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Assessment of the improvement in energy intensity by the new high-speed railway in Japan

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  • Akihiro Otsuka

    (Yokohama City University, Association of International Arts and Science)

Abstract

Energy intensity improvement is an influential policy agenda for global environmental problem-solving and sustainability enhancement. This study focuses on inter-regional networks’ impact on energy intensity and statistically examines whether the improvement of such networks promotes a modal shift from passenger vehicles to railways. The results indicate the nonlinear relationship between the improvement of inter-regional networks and the variation of the passenger vehicle sector’s energy consumption. Furthermore, the results reveal that the laying of high-speed railways, which helps strengthen inter-regional networks, can significantly improve regional energy intensity. This result has valuable implications for Japan’s national land plan. The high-quality transportation infrastructure, such as high-speed railways, to be introduced in the country can potentially change the energy consumption patterns in inter-regional travel and improve energy intensity. Our results suggest that the installation of the high-speed railway will effectively reduce carbon dioxide emissions. This revelation is expected to provide new policy evidence to scholars and policymakers.

Suggested Citation

  • Akihiro Otsuka, 2022. "Assessment of the improvement in energy intensity by the new high-speed railway in Japan," Asia-Pacific Journal of Regional Science, Springer, vol. 6(1), pages 267-282, February.
    • Handle: RePEc:spr:apjors:v:6:y:2022:i:1:d:10.1007_s41685-020-00165-5
    DOI: 10.1007/s41685-020-00165-5
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    1. Chen, Zhenhua & Xue, Junbo & Rose, Adam Z. & Haynes, Kingsley E., 2016. "The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 232-245.
    2. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    3. Evert Meijers & Martijn Burger & Roberto Camagni & Roberta Capello & Andrea Caragliu, 2016. "Static vs. dynamic agglomeration economies. Spatial context and structural evolution behind urban growth," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 133-158, March.
    4. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    5. Akihiro Otsuka, 2018. "Dynamics of agglomeration, accessibility, and total factor productivity: evidence from Japanese regions," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(7), pages 611-627, October.
    6. Jetpan Wetwitoo & Hironori Kato, 2017. "Inter-regional transportation and economic productivity: a case study of regional agglomeration economies in Japan," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(2), pages 321-344, September.
    7. Peter Pedroni, 2001. "Purchasing Power Parity Tests In Cointegrated Panels," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 727-731, November.
    8. Evert Meijers & Martijn Burger & Michiel Meeteren & Zachary Neal & Ben Derudder, 2016. "Disentangling agglomeration and network externalities: A conceptual typology," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 61-80, March.
    9. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    10. Akihiro Otsuka & Mika Goto, 2018. "Regional determinants of energy intensity in Japan: the impact of population density," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 257-278, August.
    11. Akihiro Otsuka, 2019. "Natural disasters and electricity consumption behavior: a case study of the 2011 Great East Japan Earthquake," Asia-Pacific Journal of Regional Science, Springer, vol. 3(3), pages 887-910, October.
    12. Costantini, Valeria & Martini, Chiara, 2010. "The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data," Energy Economics, Elsevier, vol. 32(3), pages 591-603, May.
    13. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    14. Evert Meijers & Martijn Burger & Martijn J. Burger & Evert J. Meijers, 2016. "Agglomerations and the rise of urban network externalities," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 5-15, March.
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    Cited by:

    1. Hao Wang & Tao Zhang & Xi Wang, 2024. "High-speed railways reduces carbon emissions: mediating effects of green innovation and the resilience of environmental investment," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-24, December.
    2. Weiya Chen & Yongzhuo Yu & Xiaoping Fang & Ziyue Yuan & Shiying Tong, 2023. "Using Mixed Methods to Identify Evaluation Indicators for Green Railway Transportation Operations in China," Sustainability, MDPI, vol. 15(24), pages 1-20, December.
    3. Yoshiro Higano & Akihiro Otsuka, 2022. "Special Feature on Regional Sustainability: analysis in a spatial and regional context with broad perspectives on the risk of global warming, natural disasters, and emerging issues due to the globaliz," Asia-Pacific Journal of Regional Science, Springer, vol. 6(1), pages 239-245, February.
    4. Elżbieta Szaruga & Elżbieta Załoga & Arkadiusz Drewnowski & Paulina Dąbrosz-Drewnowska, 2023. "Convergence of Energy Intensity of the Export of Goods by Rail Transport: Linkages with the Spatial Integration and Economic Condition of Countries," Energies, MDPI, vol. 16(9), pages 1-24, April.

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    More about this item

    Keywords

    Inter-regional network; High-speed railway; Modal shift; Energy intensity; Panel data analysis;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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