Green Productivity in Iran's Thermal Power Plants: The Malmquist-Luenberger Approach

Document Type : Research Article


Khorramshahr University of Marine Science and Technology, Khorramshahr, Iran.


Electricity generation in thermal power plants as the largest producer of electricity in Iran is associated with greenhouse gas emissions. In this paper, using the Malmquist-Luenberger method, green productivity, and efficiency changes are measured for 31 thermal power plants (including 12 steam power plants, 13 gas power plants, and six combined cycle power plants) during 2009-2016. The results show a slight increase in green productivity in gas power plants and a slight reduction in green productivity in combined cycle power plants. Also, green productivity in steam power plants has not changed approximately. The mean values of the Malmquist-Luenberger index for these three types of power plants are 1.007, 0.997, and 1.0005, respectively. Although the environmental performance of gas power plants is slightly better than the two other types of power plants, but the difference of mean values of the Malmquist-Luenberger index for the three types of power plants is small.Furthermore, if we compare the power plants individually, we get different results, the highest and lowest mean values of the Malmquist-Luenberger index (1.06 and 0.982) is for a steam power plant (Shahid Mofateh) and a gas power plant (Konarak) respectively. Therefore, the power generation method and type of power plant (gas, steam and combined cycle) have no significant effect on the environmental performance of power plants and the environmental performance of them can be affected by other factors. The results also show that combined cycle power plants are more efficient than gas power plants.


Barros, C.P., and Peypoch, N. (2008). Technical efficiency of thermoelectric power plants. Energy Economics, 30(6), 3118-3127.
Caves, D.W, Christensen, R.L, and Diewert, W. (1982). The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity. Econometrica, 50(6), 1393-1414.
Chen, S., and Golley, J. (2014). Green's productivity growth in China's industrial economy. Energy Economics, 44(3), 89-98.
Chung, Y.H., Fare, R., and Grosskopf, S. (1997). Productivity and Undesirable Outputs: A Directional Distance Function Approach. Journal of Environmental Management, 51(3), 229-240.
Coelli, T., Prasada Rao, D., and Battese, G.E. (1998). An Introduction to Efficiency and Productivity Analysis, Boston, Kluwe Academic Publishers.
EIA (energy information administration) (2016).Carbon dioxide emissions from electricity generation in 2015 were lowest since 1993,
IEA (2018), Key World Energy Statistics (2018). International Energy Agency, p. 14.
Emami meibodi, A. and Amini, F. (2017). Evaluation of Technical and Environmental Efficiency of Selected Thermal Power Plants of Iran. Quarterly Journal of Energy Policy and Planning Research, 3 (8), 33-6.
Fallahi, A., Ebrahimi, R., and Ghaderi, S, F. (2011).  Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis:  A case study. Energy, 36(11), 6398–6405
Fare, R., and Grosskopf, S. (1992). Malmquist Productivity Indexes and Fisher Ideal Indexed. Economic Journal, 102,158-160.
Giddings, B., Hopwood, B. and Obrean, G. (2002). Environment, economy, and society: fitting them together into sustainable development. Sustainable Development, 10(4), 187-196.
Hakimipour, N., and Avazalipour, M.S. (2012). Evaluating Productivity Changes of Entire Production Factors for Large Industries in the Provinces of Iran, Using Malmquist Productivity Index. Management Researches (in Persian), 5(15), 135-161
Imami Meybodi, A., Mohamadi, T., and Behroz, A. (2015).  Measuring the Economic Efficiencies and Productivity of Natural Gas Refineries in Iran. Quarterly Journal of Iranian Financial Economics (in Persian), 9(30), 61-82.
Kargari N., and Mastouri, R. (2010), Comparison of GHG Emission in Different Kinds of Power Plants by LCA Approach, Iranian Journal of Energy, 13 (2), 67-78.
Kumar, S. (2019). Carbon-sensitive Meta-Productivity Growth and Technological Gap: An Empirical Analysis of Indian Thermal Power Sector. Working Paper No. 297, Department of Business Economics, University of Delhi.
Kumar, S. (2006). Environmentally Sensitive Productivity Growth: A global analysis using the Malmquist Luenberger index. Ecological Economics, 56, 280-293.
lajevardi, H. (2013). To Assess The Impact Of Establishment Of Iran's Electric Power Market On Efficiency Of Power Plants. Iranian Electric Industry Journal of Quality and Productivity, 2 (3), 50-57.
Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estadistica, 4 (2), 209-242.
Nakano, M., and Managi, S. (2008). Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry. Energy Policy, 36(1)1, 201-209.
Sayfi, A., Salimifar, M., and Haniyeh, F. (2015). Measuring Environmental Efficiency: A Case Study of Thermal Power Generation in Jonoobi, Razavi, and Shomali Khorasan Provinces. Iranian Energy Economics, 2(7), 17-41.
Simar, L., and Wilson, P.W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136, 1–34.
Song, Y., Liu, H., Liu, X. and Yang, G. (2018). Measuring the productivity evolution of Chinese regional thermal power industries using the global Malmquist-Luenberger productivity index. International Journal of Energy Sector Management, 12(2), 221-243.
Sueyoshi, T., Goto, M., and Takahiro U. (2010). Performance analysis of US coal-fired power plants by measuring three DEA efficiencies. Energy Policy, 38(4), 1675-1688.
Tavanir (2015). A strategic document of increasing the efficiency of the country's thermal power plants.
Zhang, N., and Choi, Y. (2013).A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea. Energy Policy, 62, 324-32.
Zhang, N., Zhou, P., and Choi, Y. (2013). Energy efficiency, CO2 emission performance, and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance function analysis. Energy Policy, 56, 653-662.
Zhu, J., Zhou, D., Pu, Z., and Sun, H. (2019). A Study of Regional Power Generation Efficiency in China: Based on a Non-Radial Directional Distance Function Model. Sustainability, 11(3), 1-18.