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

Socio-Economic Planning Sciences

Volumn 47, Issue 2, 2013, Pages 120-130

  Pardo Martínez, Clara Inés ^a,b,c  

^a UNIVERSIDAD DEL ROSARIO   (Colombia)

^b UNIVERSIDAD DE LA SALLE   (Colombia)

^c ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

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

Indexed keywords

CARBON DIOXIDE; CARBON EMISSION; DATA ENVELOPMENT ANALYSIS; EMISSION CONTROL; ENERGY EFFICIENCY; ENERGY USE; MODELING; PANEL DATA; PRODUCTIVITY; SERVICE SECTOR;

SWEDEN;

EID: 84878135915     PISSN: 00380121     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.seps.2012.11.004     Document Type: Article

References (87)

1. Ang B.W., Zhang F.Q. Survey of index decomposition analysis in energy and environmental studies. Energy 2000, 25:1149-1176.
2. Baltagi B., Li Q. A Lagrange multiplier test for the error components model with incomplete panels. Econometric Reviews 1990, 9:103-107.
3. Baltagi H., Wu P. Unequally spaced panel data regressions with AR(1) disturbances. Econometric Theory 1999, 15:814-823.
4. Banker R., Natarajan R. Statistical tests based on dea efficiency scores. Handbook on data envelopment analysis 2004, 265-298. Kluwer Academic Publishers, Inc., New York, [Chapter 11]. W. Cooper, L. Seiford, J. Zhu (Eds.).
5. Bhattacharyya S., Matsumura W. Changes in the GHG emission intensity in EU-15: lessons from a decomposition analysis. Energy 2010, 35:3315-3322.
6. Böhringer C., Rutherford T. Combining bottom-up and top-down. Energy Economics 2008, 30:574-596.
7. Bretschger L., Ramer R., Schwark F. Growth effects of carbon policies: applying a fully dynamic CGE model with heterogeneous capital. Resource and Energy Economics 2011, 33:963-980.
8. Breusch T., Pagan R. The Lagrange multiplier test and its applications to model specification in econometrics. Review of Economic Studies 1980, 47:239-253.
9. Calzolari G., Magazzini L. Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood. Empirical Economics 2011, 10.1007/s00181-011-0487-7.
10. Caves D.W., Christensen L.R., Diewert W.E. The econometric theory of index numbers and the measurement of input, output, productivity. Econometrica 1982, 50:1393-1414.
11. Central Intelligence Agency (CIA) The world factbook 2011, https://www.cia.gov/library/publications/the-world-factbook/index.html.
12. Coelli T., Prasada D., O'Donnell C., Battese G. An introduction to efficiency and productivity analysis 2005, Springer, New York. 2nd ed.
13. Coelli T. A guide to DEAP version 2.1: a data envelopment analysis (computer) program, CEPA working paper 96/8 1996, Department of Econometrics, University of New England, NSW Australia. http://www.uq.edu.au/economics/cepa/deap.
14. Coelli T., Prasada Rao D.S., Battese G.E. An introduction to efficiency and productivity analysis 1998, Kluwer, Boston.
15. Collard F., Feve P., Portier F. Electricity consumption and ICT in the French service sector. Energy Economics 2005, 27:541-550.
16. Cooper W., Seiford L., Tone K. Data envelopment analysis. A comprehensive text with models, applications, references and DEA-Solver software 2007, Springer. 2nd ed.
17. Driscoll J., Kraay A. Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics 1998, 80:549-560.
18. Drucker P. Managing in the next society 2002, St. Martin Press, New York.
19. Ecofys Economic evaluation of sectoral emission reduction objectives for climate change. Top-down analysis of greenhouse gas emission reduction possibilities in the EU 2001, Ecofys Energy and Environment, AEA Technology Environment and National Technical University of Athens. http://ec.europa.eu/environment/enveco/climate_change/pdf/top_down_analysis.pdf.
20. Edquist H. Intangible investment and the Swedish manufacturing and service sector paradox - what can Europe learn? 2011, IFN Working Paper No. 863 Research Institute of Industrial Economics. http://snee.org/filer/papers/627.pdf.
21. Edquist H. Can investment in intangibles explain the Swedish productivity boom in the 1990s? Review of income and wealth 2011, 10.1111/j.1475-4991.2010.00436.x.
22. European Commission (EC) 2030 European energy and transport. Trends to 2030-update 2007 2008, Directorate-General for Energy and Transport. http://ec.europa.eu/dgs/energy_transport/figures/trends_2030_update_2007/energy_transport_trends_2030_update_2007_en.pdf.
23. European Commission (EC) Action plan for energy efficiency: realising the potential 2006, Brussels, Belgium. http://ec.europa.eu/energy/action_plan_energy_efficiency/doc/com_2006_0545_en.pdf.
24. Realizing the Potential of energy efficiency: targets, policies, and measures for G8 countries 2007, Expert Group on Energy Efficiency, United Nations Foundation, Washington, DC, 72 pp.
25. Fare R., Grosskopf S., Lovell C.A.K. Production frontier 1994, Cambridge University Press, UK.
26. Färe R., Grosskopf S., Lindgren B., Roos P. Productivity developments in Swedish hospitals: a Malmquist output index approach. Data envelopment analysis: theory, methodology and application 1995, 253-272. Kluwer, Boston, MA. A. Charnes (Ed.).
27. Färe R., Grosskopf S., Forsund F., Hayes K., Heshmati A. Measurement of productivity and quality in non-marketable services. With application to schools. Quality Assurance in Education 2006, 14:21-36.
28. Farrel M. The measurement of productive efficiency. Journal of the Royal Statistical Society, A 1957, CXX(Part 3):253-290.
29. French Environment and Energy Management Agency (ADEME) Energy-efficiency monitoring in the EU-15 2005, http://www.2.ademe.fr/servlet/getDoc%3fsort%3d-1%26cid%3d96%26m%3d3%26id%3d2830%206%26ref%3d14152%26nocache%3dyes%26p1%3d111.
30. Fuss M. The structure of technology over time: a model for testing the 'Putty-Clay' hypothesis. Econometrica 1977, 45:1797-1821.
31. Greene W. Econometric analysis 2011, Pearson Education. Global ed. of 7th revised ed.
32. Greening L., Boyd G., Roop J. Modeling of industrial energy consumption: an introduction and context. Energy Economics 2007, 29:599-608.
33. Hjalmarsson L., Veiderpass A. Productivity in Swedish electricity retail distribution. The Scandinavian Journal of Economics 1992, 94:193-205.
34. Harrison G., Kriström B. Carbon taxes in Sweden. Final report 1997, http://www-sekon.slu.se/%7Ebkr/Carbon.pdf.
35. Hausman J. Specification tests in econometrics. Econometrica 1978, 46:1251-1271.
36. 2 emissions. Energy Policy 2008, 36:2330-2350.
37. Hoechle D. Robust standard errors for panel regressions with cross-sectional dependence. The Stata Journal 2007, 7:281-312.
38. Hoff A. Second stage DEA: comparison of approaches for modelling the DEA score. European Journal of Operational Research 2007, 181:425-435.
39. 2 emissions 2007, http://www.iea.org/textbase/nppdf/free/2007/tracking_emissions.pdf.
40. International Energy Agency (IEA) Worldwide trends in energy use and efficiency. Key insights from IEA indicator analysis 2008, In support of the G8 plan of action. http://www.iea.org/papers/2008/indicators_2008.pdf.
41. International Energy Agency (IEA) Technology roadmap energy-efficient buildings: heating and cooling equipment 2011, http://www.iea.org/papers/2011/buildings_roadmap.pdf.
42. International Energy Agency (IEA) IEA scoreboard 2009: 35 key energy trends over 35 years 2009, http://www.iea.org/publications/free_new_Desc.asp%3fPUBS_ID%3d2141.
43. International Energy Agency (IEA) Energy efficiency requirements in building codes, energy efficiency policies for new buildings 2008, http://www.iea.org/g8/2008/Building_Codes.pdf.
44. Johansson B. Economic instruments in practice 1: carbon tax in Sweden. Report Swedish Environmental Protection Agency 2001, http://www.oecd.org/dataoecd/25/0/2108273.pdf.
45. Johansson H. Technical, allocative, and economic efficiency in Swedish dairy farms: the data envelopment analysis versus the stochastic frontier approach 2005, European Association of Agricultural Economists, International Congress, Copenhagen, Denmark. http://ageconsearch.umn.edu/handle/24478.
46. Karlsson S., Skoglund J. Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects. Empirical Economics 2004, 29:79-88.
47. Karmarkar U. Will you survive the services revolution?. Harvard Business Review 2004, 82:101-107.
48. Krackeler T., Schipper L., Sezgen O. Carbon dioxide emissions in OECD service sectors: the critical role of electricity use. Energy Policy 1998, 26:1137-1152.
49. Lapillonne B., Sebi C., Pollier K. Energy efficiency trends in EU services http://www.odyssee-indicators.org/reports/services/services_eu27.pdf.
50. Lowell J., Pastor T. Units invariant and translation invariant DEA models. Operations Research Letters 1995, 18:147-151.
51. Lv W, Hong X, Fang K. Chinese regional energy efficiency change and its determinants analysis: Malmquist index and Tobit model. Annals of Operation Research, . doi:10.1007/s10479-012-1094-5.
52. Mairet N., Decellas F. Determinants of energy demand in the French service sector: a decomposition analysis. Energy Policy 2009, 37:2734-2744.
53. Malmquist S. Malmquist, index numbers and indifference surfaces. Trabajos de Estadistica 1953, 4:209-242.
54. McDonald J. Using least squares and Tobit in second stage DEA efficiency analyses. European Journal of Operational Research 2008, 197:792-798.
55. Mukherjee K. Energy use efficiency in the Indian manufacturing sector: an interstate analysis. Energy Policy 2008, 36:662-672.
56. Mulder P., Groot H. International comparisons of sectoral energy- and labour-productivity performance 2004, Tinbergen Institute Discussion Paper. TI 2004-007/3.
57. Murphy R., Rivers N., Jaccard M. Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application to Canada. Energy Economics 2007, 29:826-846.
58. Nair A., Sarkar A., Ramanathan A., Subramanyam A. Anomalies in CAPM: a panel data analysis under Indian conditions. International Research Journal of Finance and Economics 2009, 33:192-206.
59. Oggioni G., Riccardi R., Toninelli R. Eco-efficiency of the world cement industry: a data envelopment analysis. Energy Policy 2011, 39:2842-2854.
60. Organisation for Economic Co-operation and Development (OECD) Environmentally related taxes in OECD countries. Issues and strategies 2001, http://www.peblds.org/files/Publications/OECD/OECD_Environmentally_Related_Taxes.pdf.
61. Pardo M.C.I. Energy efficiency development in the German and Colombian energy intensive sectors: a non-parametric analysis. WIT Transactions on Ecology and the Environment 2009, 121:499-511.
62. Pardo M.C.I. Energy efficiency development in German and Colombian non-energy-intensive sectors: a non-parametric analysis. Energy Efficiency 2011, 4:115-131.
63. Phylipsen G., Blok K., Worrell E. Handbook on international comparisons of energy efficiency in the manufacturing industry 1998, Department of Science, Technology and Society, Utrecht University.
64. Ramanathan R. A multi-factor efficiency perspective to the relationships among world GDP, energy consumption and carbon dioxide emissions. Technological Forecasting & Social Change 2006, 73:483-494.
65. Salas O. Technical efficiency during deregulation of the urban bus system in Sweden. Working papers in economics No 4 1998, School of Economics and Commercial Law Göteborg University.
66. Saunders H. Fuel conserving (and using) production functions. Energy Economics 2008, 30:2184-2235.
67. Schleich J. Barriers to energy efficiency: a comparison across the German commercial and services sector. Ecological Economics 2009, 68:2150-2159.
68. Schleich J., Gruber E. Beyond case studies: barriers to energy efficiency in commerce and the services sector. Energy Economics 2008, 30:449-464.
69. 2 emissions in Latin American and the Caribbean. CEPAL, statistic and prospective studies 2007, [In Spanish].
70. 2: energy consumption in the service sector 2000, The Association for the Conservation of Energy, London. http://www.ukace.org/.
71. Speck S. The design of carbon and broad-based energy taxes in European countries. In the reality of carbon taxes. In the 21st Century. A Joint Project of the Environmental Tax Policy Institute and the Vermont Journal of Environmental Law Vermont Law School; 2008.
72. Statistics Sweden National accounts, detailed yearly estimates, 1950-2008 2010, http://www.scb.se.
73. Stern R. The place of services in the world economy 2005, Research Seminar in International Economics. Discussion Paper No. 530. http://www.spp.umich.edu/rsie/workingpapers/wp.html.
74. Suh S. Are services better for climate change?. Environmental Science & Technology 2006, 40:6555-6560.
75. Sweden Energy The electricity year 2010 http://www.svenskenergi.se/upload/Statistik/El%e5ret/ENG_Sv%20Energi_el%e5ret2010.pdf.
76. Swedish Institute Energy: generating power for a sustainable future 2011, http://www.sweden.se/upload/Sweden_se/english/factsheets/SI/SI_FS3_Energy/FS3-Energy-low-resolution.pdf.
77. The Swedish Ministry of Industry, Employment and Communications Innovative Sweden. A strategy for growth through renewal 2004, Ds 2004:36. http://www.sweden.gov.se/content/1/c6/03/25/51/29e722a9.pdf.
78. Thompson Henry Complementarity in a simple general equilibrium production model. Canadian Journal of Economics 1985, 17:616-621.
79. UK Energy Research Centre (UKERC) UKERC review of evidence for the rebound effect technical report 3: elasticity of substitution studies 2007, Working Paper REF: UKERC/WP/TPA/2007/011.
80. Unander F. Decomposition of manufacturing energy-use in IEA countries. How do recent developments compare with historical long-term trends?. Applied Energy 2007, 84:771-780.
81. U.S.Department of Energy Energy efficiency and renewable energy. Planning, budget, and analysis - energy intensity indicators. Efficiency vs. intensity 2008, http://www1.eere.energy.gov/ba/pba/intensityindicators/printable_versions/efficiency_intensity.html.
82. WEC Energy efficiency: a worldwide review 2004, World Energy Council, London.
83. Werf E. Production functions for climate policy modelling: an empirical analysis. Energy Economics 2008, 30:2964-2979.
84. Wing I., Eckaus R. Explaining long-run changes in the energy intensity of the U.S. economy. Report No. 116. The MIT Joint Program on the Science and Policy of Global Change 2004.
85. Wooldridge J. Econometric analysis of cross section and panel data 2010, MIT Press, Cambridge, MA.
86. Zhou P., Ang W. Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy 2008, 36:2911-2916.
87. Zhou P., Ang W., Han J. Total factor carbon emission performance: a Malmquist index analysis. Energy Economics 2010, 32:194-201.