Measuring efficiency and productivity change in power electric generation management companies by us

This paper provides an empirical analysis of the determinants of energy efficiency in 32 power electric generation management companies over the period 2005–2009. The study uses non-parametric Data Envelopment Analysis (DEA) to estimate the relative technical efficiency and productivity change of these companies. In order to verify the stability of our DEA model and the importance of each input variable, a stability test is also conducted. The results of the study indicate that average technical efficiency of companies decreased during the study period. Nearly half of the companies (14) are below this average level of 88.7% for five years. Moreover, it is shown that the low increase of productivity changes is more related to low efficiency rather than technology changes.

[1]  Soo-Uk Park,et al.  The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches , 2000 .

[2]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[3]  Alice Shiu,et al.  A data envelopment analysis of the efficiency of China’s thermal power generation , 2001 .

[4]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[5]  M. Abbott,et al.  The productivity and efficiency of the Australian electricity supply industry , 2006 .

[6]  G. Debreu The Coefficient of Resource Utilization , 1951 .

[7]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[8]  Raúl Pérez-Reyes,et al.  Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms , 2009 .

[9]  Yaakov Roll,et al.  An application procedure for DEA , 1989 .

[10]  Necmi K. Avkiran,et al.  Stability and integrity tests in data envelopment analysis , 2007 .

[11]  Andrew Hughes,et al.  Sensitivity and dimensionality tests of DEA efficiency scores , 2004, Eur. J. Oper. Res..

[12]  R. Banker Estimating most productive scale size using data envelopment analysis , 1984 .

[13]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[14]  Adnan Sözen,et al.  Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis , 2010 .

[15]  William W. Cooper,et al.  Introduction to Data Envelopment Analysis and Its Uses: With Dea-Solver Software and References , 2005 .

[16]  Sue J. Lin,et al.  Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis , 2010 .

[17]  R. Färe,et al.  The measurement of efficiency of production , 1985 .

[18]  S. Deshmukh,et al.  Efficiency evaluation of the state owned electric utilities in India , 2006 .

[19]  Carlos Pestana Barros,et al.  Technical efficiency of thermoelectric power plants , 2008 .

[20]  B. Golany,et al.  Measuring efficiency of power plants in Israel by data envelopment analysis , 1994 .

[21]  Shunsuke Managi,et al.  Regulatory reforms and productivity : an empirical analysis of the Japanese electricity industry , 2008 .

[22]  Léopold Simar,et al.  Estimating efficiencies from frontier models with panel data: A comparison of parametric, non-parametric and semi-parametric methods with bootstrapping , 1992 .

[23]  M. Goto,et al.  Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities , 2003 .

[24]  Narayana Prasad Padhy,et al.  A micro level study of an Indian electric utility for efficiency enhancement , 2010 .

[25]  C. Barros Efficiency analysis of hydroelectric generating plants : A case study for Portugal , 2008 .

[26]  Emmanuel Thanassoulis,et al.  Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software , 2001 .

[27]  R. Raab,et al.  Identifying Subareas that Comprise a Greater Metropolitan Area: The Criterion of County Relative Efficiency , 2002 .

[28]  Kemal Sarica,et al.  Efficiency assessment of Turkish power plants using data envelopment analysis , 2007 .

[29]  Shiv Prasad Yadav,et al.  Relative performance of academic departments using DEA with sensitivity analysis. , 2009, Evaluation and program planning.

[30]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[31]  R. Färe,et al.  Productivity Developments in Swedish Hospitals: A Malmquist Output Index Approach , 1994 .

[32]  David Hawdon,et al.  Efficiency, performance and regulation of the international gas industry—a bootstrap DEA approach , 2003 .

[33]  Alexander Vaninsky,et al.  Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis , 2006 .

[34]  B. W. Ang,et al.  Measuring thermal efficiency improvement in power generation , 2002 .