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US long-term energy intensity: Backcast and projection

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  • Dowlatabadi, Hadi
  • Oravetz, Matthew A.

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  • Dowlatabadi, Hadi & Oravetz, Matthew A., 2006. "US long-term energy intensity: Backcast and projection," Energy Policy, Elsevier, vol. 34(17), pages 3245-3256, November.
    • Handle: RePEc:eee:enepol:v:34:y:2006:i:17:p:3245-3256
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    2. Shahiduzzaman, Md & Layton, Allan, 2017. "Decomposition analysis for assessing the United States 2025 emissions target: How big is the challenge?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 372-383.
    3. Klaus Keller & Louise I. Miltich & Alexander Robinson & Richard S.J. Tol, 2007. "How Overconfident are Current Projections of Anthropogenic Carbon Dioxide Emissions?," Working Papers 2007.39, Fondazione Eni Enrico Mattei.
    4. Sue Wing, Ian, 2008. "Explaining the declining energy intensity of the U.S. economy," Resource and Energy Economics, Elsevier, vol. 30(1), pages 21-49, January.
    5. Sue Wing, Ian & Eckaus, Richard S., 2007. "The implications of the historical decline in US energy intensity for long-run CO2 emission projections," Energy Policy, Elsevier, vol. 35(11), pages 5267-5286, November.
    6. Zha, Jianping & Tan, Ting & Fan, Rong & Xu, Han & Ma, Siqi, 2020. "How to reduce energy intensity to achieve sustainable development of China's transport sector? A cross-regional comparison analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    7. Kemp-Benedict, Eric, 2014. "The inverted pyramid: A neo-Ricardian view on the economy–environment relationship," Ecological Economics, Elsevier, vol. 107(C), pages 230-241.
    8. Bo Li & Jicong Yang & Wei Sun, 2022. "Can Expanding Cultural Consumption Improve Urban Air Quality? An Analysis Based on China’s Cultural Consumption Pilot Policy," IJERPH, MDPI, vol. 20(1), pages 1-20, December.
    9. Kialashaki, Arash & Reisel, John R., 2014. "Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States," Energy, Elsevier, vol. 76(C), pages 749-760.
    10. An, Kangxin & Wang, Can & Cai, Wenjia, 2023. "Low-carbon technology diffusion and economic growth of China: an evolutionary general equilibrium framework," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 253-263.
    11. Ahlroth, Sofia & Hojer, Mattias, 2007. "Sustainable energy prices and growth: Comparing macroeconomic and backcasting scenarios," Ecological Economics, Elsevier, vol. 63(4), pages 722-731, September.
    12. Okushima, Shinichiro & Tamura, Makoto, 2011. "Identifying the sources of energy use change: Multiple calibration decomposition analysis and structural decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 22(4), pages 313-326.
    13. Li, Yi & Sun, Linyan & Feng, Taiwen & Zhu, Chunyan, 2013. "How to reduce energy intensity in China: A regional comparison perspective," Energy Policy, Elsevier, vol. 61(C), pages 513-522.
    14. Jean-Francois Mercure, 2012. "On the changeover timescales of technology transitions and induced efficiency changes: an overarching theory," Papers 1209.0424, arXiv.org.
    15. Livas-García, A. & Bonilla, D. & Escalante Soberanis, M.A. & Bassam, A., 2019. "Projecting the energy pathway using a methodological sequence: The case of Mexico," Energy Policy, Elsevier, vol. 135(C).

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