IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v41y2020i2p143-166.html
   My bibliography  Save this article

Carbon Tax and Energy Intensity: Assessing the Channels of Impact using UK Microdata

Author

Listed:
  • Morakinyo O. Adetutu
  • Kayode A. Odusany
  • Thomas G. Weyman-Jones

Abstract

Prior empirical studies indicate that carbon taxes have a negative impact on energy intensity, yet, the literature is unable to shed much light on the channels through which a moderate carbon tax reduces industrial energy intensity. Using a two-stage econometric approach, we provide the first comprehensive analysis of the five components of the energy intensity gain (EIG) arising from the UK climate change levy (CCL). First, we propose an EIG decomposition based on a stochastic energy cost frontier and a confidential panel of UK manufacturing plants covering 2001-2006. In the second stage, we identify the impact of the CCL on EIG components using an instrumental variable (IV) approach that addresses the endogeneity of the carbon tax rules. Factor substitution and technological progress are the dominant firm responses to the CCL, while energy efficiency is surprisingly the least responsive component. Our findings underscore the challenge arising from overreliance on narrow energy policy objectives such as energy efficiency improvements, suggesting that a broader policy approach aimed at improving overall firm resource allocation might be more appropriate.

Suggested Citation

  • Morakinyo O. Adetutu & Kayode A. Odusany & Thomas G. Weyman-Jones, 2020. "Carbon Tax and Energy Intensity: Assessing the Channels of Impact using UK Microdata," The Energy Journal, , vol. 41(2), pages 143-166, March.
  • Handle: RePEc:sae:enejou:v:41:y:2020:i:2:p:143-166
    DOI: 10.5547/01956574.41.2.made
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.41.2.made
    Download Restriction: no

    File URL: https://libkey.io/10.5547/01956574.41.2.made?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Barker, Terry & Ekins, Paul & Foxon, Tim, 2007. "Macroeconomic effects of efficiency policies for energy-intensive industries: The case of the UK Climate Change Agreements, 2000-2010," Energy Economics, Elsevier, vol. 29(4), pages 760-778, July.
    2. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    3. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    4. Philippe Aghion & Antoine Dechezleprêtre & David Hémous & Ralf Martin & John Van Reenen, 2016. "Carbon Taxes, Path Dependency, and Directed Technical Change: Evidence from the Auto Industry," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 1-51.
    5. Morakinyo O. Adetutu, Anthony J. Glass, and Thomas G. Weyman-Jones, 2016. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. H. Wang & B.W. Ang & P. Zhou, 2018. "Decomposing aggregate CO2 emission changes with heterogeneity: An extended production-theoretical approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    7. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
    8. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    9. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    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. Rui Tang & Dingyao Yu & Yongbo Tan, 2025. "Navigating the Carbon Challenge: Strategic Integration of Hybrid Policies in Green Supply Chains," Sustainability, MDPI, vol. 17(6), pages 1-23, March.
    2. Hua Li & Wei Zhao & Weijun Wang & Yifan Zhang & Qin Zhang, 2024. "What Determines Rural Residents’ Intention and Behavior Towards Clean Energy Use? Evidence from Northwest China," Sustainability, MDPI, vol. 16(24), pages 1-16, December.

    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. Gale A. Boyd & Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, , vol. 41(3), pages 39-62, May.
    2. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    3. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    4. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    5. 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.
    6. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    7. Abudureheman, Maliyamu & Jiang, Qingzhe & Dong, Xiucheng & Dong, Cong, 2022. "Spatial effects of dynamic comprehensive energy efficiency on CO2 reduction in China," Energy Policy, Elsevier, vol. 166(C).
    8. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    9. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    10. Xu, Mengmeng & Tan, Ruipeng & He, Xinju, 2022. "How does economic agglomeration affect energy efficiency in China?: Evidence from endogenous stochastic frontier approach," Energy Economics, Elsevier, vol. 108(C).
    11. Kerui Du, Shuai Shao, and Zheming Yan, 2021. "Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    12. 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).
    13. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    14. Yue Liu & Siming Liu & Xueying Xu & Pierre Failler, 2020. "Does Energy Price Induce China’s Green Energy Innovation?," Energies, MDPI, vol. 13(15), pages 1-18, August.
    15. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    16. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    17. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    18. Li, Jianglong & Liu, Hongxun & Du, Kerui, 2019. "Does market-oriented reform increase energy rebound effect? Evidence from China's regional development," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    19. Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    20. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.

    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:sae:enejou:v:41:y:2020:i:2:p:143-166. 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: SAGE Publications (email available below). General contact details of provider: .

    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.