), pages 1055-1062.
    9. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    10. Daly, Hannah E. & Ramea, Kalai & Chiodi, Alessandro & Yeh, Sonia & Gargiulo, Maurizio & Gallachóir, Brian Ó, 2014. "Incorporating travel behaviour and travel time into TIMES energy system models," Applied Energy, Elsevier, vol. 135(C), pages 429-439.
    11. Meghan R. Busse & Christopher R. Knittel & Florian Zettelmeyer, 2013. "Are Consumers Myopic? Evidence from New and Used Car Purchases," American Economic Review, American Economic Association, vol. 103(1), pages 220-256, February.
    12. Mercure, Jean-François & Salas, Pablo, 2012. "An assessement of global energy resource economic potentials," Energy, Elsevier, vol. 46(1), pages 322-336.
    13. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    14. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    15. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    16. Rivers, Nic & Jaccard, Mark, 2006. "Useful models for simulating policies to induce technological change," Energy Policy, Elsevier, vol. 34(15), pages 2038-2047, October.
    17. Itf, 2010. "Stimulating Low-Carbon Vehicle Technologies: Summary and Conclusions," OECD/ITF Joint Transport Research Centre Discussion Papers 2010/13, OECD Publishing.
    18. Baltas, George & Saridakis, Charalampos, 2013. "An empirical investigation of the impact of behavioural and psychographic consumer characteristics on car preferences: An integrated model of car type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 92-110.
    19. Arthur, W. Brian & Lane, David A., 1993. "Information contagion," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 81-104, June.
    20. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    21. Mercure, Jean-François & Salas, Pablo, 2013. "On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities," Energy Policy, Elsevier, vol. 63(C), pages 469-483.
    22. Henri-David Waisman & Celine Guivarch & Franck Lecocq, 2013. "The transportation sector and low-carbon growth pathways: modelling urban, infrastructure, and spatial determinants of mobility," Climate Policy, Taylor & Francis Journals, vol. 13(sup01), pages 106-129, March.
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    Cited by:

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    2. Florian Leblanc & Ruben Bibas & Silvana Mima & Matteo Muratori & Shogo Sakamoto & Fuminori Sano & Nico Bauer & Vassilis Daioglou & Shinichiro Fujimori & Matthew J. Gidden & Estsushi Kato & Steven K. R, 2022. "The contribution of bioenergy to the decarbonization of transport: a multi-model assessment," Climatic Change, Springer, vol. 170(3), pages 1-21, February.
    3. Mercure, J.-F. & Paim, M.A. & Bocquillon, P. & Lindner, S. & Salas, P. & Martinelli, P. & Berchin, I.I. & de Andrade Guerra, J.B.S.O & Derani, C. & de Albuquerque Junior, C.L. & Ribeiro, J.M.P. & Knob, 2019. "System complexity and policy integration challenges: The Brazilian Energy- Water-Food Nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 230-243.
    4. Florian Leblanc & Ruben Bibas & Silvana Mima & Matteo Muratori & Shogo Sakamoto & Fuminori Sano & Nico Bauer & Vassilis Daioglou & Shinichiro Fujimori & Matthew J Gidden & Estsushi Kato & Steven K Ros, 2022. "The contribution of bioenergy to the decarbonization of transport: a multi-model assessment," Post-Print hal-03558507, HAL.
    5. Hafner, Sarah & Anger-Kraavi, Annela & Monasterolo, Irene & Jones, Aled, 2020. "Emergence of New Economics Energy Transition Models: A Review," Ecological Economics, Elsevier, vol. 177(C).
    6. Walter, Antonia & Held, Maximilian & Pareschi, Giacomo & Pengg, Hermann & Madlener, Reinhard, 2020. "Decarbonizing the European Automobile Fleet: Impacts of 1.5 °C-compliant Climate Policies in Germany and Norway," FCN Working Papers 18/2020, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    7. Paul Wolfram & Qingshi Tu & Niko Heeren & Stefan Pauliuk & Edgar G. Hertwich, 2021. "Material efficiency and climate change mitigation of passenger vehicles," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 494-510, April.

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