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An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries

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  • Pardo Martínez, Clara Inés

Abstract

This study determines the trends in energy efficiency and CO2 emissions of the Swedish service sector using data at the 2-digit level of aggregation for the Swedish service industry over the period 1993–2008, this empirical study examines eco-efficiency in terms of energy efficiency and CO2 emissions based on a number of models. The results show that Swedish service industries increased energy consumption and CO2 emissions during the sample period, whereas energy and CO2 emission intensities have shown a decrease in recent years. Eco-efficiency models based on the Malmquist data envelopment analysis model suggest that Swedish service industries have an excellent potential to increase energy efficiency and reduce CO2 emissions. Second-stage panel data techniques show that energy taxes, investments and labour productive have a significant and positive influence on energy and CO2 emission intensities implying that increasing these variables lead to higher energy efficiency and lower CO2 emission intensity. This analysis demonstrates the importance of designing and applying adequate energy policies that encourage better energy use and management in this industrial sector for the goal of achieving a low carbon economy.

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  • Pardo Martínez, Clara Inés, 2013. "An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries," Socio-Economic Planning Sciences, Elsevier, vol. 47(2), pages 120-130.
    • Handle: RePEc:eee:soceps:v:47:y:2013:i:2:p:120-130
    DOI: 10.1016/j.seps.2012.11.004
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    as
    1. 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.
    2. Giorgio Calzolari & Laura Magazzini, 2012. "Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood," Empirical Economics, Springer, vol. 43(1), pages 145-152, August.
    3. 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.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    5. Salas, Osvaldo, 1998. "Technical Efficiency During Deregulation of the Urban Bus System in Sweden," Working Papers in Economics 4, University of Gothenburg, Department of Economics.
    6. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    7. Harald Edquist, 2011. "CAN INVESTMENT IN INTANGIBLES EXPLAIN THE SWEDISH PRODUCTIVITY BOOM IN THE 1990s?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 57(4), pages 658-682, December.
    8. 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.
    9. 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.
    10. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    11. Bretschger, Lucas & Ramer, Roger & Schwark, Florentine, 2011. "Growth effects of carbon policies: Applying a fully dynamic CGE model with heterogeneous capital," Resource and Energy Economics, Elsevier, vol. 33(4), pages 963-980.
    12. Mukherjee, Kankana, 2008. "Energy use efficiency in the Indian manufacturing sector: An interstate analysis," Energy Policy, Elsevier, vol. 36(2), pages 662-672, February.
    13. Greening, Lorna A. & Boyd, Gale & Roop, Joseph M., 2007. "Modeling of industrial energy consumption: An introduction and context," Energy Economics, Elsevier, vol. 29(4), pages 599-608, July.
    14. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    15. Saunders, Harry D., 2008. "Fuel conserving (and using) production functions," Energy Economics, Elsevier, vol. 30(5), pages 2184-2235, September.
    16. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    17. Baltagi, Badi H. & Wu, Ping X., 1999. "Unequally Spaced Panel Data Regressions With Ar(1) Disturbances," Econometric Theory, Cambridge University Press, vol. 15(6), pages 814-823, December.
    18. Sune Karlsson & Jimmy Skoglund, 2004. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Empirical Economics, Springer, vol. 29(1), pages 79-88, January.
    19. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    20. Krackeler, Tom & Schipper, Lee & Sezgen, Osman, 1998. "Carbon dioxide emissions in OECD service sectors: the critical role of electricity use," Energy Policy, Elsevier, vol. 26(15), pages 1137-1152, December.
    21. Henning, Dag & Trygg, Louise, 2008. "Reduction of electricity use in Swedish industry and its impact on national power supply and European CO2 emissions," Energy Policy, Elsevier, vol. 36(7), pages 2330-2350, July.
    22. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    23. Bhattacharyya, Subhes C. & Matsumura, Wataru, 2010. "Changes in the GHG emission intensity in EU-15: Lessons from a decomposition analysis," Energy, Elsevier, vol. 35(8), pages 3315-3322.
    24. Hjalmarsson, Lennart & Veiderpass, Ann, 1992. " Productivity in Swedish Electricity Retail Distribution," Scandinavian Journal of Economics, Wiley Blackwell, vol. 94(0), pages 193-205, Supplemen.
    25. Schleich, Joachim, 2009. "Barriers to energy efficiency: A comparison across the German commercial and services sector," Ecological Economics, Elsevier, vol. 68(7), pages 2150-2159, May.
    26. van der Werf, Edwin, 2008. "Production functions for climate policy modeling: An empirical analysis," Energy Economics, Elsevier, vol. 30(6), pages 2964-2979, November.
    27. Edquist, Harald, 2011. "Intangible Investment and the Swedish Manufacturing and Service Sector Paradox," Working Paper Series 863, Research Institute of Industrial Economics.
    28. Robert Stern, 2005. "The Place of Services in the World Economy," Working Papers 530, Research Seminar in International Economics, University of Michigan.
    29. Johansson, Helena, 2005. "Technical, Allocative, and Economic Efficiency in Swedish Dairy Farms: The Data Envelopment Analysis Versus the Stochastic Frontier Approach," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24478, European Association of Agricultural Economists.
    30. Bohringer, Christoph & Rutherford, Thomas F., 2008. "Combining bottom-up and top-down," Energy Economics, Elsevier, vol. 30(2), pages 574-596, March.
    31. Fuss, Melvyn A, 1977. "The Structure of Technology over Time: A Model for Testing the "Putty-Clay" Hypothesis," Econometrica, Econometric Society, vol. 45(8), pages 1797-1821, November.
    32. Murphy, Rose & Rivers, Nic & Jaccard, Mark, 2007. "Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application to Canada," Energy Economics, Elsevier, vol. 29(4), pages 826-846, July.
    33. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, June.
    34. Henry Thompson, 1985. "Complementarity in a Simple General Equilibrium Production Model," Canadian Journal of Economics, Canadian Economics Association, vol. 18(3), pages 616-621, August.
    35. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    36. Collard, Fabrice & Feve, Patrick & Portier, Franck, 2005. "Electricity consumption and ICT in the French service sector," Energy Economics, Elsevier, vol. 27(3), pages 541-550, May.
    37. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, June.
    38. Schleich, Joachim & Gruber, Edelgard, 2008. "Beyond case studies: Barriers to energy efficiency in commerce and the services sector," Energy Economics, Elsevier, vol. 30(2), pages 449-464, March.
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    More about this item

    Keywords

    Swedish service industries; CO2 emissions; Energy efficiency; Data envelopment analysis; The Malmquist productivity index; Panel data model;
    All these keywords.

    JEL classification:

    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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