References
- Apostolakis, B. 1990. Energy-capital substitutability/complementarity: The dichotomy. Energ. Econ. 12:48–58.
- Banker, R., and Natarajan, R. 2008. Evaluating contextual variables affecting productivity using data envelopment analysis. Oper. Res. 56:48–58.
- Coelli, T. 1996. A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program. CEPA Working Paper 96/8. Available at: www.uq.edu.au/economics.
- Cooper, W., Lawrence, M., and Zhu, J. 2000. A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA. Socio. Econ. Plan. Sci. 34:1–25.
- Council of the European Union (CEU). 2005. Council conclusions on climate change and energy efficiency. EN2695. Brussels, Belgium: Council of the European Union.
- Farrel, M. 1957. The measurement of productive efficiency. J. R. Stat. Soc. A CXX, Part 3: 253–290.
- Halkos, G., and Tzeremes, N. 2005. A DEA Approach to Regional Development. MPRA Paper No. 3992. Available at: http://mpra.ub.uni-muenchen.de/3992/.
- Hoff, A. 2007. Second stage DEA: Comparison of approaches for modelling the DEA score. Euro. J. Oper. Res. 181:425–435.
- Hu, J., and Kao, C. H. 2007. Efficient energy-saving targets for APEC economies. Energ. Policy 35:373–382.
- Hu, J., and Wang, S. 2006. Total-factor energy efficiency of regions in China. Energ. Policy 34:3206–3217.
- International Energy Agency (IEA). 2007. Tracking industrial energy efficiency and CO2 emissions. Paris: IEA.
- Kander, A., and Schön, L. 2007. The energy-capital relation—Sweden 1870–2000. Structural Change and Economic Dynamics 18:291–305.
- Klein, Y., and Robison, D. 1992. Energy efficiency, fuel switching, and environmental emissions. Sout. Econ. J. 58:1088–1094.
- Knox Lovell, C. A. 1993. Production Frontiers and Productive Efficiency. In: The Measurement of Productive Efficiency: Techniques and Applications, Fried, H. O., Schmidt, S. S., and Knox Lovell, C. A. (Eds.). Oxford, UK: Oxford University Press, pp. 3–67.
- Mattera, P., Dubro, A., Gradel, Y., Yompson, R., Gordon, K., and Foshay, E. 2009. Job quality in the new green economy. Washington, DC: Good Job First.
- Mukherjee, K. 2008. Energy use efficiency in the Indian manufacturing sector: An interstate analysis. Energ. Policy 36:662–672.
- Oude, A., and Bezlepkin, I. 2003. The effect of heating technologies on CO2 and energy efficiency of Dutch greenhouse firms. J. Environ. Manage. 68:73–82.
- Pardo, C. I. 2011. Energy efficiency development in German and Colombian non-energy-intensive sectors: A non-parametric analysis. J. Energy Efficiency 4:115–131
- Pardo, C. I. 2013. An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries. Soc.Econ. Plan. Sci. 47:120–130.
- Pye, M., and McKane, A. 2000. Making a stronger case for industrial energy efficiency by quantifying non-energy benefits. Resour. Conser. Recy. 28:171–183.
- Ray, C. 2004. Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research. Cambridge, UK: Cambridge University Press.
- Unit of Mines and Energy Planning/National Association of Industry. 2003. Comparative analysis of international electricity prices. Industrial sector. Bogotá, Colombia: Unit of Mines and Energy Planning. (In Spanish).
- United Nations (UN). 2009. Increasing the competitiveness of small and medium-sized enterprises through the use of environmentally sound technologies. Report E/ESCWA/SDPD/2009/5. Beirut, Lebanon: United Nations Economic and Social Commission for Western Asia.
- United Nations Industrial Development Organization (UNIDO). 2007. Policies for promoting industrial energy efficiency in developing countries and transition economies. Commission for Sustainable Development (CSD-15). New York: UNIDO.
- United States Energy Information Administration (EIA). 2007. Industrial Sector Energy Demand: Revisions for Non-Energy-Intensive Manufacturing. Available at: www.eia.doe.gov.
- Wuppertal Institute. 2009. Evaluate Energy Savings EU, Intelligent Energy Europe. Measuring and reporting energy savings for the Energy Services Directive – How it can be done. Results and recommendations from the EMEEES project. Wuppertal, Germany: EMEEES Consortium.
- Zhou, P., and Ang, B. 2008. Linear programming models for measuring economy-wide energy efficiency performance. Energ. Policy 36:2911–2916.