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Industrial energy demand and energy efficiency – Evidence from Sweden

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  • Lundgren, Tommy
  • Marklund, Per-Olov
  • Zhang, Shanshan

Abstract

This paper estimates firm level energy demand and energy efficiency for 14 sectors in Swedish manufacturing using stochastic frontier analysis (SFA). We derive sector level energy demand frontiers that account for firm specific heterogeneity. Results show that there is potential to improve energy efficiency for fuel and electricity use in all sectors; energy intensity is not an appropriate proxy for energy efficiency; the EU ETS had a modest or no effect on Swedish firms’ efficient use of energy during the first trading phase and the beginning of the second, indicating that the carbon permit price was too low to generate the necessary incentives for energy efficiency investments.

Suggested Citation

  • Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
  • Handle: RePEc:eee:resene:v:43:y:2016:i:c:p:130-152
    DOI: 10.1016/j.reseneeco.2016.01.003
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    References listed on IDEAS

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    Cited by:

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    2. Amjadi, Golnaz & Lundgren, Tommy & Persson, Lars, 2018. "The Rebound Effect in Swedish Heavy Industry," Energy Economics, Elsevier, vol. 71(C), pages 140-148.
    3. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
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    6. Liao, Nuo & He, Yong, 2018. "Exploring the effects of influencing factors on energy efficiency in industrial sector using cluster analysis and panel regression model," Energy, Elsevier, vol. 158(C), pages 782-795.
    7. Lutz, Benjamin Johannes & Massier, Philipp & Sommerfeld, Katrin & Löschel, Andreas, 2017. "Drivers of energy efficiency in German manufacturing: A firm-level stochastic frontier analysis," ZEW Discussion Papers 17-068, ZEW - Leibniz Centre for European Economic Research.
    8. Sahoo, Nihar R. & Mohapatra, Pratap K.J. & Sahoo, Biresh K. & Mahanty, Biswajit, 2017. "Rationality of energy efficiency improvement targets under the PAT scheme in India – A case of thermal power plants," Energy Economics, Elsevier, vol. 66(C), pages 279-289.
    9. Gale A. Boyd and Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 39-62.
    10. A S M Monjurul Hasan & Mohammad Rokonuzzaman & Rashedul Amin Tuhin & Shah Md. Salimullah & Mahfuz Ullah & Taiyeb Hasan Sakib & Patrik Thollander, 2019. "Drivers and Barriers to Industrial Energy Efficiency in Textile Industries of Bangladesh," Energies, MDPI, Open Access Journal, vol. 12(9), pages 1-19, May.
    11. Manuel Llorca & José Baños & José Somoza & Pelayo Arbués, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    12. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    13. Dahlqvist, Anna & Lundgren, Tommy & Marklund, Per-Olov, 2017. "Assessing the Rebound Effect in Energy Intensive Industries: A Factor Demand Model Approach with Asymmetric Price Response," Working Papers 150, National Institute of Economic Research.
    14. Jia-Yin Yin & Yun-Fei Cao & Bao-Jun Tang, 2019. "Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 343-362, January.
    15. Bashir, Muhammad Farhan & MA, Benjiang & Shahbaz, Muhammad & Shahzad, Umer & Vo, Xuan Vinh, 2021. "Unveiling the heterogeneous impacts of environmental taxes on energy consumption and energy intensity: Empirical evidence from OECD countries," Energy, Elsevier, vol. 226(C).
    16. Zhang, H. & Fan, L.W. & Zhou, P., 2020. "Handling heterogeneity in frontier modeling of city-level energy efficiency: The case of China," Applied Energy, Elsevier, vol. 279(C).

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    More about this item

    Keywords

    Energy demand; Energy efficiency; Manufacturing industry; Stochastic frontier analysis; True random effects;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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