IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1612-d146955.html
   My bibliography  Save this article

Policies and Predictions for a Low-Carbon Transition by 2050 in Passenger Vehicles in East Asia: Based on an Analysis Using the E3ME-FTT Model

Author

Listed:
  • Aileen Lam

    (Department of Economics, Faculty of Social Sciences, University of Macao, E21, Taipa, Macau, China
    Department of Land Economy, University of Cambridge, 19 Silver Street, Cambridge CB31EP, UK)

  • Soocheol Lee

    (Faculty of Economics, Meijo University, 501 Shiogamaguchi, Tenparku, Nagoya 468-0073, Japan)

  • Jean-François Mercure

    (Department of Land Economy, University of Cambridge, 19 Silver Street, Cambridge CB31EP, UK
    Department of Environmental Science, Radbound University, 6500 GL Nijmegen, The Netherlands
    Department of International Modelling, Cambridge Econometrics, Covent Garden, Cambridge CB12HT, UK)

  • Yongsung Cho

    (Department of Food and Resource Economics, Korea University, Korea Center for Green Economy, Anamdong, Seoul 02841, Korea)

  • Chun-Hsu Lin

    (Chung-Hua Institution for Economic Research, Taipei 1106, Taiwan)

  • Hector Pollitt

    (Department of Land Economy, University of Cambridge, 19 Silver Street, Cambridge CB31EP, UK
    Department of International Modelling, Cambridge Econometrics, Covent Garden, Cambridge CB12HT, UK)

  • Unnada Chewpreecha

    (Department of International Modelling, Cambridge Econometrics, Covent Garden, Cambridge CB12HT, UK)

  • Sophie Billington

    (Department of International Modelling, Cambridge Econometrics, Covent Garden, Cambridge CB12HT, UK)

Abstract

In this paper we apply a model of technological diffusion, Future Technology Transformations in the Transport Sector (FTT: Transport), linked to the E3ME macroeconomic model, to study possible future technological transitions in personal passenger transport in four East Asian countries. We assess how targeted policies could impact on these transitions by defining four scenarios based on policies that aim to reduce emissions from transport. For each country we find that an integrated approach of tax incentives, subsidies, regulations (fuel economy efficiency), kick-start programs and biofuel programs yield the most significant emission reductions because, when combined, they accelerate effectively the diffusion of electric vehicles in the region.

Suggested Citation

  • Aileen Lam & Soocheol Lee & Jean-François Mercure & Yongsung Cho & Chun-Hsu Lin & Hector Pollitt & Unnada Chewpreecha & Sophie Billington, 2018. "Policies and Predictions for a Low-Carbon Transition by 2050 in Passenger Vehicles in East Asia: Based on an Analysis Using the E3ME-FTT Model," Sustainability, MDPI, vol. 10(5), pages 1-32, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1612-:d:146955
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1612/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/5/1612/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Don Fullerton & Li Gan & Miwa Hattori, 2015. "A model to evaluate vehicle emission incentive policies in Japan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(1), pages 79-108, January.
    4. H. Pollitt & J. -F. Mercure, 2015. "The role of money and the financial sector in energy-economy models used for assessing climate policy," Papers 1512.02912, arXiv.org.
    5. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    6. Ko, Ahyun & Myung, Cha-Lee & Park, Simsoo & Kwon, Sangil, 2014. "Scenario-based CO2 emissions reduction potential and energy use in Republic of Korea’s passenger vehicle fleet," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 346-356.
    7. Mercure, Jean-François, 2012. "FTT:Power : A global model of the power sector with induced technological change and natural resource depletion," Energy Policy, Elsevier, vol. 48(C), pages 799-811.
    8. Fanchao Liao & Eric Molin & Bert van Wee, 2017. "Consumer preferences for electric vehicles: a literature review," Transport Reviews, Taylor & Francis Journals, vol. 37(3), pages 252-275, May.
    9. Jean-Jacques Chanaron, 1998. "Automobiles: a static technology, a ""wait-and-see"" industry ?," Grenoble Ecole de Management (Post-Print) halshs-00143994, HAL.
    10. Hector Pollitt & Jean-Francois Mercure, 2018. "The role of money and the financial sector in energy-economy models used for assessing climate and energy policy," Climate Policy, Taylor & Francis Journals, vol. 18(2), pages 184-197, February.
    11. Jean-Jacques Chanaron, 1998. "Automobiles: a static technology, a ""wait-and-see"" industry ?," Post-Print halshs-00143994, HAL.
    12. Huiming Gong & Michael Wang & Hewu Wang, 2013. "New energy vehicles in China: policies, demonstration, and progress," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 18(2), pages 207-228, February.
    13. Oshiro, Ken & Masui, Toshihiko, 2015. "Diffusion of low emission vehicles and their impact on CO2 emission reduction in Japan," Energy Policy, Elsevier, vol. 81(C), pages 215-225.
    14. Soocheol Lee & Unnada Chewpreecha & Hector Pollitt & Satoshi Kojima, 2018. "An economic assessment of carbon tax reform to meet Japan’s NDC target under different nuclear assumptions using the E3ME model," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 411-429, April.
    15. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    16. Wang, Hailin & Ou, Xunmin & Zhang, Xiliang, 2017. "Mode, technology, energy consumption, and resulting CO2 emissions in China's transport sector up to 2050," Energy Policy, Elsevier, vol. 109(C), pages 719-733.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Odenweller, Adrian, 2022. "Climate mitigation under S-shaped energy technology diffusion: Leveraging synergies of optimisation and simulation models," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    2. Elena Magaril & Romen Magaril & Hussain H. Al-Kayiem & Elena Skvortsova & Ilya Anisimov & Elena Cristina Rada, 2019. "Investigation on the Possibility of Increasing the Environmental Safety and Fuel Efficiency of Vehicles by Means of Gasoline Nano-Additive," Sustainability, MDPI, vol. 11(7), pages 1-10, April.
    3. Shih, Hsiu-Ching & Chiang, Chia-Yun & Lai, Hsin-Chih & Hsiao, Min-Chuan & Chen, Li-Heng & Ma, Hwong-wen, 2023. "Assessing the nexus of electric vehicle and energy policies on health risks," Energy, Elsevier, vol. 282(C).
    4. Anders F. Jensen & Thomas K. Rasmussen & Carlo G. Prato, 2020. "A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    5. José M. Cansino & Antonio Sánchez-Braza & Teresa Sanz-Díaz, 2018. "Policy Instruments to Promote Electro-Mobility in the EU28: A Comprehensive Review," Sustainability, MDPI, vol. 10(7), pages 1-27, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Soocheol Lee & Unnada Chewpreecha & Hector Pollitt & Satoshi Kojima, 2018. "An economic assessment of carbon tax reform to meet Japan’s NDC target under different nuclear assumptions using the E3ME model," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 411-429, April.
    2. Jean-François Mercure, 2015. "An age structured demographic theory of technological change," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 787-820, September.
    3. Knobloch, Florian & Pollitt, Hector & Chewpreecha, Unnada & Lewney, Richard & Huijbregts, Mark A.J. & Mercure, Jean-Francois, 2021. "FTT:Heat — A simulation model for technological change in the European residential heating sector," Energy Policy, Elsevier, vol. 153(C).
    4. Dmitry V. Pelegov & Jean-Jacques Chanaron, 2022. "Electric Car Market Analysis Using Open Data: Sales, Volatility Assessment, and Forecasting," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    5. Floor Brouwer & Lydia Vamvakeridou-Lyroudia & Eva Alexandri & Ingrida Bremere & Matthew Griffey & Vincent Linderhof, 2018. "The Nexus Concept Integrating Energy and Resource Efficiency for Policy Assessments: A Comparative Approach from Three Cases," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    6. 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.
    7. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
    8. 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).
    9. Martin Kalthaus & Jiatang Sun, 2021. "Determinants of Electric Vehicle Diffusion in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 80(3), pages 473-510, November.
    10. Jean-Jacques Chanaron & Julius Teske, 2007. "Hybrid vehicles: a temporary step," Post-Print halshs-00207392, HAL.
    11. F. Knobloch & J. -F. Mercure, 2016. "The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents," Papers 1603.06888, arXiv.org.
    12. Kristoffer Palage & Robert Lundmark & Patrik Söderholm, 2019. "The innovation effects of renewable energy policies and their interaction: the case of solar photovoltaics," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 21(2), pages 217-254, April.
    13. Mark Meyer & Martin Hirschnitz-Garbers & Martin Distelkamp, 2018. "Contemporary Resource Policy and Decoupling Trends—Lessons Learnt from Integrated Model-Based Assessments," Sustainability, MDPI, vol. 10(6), pages 1-28, June.
    14. Mazzucato, Mariana & Semieniuk, Gregor, 2018. "Financing renewable energy: Who is financing what and why it matters," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 8-22.
    15. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    16. van den Heuvel, Stijn T.A. & van den Bergh, Jeroen C.J.M., 2009. "Multilevel assessment of diversity, innovation and selection in the solar photovoltaic industry," Structural Change and Economic Dynamics, Elsevier, vol. 20(1), pages 50-60, March.
    17. Jin, Wei & Zhang, ZhongXiang, 2014. "Explaining the Slow Pace of Energy Technological Innovation Why Market Conditions Matter?," Energy: Resources and Markets 165758, Fondazione Eni Enrico Mattei (FEEM).
    18. Shih, Hsiu-Ching & Chiang, Chia-Yun & Lai, Hsin-Chih & Hsiao, Min-Chuan & Chen, Li-Heng & Ma, Hwong-wen, 2023. "Assessing the nexus of electric vehicle and energy policies on health risks," Energy, Elsevier, vol. 282(C).
    19. James Holehouse & Hector Pollitt, 2021. "Non-equilibrium time-dependent solution to discrete choice with social interactions," Papers 2109.09633, arXiv.org, revised Jan 2022.
    20. Ekaterina Rhodes & Kira Craig & Aaron Hoyle & Madeleine McPherson, 2021. "How Do Energy-Economy Models Compare? A Survey of Model Developers and Users in Canada," Sustainability, MDPI, vol. 13(11), pages 1-39, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1612-:d:146955. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.