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Monitoring energy efficiency trends in European industry: Which top-down method should be used?

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  • Cahill, Caiman J.
  • Ó Gallachóir, Brian P.

Abstract

Several index decomposition methods are commonly employed to provide a top-down view of energy consumption trends in manufacturing industry. These approaches typically use value added data for an industrial sector to decompose energy trends into structural, intensity and activity effects. Additionally in Europe a commonly employed top-down indicator called ODEX uses units of physical output, rather than value added, to analyse energy efficiency developments only. Therefore it has been difficult to compare ODEX directly to decomposition approaches. This paper presents a new decomposition method called VALDEX, based on the existing ODEX methodology, but using value added data. Extending ODEX to a full decomposition method allows tests commonly used in index decomposition theory to be applied and enables direct comparison with other methods. This helps evaluate the robustness of the existing ODEX methodology. Using industry data from three European countries, the results yielded by five decomposition methods are compared. In the cases examined, both the Laspeyres and VALDEX methods have significant residuals. Laspeyres consistently overestimates total energy consumption while VALDEX underestimates it. Methods that produce small or no unexplained residuals give converging results for each effect for the countries analysed, and provide a more reliable view of energy trends.

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  • Cahill, Caiman J. & Ó Gallachóir, Brian P., 2010. "Monitoring energy efficiency trends in European industry: Which top-down method should be used?," Energy Policy, Elsevier, vol. 38(11), pages 6910-6918, November.
  • Handle: RePEc:eee:enepol:v:38:y:2010:i:11:p:6910-6918
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    References listed on IDEAS

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    Cited by:

    1. Hannah Förster & Katja Schumacher & Enrica De Cian & Michael Hübler & Ilkka Keppo & Silvana Mima & Ronald D. Sands, 2013. "European Energy Efficiency And Decarbonization Strategies Beyond 2030 — A Sectoral Multi-Model Decomposition," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 4(supp0), pages 1-29.
    2. Schlomann, Barbara & Reuter, Matthias & Lapillonne, Bruno & Pollier, Karine & Rosenow, Jan, 2014. "Monitoring of the "Energiewende": Energy efficiency indicators for Germany," Working Papers "Sustainability and Innovation" S10/2014, Fraunhofer Institute for Systems and Innovation Research (ISI).
    3. Guarino, Francesco & Cassarà, Pietro & Longo, Sonia & Cellura, Maurizio & Ferro, Erina, 2015. "Load match optimisation of a residential building case study: A cross-entropy based electricity storage sizing algorithm," Applied Energy, Elsevier, vol. 154(C), pages 380-391.
    4. Tan, Xianchun & Dong, Lele & Chen, Dexue & Gu, Baihe & Zeng, Yuan, 2016. "China’s regional CO2 emissions reduction potential: A study of Chongqing city," Applied Energy, Elsevier, vol. 162(C), pages 1345-1354.
    5. Xu, Jin-Hua & Fan, Ying & Yu, Song-Min, 2014. "Energy conservation and CO2 emission reduction in China's 11th Five-Year Plan: A performance evaluation," Energy Economics, Elsevier, vol. 46(C), pages 348-359.
    6. Xu, Jin-Hua & Fleiter, Tobias & Eichhammer, Wolfgang & Fan, Ying, 2012. "Energy consumption and CO2 emissions in China's cement industry: A perspective from LMDI decomposition analysis," Energy Policy, Elsevier, vol. 50(C), pages 821-832.
    7. Li, Li & Wang, Jianjun & Tan, Zhongfu & Ge, Xinquan & Zhang, Jian & Yun, Xiaozhe, 2014. "Policies for eliminating low-efficiency production capacities and improving energy efficiency of energy-intensive industries in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 312-326.
    8. Rogan, Fionn & Cahill, Caiman J. & Ó Gallachóir, Brian P., 2012. "Decomposition analysis of gas consumption in the residential sector in Ireland," Energy Policy, Elsevier, vol. 42(C), pages 19-36.
    9. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    10. Cahill, Caiman J. & Ó Gallachóir, Brian P., 2012. "Combining physical and economic output data to analyse energy and CO2 emissions trends in industry," Energy Policy, Elsevier, vol. 49(C), pages 422-429.

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