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Measuring the efficiency of energy-intensive industries across European countries

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  • Makridou, Georgia
  • Andriosopoulos, Kostas
  • Doumpos, Michael
  • Zopounidis, Constantin

Abstract

This study evaluates the energy efficiency trends of five energy-intensive industries in 23 European Union (EU) countries over the period 2000–2009. In particular, the performance of the construction, electricity, manufacturing, mining and quarrying, and transport sectors is examined. The analysis is based on Data Envelopment Analysis (DEA) combined with the Malmquist Productivity Index (MPI), which allows for distinctions between efficiency and technology changes over time. At the second stage of the analysis, cross-classified multilevel modelling is applied to analyse the main drivers behind efficiency performance using a number of sector and country characteristics. Based on DEA results, an overall improvement in efficiency is observed in all sectors over the period. The decomposition of the MPI indicates that technology change is primarily responsible for the improvements achieved in most sectors. The results obtained by the cross-classified model show, among other things, that the high electricity prices, energy taxes, and market share of the largest generator in the electricity market have a negative effect on industrial energy efficiency.

Suggested Citation

  • Makridou, Georgia & Andriosopoulos, Kostas & Doumpos, Michael & Zopounidis, Constantin, 2016. "Measuring the efficiency of energy-intensive industries across European countries," Energy Policy, Elsevier, vol. 88(C), pages 573-583.
    • Handle: RePEc:eee:enepol:v:88:y:2016:i:c:p:573-583
    DOI: 10.1016/j.enpol.2015.06.042
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    1. Christian Growitsch & Tooraj Jamasb & Michael Pollitt, 2009. "Quality of service, efficiency and scale in network industries: an analysis of European electricity distribution," Applied Economics, Taylor & Francis Journals, vol. 41(20), pages 2555-2570.
    2. Mairet, Nicolas & Decellas, Fabrice, 2009. "Determinants of energy demand in the French service sector: A decomposition analysis," Energy Policy, Elsevier, vol. 37(7), pages 2734-2744, July.
    3. Birol, Fatih & Keppler, Jan Horst, 2000. "Prices, technology development and the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 457-469, June.
    4. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    5. Jaraitė, Jūratė & Di Maria, Corrado, 2012. "Efficiency, productivity and environmental policy: A case study of power generation in the EU," Energy Economics, Elsevier, vol. 34(5), pages 1557-1568.
    6. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    7. Bampatsou, Christina & Papadopoulos, Savas & Zervas, Efthimios, 2013. "Technical efficiency of economic systems of EU-15 countries based on energy consumption," Energy Policy, Elsevier, vol. 55(C), pages 426-434.
    8. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA)," Energy Economics, Elsevier, vol. 34(3), pages 634-644.
    9. Oggioni, G. & Riccardi, R. & Toninelli, R., 2011. "Eco-efficiency of the world cement industry: A data envelopment analysis," Energy Policy, Elsevier, vol. 39(5), pages 2842-2854, May.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    12. Mukherjee, Kankana, 2008. "Energy use efficiency in U.S. manufacturing: A nonparametric analysis," Energy Economics, Elsevier, vol. 30(1), pages 76-96, January.
    13. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation," Energy Economics, Elsevier, vol. 33(2), pages 292-303, March.
    14. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    15. Kashani, Hossein A., 2005. "Regulation and efficiency: an empirical analysis of the United Kingdom continental shelf petroleum industry," Energy Policy, Elsevier, vol. 33(7), pages 915-925, May.
    16. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    17. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    18. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    19. Blomberg, Jerry & Henriksson, Eva & Lundmark, Robert, 2012. "Energy efficiency and policy in Swedish pulp and paper mills: A data envelopment analysis approach," Energy Policy, Elsevier, vol. 42(C), pages 569-579.
    20. Oda, Junichiro & Akimoto, Keigo & Tomoda, Toshimasa & Nagashima, Miyuki & Wada, Kenichi & Sano, Fuminori, 2012. "International comparisons of energy efficiency in power, steel, and cement industries," Energy Policy, Elsevier, vol. 44(C), pages 118-129.
    21. Satoshi Honma & Jin-Li Hu, 2011. "Industry-level Total-factor Energy Efficiency in Developed Countries," Discussion Papers 51, Kyushu Sangyo University, Faculty of Economics.
    22. Fisher-Vanden, Karen & Jefferson, Gary H. & Jingkui, Ma & Jianyi, Xu, 2006. "Technology development and energy productivity in China," Energy Economics, Elsevier, vol. 28(5-6), pages 690-705, November.
    23. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    24. Johansson, Bengt, 2006. "Climate policy instruments and industry--effects and potential responses in the Swedish context," Energy Policy, Elsevier, vol. 34(15), pages 2344-2360, October.
    25. Geller, Howard & Harrington, Philip & Rosenfeld, Arthur H. & Tanishima, Satoshi & Unander, Fridtjof, 2006. "Polices for increasing energy efficiency: Thirty years of experience in OECD countries," Energy Policy, Elsevier, vol. 34(5), pages 556-573, March.
    26. repec:dau:papers:123456789/10972 is not listed on IDEAS
    27. Fang, Hong & Wu, Junjie & Zeng, Catherine, 2009. "Comparative study on efficiency performance of listed coal mining companies in China and the US," Energy Policy, Elsevier, vol. 37(12), pages 5140-5148, December.
    28. Christina Bampatsou & George Hadjiconstantinou, 2009. "The use of the DEA method for simultaneous analysis of the interrelationships among economic growth, environmental pollution and energy consumption," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 2(2), pages 65-86, December.
    29. He, Feng & Zhang, Qingzhi & Lei, Jiasu & Fu, Weihui & Xu, Xiaoning, 2013. "Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs," Energy Policy, Elsevier, vol. 54(C), pages 204-213.
    30. Neelis, Maarten & Ramirez-Ramirez, Andrea & Patel, Martin & Farla, Jacco & Boonekamp, Piet & Blok, Kornelis, 2007. "Energy efficiency developments in the Dutch energy-intensive manufacturing industry, 1980-2003," Energy Policy, Elsevier, vol. 35(12), pages 6112-6131, December.
    31. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    32. Farsi, Mehdi & Filippini, Massimo & Kuenzle, Michael, 2007. "Cost efficiency in the Swiss gas distribution sector," Energy Economics, Elsevier, vol. 29(1), pages 64-78, January.
    33. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    34. Hasanbeigi, Ali & Price, Lynn & Lu, Hongyou & Lan, Wang, 2010. "Analysis of energy-efficiency opportunities for the cement industry in Shandong Province, China: A case study of 16 cement plants," Energy, Elsevier, vol. 35(8), pages 3461-3473.
    35. R Ramanathan, 2005. "Estimating energy consumption of transport modes in India using DEA and application to energy and environmental policy," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 732-737, June.
    36. Azadeh, A. & Ghaderi, S.F. & Omrani, H. & Eivazy, H., 2009. "An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units," Energy Policy, Elsevier, vol. 37(7), pages 2605-2618, July.
    37. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    38. Abeelen, Christiaan & Harmsen, Robert & Worrell, Ernst, 2013. "Implementation of energy efficiency projects by Dutch industry," Energy Policy, Elsevier, vol. 63(C), pages 408-418.
    39. Susanna Zaccarin & Giulia Rivellini, 2002. "Multilevel analysis in social research: An application of a cross-classified model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 95-108, February.
    40. Lindmark, Magnus & Bergquist, Ann-Kristin & Andersson, Lars Fredrik, 2011. "Energy transition, carbon dioxide reduction and output growth in the Swedish pulp and paper industry: 1973-2006," Energy Policy, Elsevier, vol. 39(9), pages 5449-5456, September.
    41. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    42. Watanabe, Michio & Tanaka, Katsuya, 2007. "Efficiency analysis of Chinese industry: A directional distance function approach," Energy Policy, Elsevier, vol. 35(12), pages 6323-6331, December.
    43. Managi, Shunsuke & Opaluch, James J. & Jin, Di & Grigalunas, Thomas A., 2006. "Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry," Ecological Economics, Elsevier, vol. 60(1), pages 204-215, November.
    44. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    45. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    46. Alyousef, Yousef & Stevens, Paul, 2011. "The cost of domestic energy prices to Saudi Arabia," Energy Policy, Elsevier, vol. 39(11), pages 6900-6905.
    47. 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.
    48. Kim, Kyunam & Kim, Yeonbae, 2012. "International comparison of industrial CO2 emission trends and the energy efficiency paradox utilizing production-based decomposition," Energy Economics, Elsevier, vol. 34(5), pages 1724-1741.
    49. Chu Wei & Jinlan Ni & Manhong Shen, 2009. "Empirical Analysis of Provincial Energy Efficiency in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 17(5), pages 88-103, September.
    50. Jiuwen Sun & Shanshan Li, 2014. "Total Factor Energy Efficiency of Yangtze River Delta Region in China," ERSA conference papers ersa14p799, European Regional Science Association.
    51. Broeren, M.L.M. & Saygin, D. & Patel, M.K., 2014. "Forecasting global developments in the basic chemical industry for environmental policy analysis," Energy Policy, Elsevier, vol. 64(C), pages 273-287.
    52. Siitonen, Sari & Tuomaala, Mari & Ahtila, Pekka, 2010. "Variables affecting energy efficiency and CO2 emissions in the steel industry," Energy Policy, Elsevier, vol. 38(5), pages 2477-2485, May.
    53. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    54. Hillard G. Huntington, 2010. "Structural Change and U.S. Energy Use: Recent Patterns," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 25-40.
    55. See, Kok Fong & Coelli, Tim, 2013. "Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis," Energy Policy, Elsevier, vol. 62(C), pages 207-214.
    56. Mahmood, Arshad & Marpaung, Charles O.P., 2014. "Carbon pricing and energy efficiency improvement -- why to miss the interaction for developing economies? An illustrative CGE based application to the Pakistan case," Energy Policy, Elsevier, vol. 67(C), pages 87-103.
    57. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    58. Cornillie, Jan & Fankhauser, Samuel, 2004. "The energy intensity of transition countries," Energy Economics, Elsevier, vol. 26(3), pages 283-295, May.
    59. Pérez-Reyes, Raúl & Tovar, Beatriz, 2009. "Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms," Energy Policy, Elsevier, vol. 37(6), pages 2249-2261, June.
    60. Xiaoli, Zhao & Rui, Yang & Qian, Ma, 2014. "China's total factor energy efficiency of provincial industrial sectors," Energy, Elsevier, vol. 65(C), pages 52-61.
    61. Clara Inés Pardo Martínez, 2009. "Energy efficiency developments in the manufacturing industries of Germany and Colombia, 1998-2005," Serie de Documentos en Economía y Violencia 6144, Centro de Investigaciones en Violencia, Instituciones y Desarrollo Económico (VIDE).
    62. Saygin, D. & Worrell, E. & Patel, M.K. & Gielen, D.J., 2011. "Benchmarking the energy use of energy-intensive industries in industrialized and in developing countries," Energy, Elsevier, vol. 36(11), pages 6661-6673.
    63. Piesse, Jenifer & Thirtle, Colin, 2000. "A Stochastic Frontier Approach to Firm Level Efficiency, Technological Change, and Productivity during the Early Transition in Hungary," Journal of Comparative Economics, Elsevier, vol. 28(3), pages 473-501, September.
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