Measuring the efficiency of energy-intensive industries across european countries

Energy Policy

Volumn 88, Issue , 2016, Pages 573-583

  Makridou, Georgia ^a,b   Andriosopoulos, Kostas ^a   Doumpos, Michael ^b   Zopounidis, Constantin ^b,c  

^a ESCP EUROPE BUSINESS SCHOOL   (United Kingdom)

^b TECHNICAL UNIVERSITY OF CRETE   (Greece)

^c AUDENCIA BUSINESS SCHOOL   (France)

Author keywords

Cross classified modelling; Data envelopment analysis; Energy efficiency; Energy intensive industries; malmquist; Productivity index

Indexed keywords

COMMERCE; COMPETITION; CONSUMER PRODUCTS; DATA ENVELOPMENT ANALYSIS; PRODUCTIVITY; TAXATION;

ELECTRICITY MARKET; ELECTRICITY PRICES; ENERGY INTENSIVE INDUSTRIES; EUROPEAN COUNTRIES; EUROPEAN UNION COUNTRIES; INDUSTRIAL ENERGY EFFICIENCY; MALMQUIST PRODUCTIVITY INDEX; MINING AND QUARRYING;

ENERGY EFFICIENCY;

DATA ENVELOPMENT ANALYSIS; EFFICIENCY MEASUREMENT; ENERGY EFFICIENCY; EUROPEAN UNION; INDUSTRIAL PRODUCTION; MODELING; PRODUCTIVITY;

EUROPE;

EID: 84949728819     PISSN: 03014215     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enpol.2015.06.042     Document Type: Article

References (76)

1. Abeelen, C., Harmsen, R., Worrell, E., 2013. Implementation of energy efficiency projects by Dutch industry. Energy Policy 63, 408-418.
2. Alyousef, Y., Stevens, P., 2011. The cost of domestic energy prices to Saudi Arabia. Energy Policy 39, 6900-6905.
3. Azadeh, A., Amalnick, M.S., Ghaderi, S.F., Asadzadeh, S.M., 2007. An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and con-sumption optimization in energy intensive manufacturing sectors. Energy Policy 35, 3792-3806.
4. Azadeh, A., Ghaderi, S.F., Omrani, H., Eivazy, H., 2009. An integrated DEA-COLS-SFA algorithm for optimization and policymaking of electricity distribution units. Energy Policy 37, 2605-2618.
5. Bampatsou, C., Hadjiconstantinou, G., 2009. The use of the DEA method for si-multaneous analysis of the interrelationships among economic growth, en-vironmental pollution and energy consumption. Int. J. Econ. Sci. Appl. Res. 2, 65-86.
6. Bampatsou, C., Papadopoulos, S., Zervas, E., 2013. Technical efficiency of economic systems of EU-15 countries based on energy consumption. Energy Policy 55, 426-434.
7. Banker, R.D., Charnes, A., Cooper, W.W., 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag. Sci. 30, 1078-1092.
8. Birol, F., Keppler, J.H., 2000. Prices, technology development and the rebound effect. Energy Policy 28, 457-469.
9. Blomberg, J., Henriksson, E., Lundmark, R., 2012. Energy efficiency and policy in Swedish pulp and paper mills: a data envelopment analysis approach. Energy Policy 42, 569-579.
10. Boyd, G., Dutrow, E., Tunnessen, W., 2008. The evolution of the ENERGY STARs energy performance indicator for benchmarking industrial plant manufactur-ing energy use. J. Clean. Prod. 16, 709-715.
11. Broeren, M.L.M., Saygin, D., Patel, M.K., 2014. Forecasting global developments in the basic chemical industry for environmental policy analysis. Energy Policy 64, 273-287.
12. Cahill, C.J., Gallachoir, B.P., 2012. Combining physical and economic output data to analyse energy and CO2 emissions trends in industry. Energy Policy 49, 422-429.
13. Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429-444.
14. Cornillie, J., Fankhauser, S., 2004. The energy intensity of transition countries. En-ergy Econ. 26, 283-295.
15. Davidsdottir, B., Ruth, M., 2004. Capital vintage and climate change policies: The case of US pulp and paper. Environ. Sci. Policy 7, 221-233.
16. Fang, H., Wu, J., Zeng, C., 2009. Comparative study on efficiency performance of listed coal mining companies in China and the US. Energy Policy 37, 5140-5148.
17. Färe, R., Grosskopf, S., Lindgren, B., Roos, P., 1992. Productivity changes in swedish pharamacies 1980-1989: Anon-parametric malmquist approach. J. Product. Anal. 3 (1-2), 85-101.
18. Färe, R., Grosskopf, S., Norris, M., Zhang, Z., 1994. Productivity growth, technical progress, and efficiency change in industrialized countries. Am. Econ. Rev. 84 (1), 66-83.
19. Farsi, M., Filippini, M., Kuenzle, M., 2007. Cost efficiency in the Swiss gas dis-tribution sector. Energy Econ. 29, 64-78.
20. Fisher-Vanden, K., Jefferson, G.H., Jingkui, M., Jianyi, X., 2006. Technology devel-opment and energy productivity in China. Energy Economics 28, 690-705.
21. Geller, H., Harrington, P., Rosenfeld, A.H., Tanishima, S., Unander, F., 2006. Polices for increasing energy efficiency: Thirty years of experience in OECD countries. Energy Policy 34, 556-573.
22. Growitsch, C., Jamasb, T., Pollitt, M., 2009. Quality of service, efficiency and scale in network industries: An analysis of European electricity distribution. Applied Economics 41 (20), 2555-2570.
23. Hasanbeigi, A., Price, L., Lu, H., Lan, W., 2010. Analysis of energy-efficiency oppor-tunities for the cement industry in Shandong Province, China: A case study of 16 cement plants. Energy 35 (8), 3461-3473.
24. He, F., Zhang, Q., Lei, J., Fu, W., Xu, X., 2013. Energy efficiency and productivity change of China's iron and steel industry: Accounting for undesirable outputs. Energy Policy 54, 204-213.
25. Honma, S., Hu, J.L., 2011. Industry-level total-factor energy efficiency in developed countries. Energy Policy 36 (2), 821-833.
26. Honma, S., Hu, J.L., 2014. A panel data parametric frontier technique for measuring total factor energy efficiency: An application to Japanese regions. Energy 78, 732-739.
27. Huang, T., Onishi, A., Shi, F., Morisugi, M., Cherry, M.L., 2015. Regional characteristics of industrial energy efficiency in China: Application of stochastic frontier ana-lysis method. Front. Environ. Sci. Eng. 9, 506-521.
28. Huntington, H.G., 2010. Structural change and U.S. energy use: Recent patterns. Energy J. 31, 25-39.
29. IEA, 2010. Transport Energy Efficiency. International Energy Agency, Paris.
30. IEO, 2014. World petroleum and other liquid fuels. International Energy Outlook. U.S. Energy Information Administration.
31. Jaraite, J., Maria, C.D., 2012. Efficiency, productivity and environmental policy: A case study of power generation in the EU. Energy Econ. 34, 1557-1568.
32. Johansson, B., 2006. Climate policy instruments and industry-effects and potential responses in the Swedish context. Energy Policy 34, 2344-2360.
33. Kashani, H.A., 2005. Regulation and efficiency: An empirical analysis of the United Kingdom continental shelf petroleum industry. Energy Policy 33, 915-925.
34. Kim, K., Kim, Y., 2012. International comparison of industrial CO2 emission trends and the energy efficiency paradox utilizing production-based decomposition. Energy Econ. 34, 1724-1741.
35. Lindmark, M., Bergquist, A.K., Andersson, L.F., 2011. Energy transition, carbon di-oxide reduction and output growth in theSwedish pulp and paper industry: 1973-2006. Energy Policy 39, 5449-5456.
36. Mahmood, A., Marpaung, C.O.P., 2014. Carbon pricing and energy efficiency im-provement-why to miss the interaction for developing economies? An illus-trative CGE based application to the Pakistan case. Energy Policy 67, 87-103.
37. Mairet, N., Decellas, F., 2009. Determinants of energy demand in the French service sector: A decomposition analysis. Energy Policy 37, 2733-2744.
38. Malmquist, S., 1953. Index number and indifferences surfaces. Trab. Estad. 4, 209-2042.
39. Managi, S., Jin, D., Grigalunas, T.A., 2006. Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry. Ecol. Econ. 60, 204-215.
40. Mandal, S.K., Madheswaran, S., 2011. Energy use efficiency of Indian cement companies: A data envelopment analysis. Energy Effic. 4, 57-73.
41. Metcalf, G.E., 2008. An empirical analysis of energy intensity and its determinants at the state level. Energy J. 29 (3), 1-25.
42. Mukherjee, K., 2008. Energy use efficiency in U.S. manufacturing: A nonparametric analysis. Energy Econ. 30, 76-96.
43. Neelis, M., Ramirez-Ramirez, A., Patel, M., Farla, J., Boonekamp, P., Blok, K., 2007. Energy efficiency developments in theDutch energy-intensive manufacturing industry, 1980-2003. Energy Policy 35, 6112-6131.
44. Oda, J., Akimoto, K., Tomoda, T., Nagashima, M., Wada, K., Sano, F., 2012. Interna-tional comparisons of energy efficiency in power, steel and cement industries. Energy Policy 44, 118-129.
45. Oggioni, G., Riccardi, R., Toninelli, R., 2011. Eco-efficiency of the world cement in-dustry: A data envelopment analysis. Energy Policy 39, 2842-2854.
46. Pardo Martinez, C., 2009. Energy efficiency developments in the manufacturing industries of Germany and Colombia, 1998-2005. Energy Sustain. Dev. 13, 189-201.
47. Pardo Martinez, C., 2011. Energy efficiency development in German and Colombian non-energy-intensive sectors: A non-parametric analysis. Energy Effic. 4, 115-131.
48. Perez-Reyes, R., Tovar, B., 2009. Measuring efficiency and productivity change (PTF) in the peruvian electricity distribution companies after reforms. Energy policy 37, 2249-2261.
49. Piesse, J., Thirtle, C., 2000. A stochastic frontier approach to firm level efficiency, technological change, and productivity during the early transition in Hungary. J. Comp. Econ. 28, 473-501.
50. Ramanathan, R., 2005. Estimating energy consumption of transport modes in India using DEA and application to energy and environmental policy. J. Oper. Res. Soc. 56 (6), 732-737.
51. Ramli, N.A., Munisamy, S., 2013. Modeling undesirable factors in efficiency mea-surement using data envelopment analysis: A review. J. Sustain. Sci. Manag. 8 (1), 126-135.
52. Riccardi, R., Oggioni, G., Toninelli, R., 2012. Efficiency analysis of world cement in-dustry in presence of undesirable output: Application of data envelopment analysis and directional distance function. Energy Policy 44, 140-152.
53. 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. En-ergy 36, 6661-6673.
54. See, K.F., Coelli, T., 2013. Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis. En-ergy Policy 62, 207-214.
55. Siitonen, S., Tuomaala, M., Ahtila, P., 2010. Variables affecting energy efficiency and CO2 emissions in the steel industry. Energy Policy 38, 2477-2485.
56. Simar, L., Wilson, P.W., 1998. Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Manag. Sci. 44 (1), 49-61.
57. Shi, G.M., Bi, J., Wang, J.N., 2010. Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs. Energy Policy 38, 6172-6179.
58. Stern, D.I., 2012. Modeling international trends in energy efficiency. Energy Econ. 34, 2200-2208.
59. Subrahmanya, M.H.B., 2006. Labour productivity, energy intensity and economic performance in small enterprises: A study of brick enterprises cluster in India. Energy Convers. Manag. 47, 763-777.
60. Sueyoshi, T., Goto, M., 2011. DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation. Energy Econ. 33, 292-303.
61. Sueyoshi, T., Goto, M., 2012. Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA Dis-criminant Analysis (DA). Energy Econ. 34 (3), 634-644.
62. Timmer, M.P., Dietzenbacher, E., Los, B., Stehrer, R., De Vries, G.J., 2015. An illu-strated user guide to the world input-output database: The case of global au-tomotive production. Rev. Int. Econ. http://dx.doi.org/10.1111/roie.12178.
63. Walton, A.L., 1981. Variations in the substitutability of energy and non energy in-puts: The case of the middle Atlantic region. J. Reg. Sci. 21, 411-420.
64. Wang, Z.H., Zeng, H.L., Wei, Y.M., Zhang, Y.X., 2012. Regional total factor energy efficiency: An empirical analysis of industrial sector in China. Appl. Energy 97, 115-123.
65. Watanabe, M., Tanaka, K., 2007. Efficiency analysis of Chinese industry: A direc-tional distance function approach. Energy Policy 35, 6323-6331.
66. Wei, Y.M., Liao, H., Fan, Y., 2007. An empirical analysis of energy efficiency in Chi-na's iron and steel sector. Energy 32, 2262-2270.
67. Wei, C., Ni, J., Shen, M., 2009. Empirical analysis of provincial energy efficiency in china. China World Econ. 17, 88-103.
68. Wu, F., Fan, L.W., Zhou, P., Zhou, D.Q., 2012. Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis. Energy Policy 49, 164-172.
69. Wu, Y., 2012. Energy intensity and its determinants in China's regional economies. Energy Policy 41, 703-711.
70. Xiaoli, Z., Rui, Y., Qian, M., 2014. China's total factor energy efficiency of provincial industrial sectors. Energy 65, 52-61.
71. Xue, X., Shen, Q., Wang, Y., Lu, J., 2008. Measuring the productivity of the con-struction industry in china by using DEA-based malmquist productivity in-dices. J. Constr. Eng. Manag. 134 (1), 64-71.
72. Zaccarin, S., Rivellini, G., 2002. Multilevel analysis in social research: An application of a cross-classified model. Stat. Methods Appl. 11 (1), 95-108.
73. Zhou, P., Ang, P.W., 2008. Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy 36, 2911-2916.
74. Zhou, P., Ang, P.W., Han, J.Y., 2010. Total factor carbon emission performance: A Malmquist index analysis. Energy Econ. 32, 194-201.
75. Zhou, P., Ang, P.W., Zhou, D.Q., 2012. Measuring economy-wide energy efficiency performance: A parametric frontier approach. Appl. Energy 90, 196-200.
76. Zhou, G., Chung, W., Zhang, Y., 2014. Measuring energy efficiency performance of China's transport sector: A data envelopment analysis approach. Expert Syst. Appl. 41 (2), 709-722.