DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations

Energy Economics

Volumn 40, Issue , 2013, Pages 370-382

  Sueyoshi, Toshiyuki ^a   Goto, Mika ^b  

^a NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY   (United States)

^b CENTRAL RESEARCH INSTITUTE OF ELECTRIC POWER INDUSTRY   (Japan)

Author keywords

DEA; Electricity; Environmental assessment; Time series

Indexed keywords

DEA; ECONOMIC DEVELOPMENT; ELECTRIC POWER INDUSTRIES; ELECTRICITY GENERATION; ENVIRONMENTAL ASSESSMENT; SUSTAINABLE SOCIETY; TECHNOLOGY INNOVATION; TECHNOLOGY PROGRESS;

ECONOMICS; ELECTRIC INDUSTRY; ELECTRICITY; EMISSION CONTROL; ENGINEERING RESEARCH; GLOBAL WARMING; MANAGERS; SUSTAINABLE DEVELOPMENT; TIME SERIES;

CARBON DIOXIDE;

CARBON DIOXIDE; CARBON EMISSION; DATA ENVELOPMENT ANALYSIS; ECONOMIC DEVELOPMENT; ELECTRICITY GENERATION; ELECTRICITY SUPPLY; ENERGY EFFICIENCY; ENVIRONMENTAL ASSESSMENT; ENVIRONMENTAL ECONOMICS; ENVIRONMENTAL PROTECTION; INNOVATION; SUSTAINABILITY; TIME SERIES ANALYSIS;

EID: 84883356860     PISSN: 01409883     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eneco.2013.07.013     Document Type: Article

References (53)

1. Bjurek H. The Malmquist total factor productivity index. Scand. J. Econ. 1996, 98:303-3013.
2. Bjurek H., Hjalmarsson L. Productivity in multiple output public services: a quadratic frontier function and the Malmquist index approach. J. Public Econ. 1995, 56:447-460.
3. Bowlin W.F. Evaluating the efficiency of US air force real-property maintenance activities. J. Oper. Res. Soc. 1987, 38:127-135.
4. Dyckhoff H., Allen K. Measuring ecological efficiency with data envelopment analysis (DEA). Eur. J. Oper. Res. 2001, 132:312-325.
5. Färe R., Grosskoph S. Malmquist productivity indexes and fisher ideal indexes. Econ. J. 1992, 102:158-160.
6. Glover F., Sueyoshi T. Contributions of Professor William W. Cooper in operations research and management science. Eur. J. Oper. Res. 2009, 197:1-16.
7. Goto M., Tsutsui M. Comparison of productive and cost efficiencies among Japanese and US electric utilities. Omega 1998, 26:177-194.
8. Grifell-Tatje E., Lovel C.A.K. A note on the Malmquist productivity index. Econ. Lett. 1995, 47:167-175.
9. Ijiri Y., Sueyoshi T. Accounting essays by Professor William W. Cooper: revisiting in commemoration of his 95th birthday. Abacus 2010, 46:464-505.
10. Korhonen P.J., Luptacik M. Eco-efficiency analysis of power plants: an extension of data envelopment analysis. Eur. J. Oper. Res. 2004, 154:437-446.
11. Kumar S. Environmentally sensitive productivity growth: a global analysis using Malmquist-Luenberger index. Ecol. Econ. 2006, 56:280-293.
12. Liang L., Wu D., Hua Z. MES-DEA modeling for analyzing anti-industrial pollution efficiency and its application in Anhui province of China. Int J Global Energy 2004, 22:88-98.
13. Malmquist S. Index number and indifferences surfaces. Trab. Estat. 1953, 4:209-2042.
14. 2 and energy efficiency of Dutch greenhouse firms. J. Environ. Manage. 2003, 68:73-82.
15. Palmer K.W., Oates W.E., Portney P.R. Tightening environmental standards - the benefit-cost or the no-cost paradigm. J. Econ. Perspect. 1995, 9:119-132.
16. Pasurka C.A. Decomposing electric power plant emissions within a joint production framework. Energy Econ. 2006, 28:26-43.
17. Picazo-Tadeo A.J., Reig-Martinez E., Hernandez-Sancho F. Directional distance functions and environmental regulation. Resour. Energy Econ. 2005, 27:131-142.
18. Porter M.E., van der Linde C. Toward a new conception of the environment competitiveness relationship. J. Econ. Perspect. 1995, 9:97-118.
19. 2 emissions: a cross-country comparison. Int. J. Global Energy 2002, 17:214-227.
20. Sueyoshi T., Aoki S. A use of a nonparametric statistic for DEA frontier shift: the Kruskal and Wallis rank test. Omega 2001, 29:1-18.
21. Sueyoshi T., Goto M. Slack-adjusted DEA for time series analysis: performance measurement of Japanese electric power generation industry in 1984-1993. Eur. J. Oper. Res. 2001, 133:232-259.
22. Sueyoshi T., Goto M. Can environmental investment and expenditure enhance financial performance of US electric utility firms under the clean air act amendment of 1990?. Energy Policy 2009, 37:4819-4826.
23. Sueyoshi T., Goto M. Methodological comparison between DEA (Data Envelopment Analysis) and DEA-DA (Discriminant Analysis) from the perspective of bankruptcy assessment. Eur. J. Oper. Res. 2009, 199:561-575.
24. Sueyoshi T., Goto M. Measurement of a linkage among environmental, operational and financial performance in Japanese manufacturing firms: a use of data envelopment analysis with strong complementary slackness condition. Eur. J. Oper. Res. 2010, 207:1742-1753.
25. 2 emission control? Examination by data envelopment analysis. Energy Policy 2010, 38:5902-5911.
26. Sueyoshi T., Goto M. DEA approach for unified efficiency measurement: assessment of Japanese fossil fuel power generation. Energy Econ. 2011, 33:195-208.
27. Sueyoshi T., Goto M. Methodological comparison between two unified (operational and environmental) efficiency measurements for environmental assessment. Eur. J. Oper. Res. 2011, 210:684-693.
28. Sueyoshi T., Goto M. Measurement of returns to scale and damages to scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs?. Eur. J. Oper. Res. 2011, 211:76-89.
29. Sueyoshi T., Goto M. A combined use of DEA (data envelopment analysis) with strong complementary slackness condition and DEA-DA (discriminant analysis). Appl. Math. Lett. 2011, 24:1051-1056.
30. Sueyoshi T., Goto M. Data envelopment analysis for environmental assessment: comparison between public and private ownership in petroleum industry. Eur. J. Oper. Res. 2012, 216:668-678.
31. Sueyoshi T., Goto M. Returns to scale and damages to scale under natural and managerial disposability: strategy, efficiency and competitiveness of petroleum firms. Energy Econ. 2012, 34:645-662.
32. Sueyoshi T., Goto M. Environmental assessment by DEA radial measurement: U.S. coal-fired power plants in ISO (Independent System Operator) and RTO (Regional Transmission Organization). Energy Econ. 2012, 34:663-676.
33. Sueyoshi T., Goto M. Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: comparison between Japanese electric power industry and manufacturing industries. Energy Econ. 2012, 34:686-699.
34. Sueyoshi T., Goto M. DEA radial and non-radial models for unified efficiency under natural and managerial disposability: theoretical extension by strong complementary slackness conditions. Energy Econ. 2012, 34:700-713.
35. Sueyoshi T., Goto M. Returns to scale, damages of scale, marginal rate of transformation and rate of substitution in DEA environmental assessment. Energy Econ. 2012, 34:905-917.
36. Sueyoshi T., Goto M. Returns to scale and damages to scale under strong complementary slackness conditions in DEA assessment: Japanese corporate effort on environmental protection. Energy Econ. 2012, 34:1422-1434.
37. Sueyoshi T., Goto M. DEA environmental assessment of coal fired power plants: methodological comparison between radial and non-radial models. Energy Econ. 2012, 34:1854-1863.
38. Sueyoshi T., Goto M. Returns to scale and damages to scale on U.S. fossil fuel power plants: Radial and non-radial approaches for DEA environment assessment. Energy Econ. 2012, 34:2240-2259.
39. Sueyoshi T., Goto M. DEA radial measurement for environmental assessment and planning: desirable procedures to evaluate fossil fuel power plants. Energy Policy 2012, 41:422-432.
40. Sueyoshi T., Goto M. Efficiency-based rank assessment for electric power industry: a combined use of data envelopment analysis (DEA) and DEA-discriminant analysis (DA). Energy Econ. 2012, 34:634-644.
41. Sueyoshi T., Goto M. Returns to scale vs. damages to scale in data envelopment analysis: an impact of U.S. clean air act on coal-fired power plants. Omega 2013, 41:164-175.
42. Sueyoshi T., Goto M. A use of DEA-DA to measure importance of R&D expenditure in Japanese information technology industry. Decis. Support. Syst. 2013, 54:941-952.
43. Sueyoshi T., Goto M. Pitfalls and remedies in DEA applications: how to handle an occurrence of zero in multipliers by strong complementary slackness conditions. Engineering 2013, 5:29-34.
44. Sueyoshi T., Goto M. A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment. Energy Econ. 2013, 40:130-145.
45. Sueyoshi T., Sekitani K. An occurrence of multiple projections in DEA-based measurement of technical efficiency: theoretical comparison among DEA Models from desirable properties. Eur. J. Oper. Res. 2009, 196:764-794.
46. Sueyoshi T., Goto M., Shang J. Core business concentration vs. corporate diversification in the US electric utility industry: synergy and deregulation effects. Energy Policy 2009, 37:4583-4594.
47. Sueyoshi T., Goto M., Snell M.A. DEA environmental assessment: measurement of damages to scale with unified efficiency under managerial disposability or environmental efficiency. Appl. Math. Model. 2013, 37:7300-7314.
48. Thore S., Kozmetsky G., Phillips F. DEA of financial statements data: the US computer industry. J. Product. Anal. 1994, 5:229-248.
49. Triantis K., Otis P. Dominance-based measurement of productive and environmental performance for manufacturing. Eur. J. Oper. Res. 2004, 154:447-464.
50. Zaim O. Measuring environmental performance of state manufacturing through changes in pollution intensities: A DEA framework. Ecol. Econ. 2004, 48:37-47.
51. Zhou P., Ang B.W., Poh K.L. A survey of data envelopment analysis in energy and environmental studies. Eur. J. Oper. Res. 2008, 189:1-18.
52. Zhou P., Ang B.W., Han J.Y. Total factor carbon emission performance: A Malmquist index analysis. Energy Econ. 2010, 32:194-201.
53. 2 emission performance in electricity generation: a non-radial directional distance function approach. Eur. J. Oper. Res. 2012, 221:625-635.