Environmental Efficiency of Electric Power Industry of the United States: A Data Envelopment Analysis Approach

Importance of environmental efficiency of electric power industry stems from high demand for energy combined with global warming concerns. It is especially essential for the world largest economies like that of the United States. The paper introduces a Data Envelopment Analysis (DEA) model of environmental efficiency using indicators of fossil fuels utilization, emissions rate, and electric power losses. Using DEA is advantageous in this situation over other approaches due to its nonparametric nature. The paper analyzes data for the period of 1990 - 2006 by comparing actual yearly levels in each dimension with the best values of partial indicators for the period. As positive factors of efficiency, tendency to the decline in emissions rates starting 2000, and in electric power losses starting 2004 may be mentioned together with increasing trend of fuel utilization starting 1999. As a result, dynamics of environmental efficiency is positive starting 2002. The main concern is the decline in fossil fuels utilization in 2006. This negative change should be reversed to comply with ecological and economic requirements.

• Alexander Y. Vaninsky

• Environmental efficiency
• electric power industry
• DEA
• United States.

[1] Agrell, P, Bogetoft, P. Economic and environmental efficiency of district
heating plants. Energy Policy 2005; 33(10):1351 - 1362.
[2] Ajodhia, V., Petrov, K. Scarci, G.C. Integrated cost and quality
benchmarking in electricity distribution. 2001. Available at
http://www.informs.org/Conf/Hawaii2001/TALKS/Sessions.html
[3] Amirteimoori, A., Jahanshahloo, G., Kordrostami, S. Ranking of
decision making units in data envelopment analysis: A distance-based
approach. Applied Mathematics and Computation 2005; 171 (1): 122-
135.
[4] Arocena, P. Cost and quality gains from diversification and vertical
integration in the electricity industry: A DEA approach. Economics
2008; 30(1): 39-58.
[5] Bagdadioglu, N. Privatization, Ownership, and Technical Efficiency in
the Turkish Electricity Supply Industry. Pacific and Asian Journal of
Energy 1996; 6(1): 25-37.
[6] Bagdadioglu, N., Price, C. M. W., Weyman-Jones, T.G. Efficiency and
ownership in electricity distribution: A non-parametric model of the
Turkish experience. Energy Economics 1996; 18:1-23.
[7] Banker, R. Estimating most productive scale size using data
envelopment analysis. European Journal of Operational Research 1984;
17(1): 35-44.
[8] Banker R.D., Charnes, Cooper, A. Some models for estimating technical
and scale efficiency in Data Envelopment Analysis. Management
Science 1984; 30(9): 1078-1092.
[9] Blose, J., Tankersley, W. Linking dimensions of service quality to
organizational outcomes. Managing Service Quality 2004; 14(1): 75-89.
[10] Charnes A., Cooper W.W., Rhodes, E. Evaluating program and
managerial efficiency: An application of Data Envelopment Analysis to
program follow through. Management Science 1978; 27: 668 - 697.
[11] Chen, T. An assessment of technical efficiency and cross-efficiency in,
Taiwan's electricity distribution sector. European Journal of Operational
Research 2002; 137(2): 421-433.
[12] Chen, Y. Ranking efficient units in DEA. Omega 2004; 32 (3): 213-219.
[13] Cooper, W.W., Seiford, L.M. and K.Tone, Data Envelopment Analysis:
A Comprehensive Text with Models, Applications, References. New
York: Springer, 2005.
[14] Cote, D. Firm efficiency and ownership structure - The case of U.S.
electric utilities using panel data. Annals of Public and Cooperative
Economics 1989; 60(4): 431-450.
[15] Delmas, M.,Tokat, Y. Deregulation, Governance Structures, And
Efficiency: The U.S. Electric Utility Sector. Management Journal 2005;
26 (5): 441-460.
[16] Domah, P. Technical efficiency in electricity generation - the impact of
smallness and isolation of island economies. Department of Applied
Economics, University of Cambridge, Cambridge Working Papers in
Economics. 2002.
[17] Electric Power Annual 2006. Energy Information Administration 2007.
Available at http://www.eia.doe.gov/cneaf/electricity/epa/epa_sum.html
[18] Farrell M.J. The Measurement of Production Efficiency. Journal of the
Royal Statistical Society, Series A 1957; 120(3): 253 - 282.
[19] Fuh-Hwa F., Hao H. Ranking of units on the DEA frontier with common
weights. Computers & Operations Research 2008; 35(5):1624 - 1637.
[20] Golany, B., Roll, Y. Measuring efficiency of power plants in Israel by
data envelopment analysis. IEEE Transactions on Engineering
Management 1994; 41(3): 291-301.
[21] Hjalmarsson, L., A. Veiderpass. Efficiency and ownership in Swedish
electricity retail distribution. Journal of Productivity Analysis 1992; 3: 7-
23.
[22] Honma, S., Hu, J-L. Total-factor energy efficiency of regions in Japan.
Energy Policy 2008; 36:821-833.
[23] Jahanshahloo, G., Lotfi, F., Rezai, H., Balf, F. Using Monte Carlo
method for ranking efficient DMUs. Applied Mathematics and
Computation 2005; 162 (1): 371-379.
[24] Key World Energy Statistics. International Energy Agency, 2007.
Available at http://iea.data.org.
[25] Khodabakhshi, M. A super-efficiency model based on improved outputs
in data envelopment analysis. Applied Mathematics and Computation
2007;184 (2): 695-703.
[26] Korhonen, P., Syrjanen, M. Evaluation of cost efficiency in Finnish
electricity distribution. Annals of Operations Research 2003; 121 (1-4);
105 - 122.
[27] Lam, P., Shiu, A. Efficiency and Productivity of China's Thermal Power
Generation. Review of Industrial Organization 2004; 24(1): 73-93.
[28] Li, S., Jahanshahloo, G.R., Khodabakhshi, M. A super-efficiency model
for ranking efficient units in data envelopment analysis. Applied
Mathematics and Computation 2007; 184 (2): 638-648.
[29] Li, Y. , Wang, D. Technology efficiency study on nuclear power and
coal power in Guangdong province based on DEA. Proceedings of the
International Conference on Nuclear Engineering, Proceedings,
(ICONE) 2006; (2006).
[30] Liu, Y., Gu, X. Hierarchical data envelopment analysis for assessing
black-start plans. Dianli Xitong Zidonghua/Automation of Electric
Power Systems 2006; 30 (21): 33-38.
[31] Majumdar, S., Marcus, A. Do Environmental Regulations Retard
Productivity? Evidence from U.S. Electric Utilities. University of
Michigan Business School, Working Papers, 1998:1-43.
[32] Meimodi, A.E. Efficiency considerations in the electricity supply
industry: The case of Iran. 1998. Available at
http://www.econ.surrey.ac.uk/WorkingPapers/seed95.pdf.
[33] Miliotis, P A. Data envelopment analysis applied to electricity
distribution districts. Journal of the Operational Research Society 1992;
43: 549-55.
[34] Nakicenovic, N., Wien, TU. World Energy Outlook 2007: CO2
Emissions Pathways Compared to Long-Term CO2 Stabilization
Scenarios in the Literature and IPCC AR4. 2007. Available at
http://www.worldenergyoutlook.org/docs/weo2007/CO2_Scenarios.pdf.
[35] Nemoto, J., Goto, M. Measurement of dynamic efficiency in production:
An application of data envelopment analysis to Japanese electric
utilities, Journal of Productivity Analysis 2003; 19 (2-3): 191 - 210.
[36] Pacudan, R., de Guzman, E. Impact of energy efficiency policy to
productive efficiency of electricity distribution industry in the
Philippines. Energy Economics 2002; 24(1): 41-54.
[37] Pahwa, A., Xiaoming, F., Lubkemann, D. Performance Evaluation of
Electric Distribution Utilities Based on Data Envelopment Analysis.
IEEE Transactions on Power Systems 2003; 18(1): 400-405.
[38] Rungsuriyawiboon, S., Stefanou, S. Dynamic efficiency estimation: An
application to U.S. Electric utilities. Journal of Business and Economic
Statistics 2007; 25(2): 226 - 238.
[39] Sanhueza, R., Rudnick, H. Discussion of "Performance evaluation of
electric distribution, utilities based on data envelopment analysis". IEEE
Transactions on Power Systems 2003; 18 (3): 1220 - 1221.
[40] Scarsi, G. Local Electricity Distribution in Italy: Comparative Efficiency
Analysis and Methodological Cross-Checking. Fondazione Eni Enrico
Mattei, Working Papers: 1999.16. 2000. Available at
http://www.feem.it/Feem/Pub/Publications/default.htm
[41] Sueyoshi, T. Tariff structure of Japanese electric power companies: An
empirical analysis using DEA. European Journal of Operational
Research 1999; 118(2); 350-374.
[42] Sueyoshi, T., Goto, M. Slack-adjusted DEA for time series analysis:
Performance, measurement of Japanese electric power generation
industry in, 1984-1993. European Journal of Operational Research 2001;
133 (2): 232 - 259.
[43] Tahvanainen, K., Viljainen, S., Honkapuro, S., Lassila,J., Partanen, J.,
Järventausta, P., Kivikko, K., Mäkinen, A. Quality regulation in
electricity distribution business. 2004. Available at
http://powersystems.tkk.fi/nordac2004/papers/nordac2004_tahvanainen_
et_al_paper.pdf.
[44] Tanure, S., Tahan, J., Lima, C., Marangon, J. Establishing Quality
Performance of Distribution Companies Based on Yardstick Regulation.
IEEE Transactions on Power Systems 2006; 21(3): 1148-1153.
[45] Thakur, T. Efficiency evaluation of the state owned electric utilities in
India. Energy Policy 2006; 34(17): 2788-2804.
[46] Torgersen, A., Fo├©rsund, F., Kittelsen, S.. Slack-adjusted efficiency
measures and ranking of efficient units. Journal of Productivity Analysis
1996; 7 (4): 379-398.
[47] Vaninsky, A. Efficiency of Electric Power Generation in the United
States: Analysis and Forecast Based on Data Envelopment Analysis.
Energy Economics 2006; 28 (3): 326 - 338.
[48] Vitaliano, D, and Stella, G. A Frontier Approach to Testing the Averch-
Johnson Hypothesis. Rensselaer Polytechnic Institute, Department of
Economics. Rensselaer Working Papers in Economics 2006.
[49] Yunos, JM, Hawdon, D. The efficiency of the National Electricity
Board in Malaysia: An intercountry comparison using DEA. Energy
Economics 1997;19 (2): 255-269.
[50] Zhou, M., Zhao, W., Wang, P., Li, G. Hierarchical yardstick competition
approach to assessing operation performance of distribution utilities.
Dianli Xitong Zidonghua/Automation of Electric Power Systems 2008;
32(4):20-24.
[51] http://www.bea.doe.gov - a website of the Bureau of Economic Analysis
of the United States Department of Commerce (BEA).
[52] http://www.eia.doe.gov - a website of the Energy Information
Administration of the United States, a section of the U.S. Department of
Energy (DOE).