IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v81y2019icp104-116.html
   My bibliography  Save this article

Carbon-sensitive meta-productivity growth and technological gap: An empirical analysis of Indian thermal power sector

Author

Listed:
  • Kumar, Surender
  • Jain, Rakesh Kumar

Abstract

This paper measures carbon-sensitive efficiency and productivity growth in technologically heterogeneous coal-fired thermal power plants in India for the period of 2000 to 2013. It uses a unique data set of 56 plants, obtained petitioning the Right to Information Act 2005. We apply ‘within-MLE’ fixed effects stochastic frontier model to get consistent estimates of meta-directional output distance function. The thermal power plants are grouped into two categories: central sector and state sector. We find that the state sector plants have higher potential to simultaneously increase electricity generation and reduce carbon emissions than the central sector plants. If all the state and central sectors plants were made to operate on the meta-frontier, reduction of 98 million tonnes of CO2 could have been achieved. Carbon-sensitive productivity growth in the central sector plants is higher than the plants in state sector, though in both the sectors productivity growth is governed by carbon-sensitive innovation effect. Commercialisation or autonomy in electricity generation also induces carbon-sensitive productivity growth and reduces carbon-sensitive productivity growth gap.

Suggested Citation

  • Kumar, Surender & Jain, Rakesh Kumar, 2019. "Carbon-sensitive meta-productivity growth and technological gap: An empirical analysis of Indian thermal power sector," Energy Economics, Elsevier, vol. 81(C), pages 104-116.
  • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:104-116
    DOI: 10.1016/j.eneco.2019.03.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319300945
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2019.03.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kumar, Surender & Managi, Shunsuke, 2016. "Carbon-sensitive productivity, climate and institutions," Environment and Development Economics, Cambridge University Press, vol. 21(1), pages 109-133, February.
    2. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    3. Fujii, Hidemichi & Managi, Shunsuke & Matousek, Roman, 2014. "Indian bank efficiency and productivity changes with undesirable outputs: A disaggregated approach," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 41-50.
    4. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    5. Rolf Färe & Carlos Martins-Filho & Michael Vardanyan, 2010. "On functional form representation of multi-output production technologies," Journal of Productivity Analysis, Springer, vol. 33(2), pages 81-96, April.
    6. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    7. Rakesh Kumar Jain & Surender Kumar, 2018. "Shadow price of CO2 emissions in Indian thermal power sector," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(4), pages 879-902, October.
    8. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    9. Wei, Chu & Löschel, Andreas & Liu, Bing, 2013. "An empirical analysis of the CO2 shadow price in Chinese thermal power enterprises," Energy Economics, Elsevier, vol. 40(C), pages 22-31.
    10. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    11. M. Murty & Surender Kumar & Kishore Dhavala, 2007. "Measuring environmental efficiency of industry: a case study of thermal power generation in India," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(1), pages 31-50, September.
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment," Energy Economics, Elsevier, vol. 40(C), pages 130-145.
    13. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    14. Pooran Lall & Allen Featherstone & David Norman, 2002. "Productivity Growth in the Western Hemisphere (1978–94): The Caribbean in Perspective," Journal of Productivity Analysis, Springer, vol. 17(3), pages 213-231, May.
    15. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    16. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    17. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    18. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464, January.
    19. Huang, Tai-Hsin & Chiang, Dien-Lin & Tsai, Chao-Min, 2015. "Applying the New Metafrontier Directional Distance Function to Compare Banking Efficiencies in Central and Eastern European Countries," Economic Modelling, Elsevier, vol. 44(C), pages 188-199.
    20. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    21. Jia-Ching Juo & Yu-Hui Lin & Tsai-Chia Chen, 2015. "Productivity change of Taiwanese farmers’ credit unions: a nonparametric metafrontier Malmquist–Luenberger productivity indicator," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 125-147, March.
    22. Shunsuke Managi & Surender Kumar, 2009. "The Economics of Sustainable Development," Natural Resource Management and Policy, Springer, number 978-0-387-98176-5, December.
    23. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    24. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    25. Jean‐Philippe Boussemart & Walter Briec & Kristiaan Kerstens & Jean‐Christophe Poutineau, 2003. "Luenberger and Malmquist Productivity Indices: Theoretical Comparisons and Empirical Illustration," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 391-405, October.
    26. Víctor Moreira & Boris Bravo-Ureta, 2010. "Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model," Journal of Productivity Analysis, Springer, vol. 33(1), pages 33-45, February.
    27. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    28. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    29. Surender Kumar & Hidemichi Fujii & Shunsuke Managi, 2015. "Substitute or complement? Assessing renewable and nonrenewable energy in OECD countries," Applied Economics, Taylor & Francis Journals, vol. 47(14), pages 1438-1459, March.
    30. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    31. Chambers, Robert G. & Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity Growth in APEC Countries," Working Papers 197843, University of Maryland, Department of Agricultural and Resource Economics.
    32. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    33. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
    34. Russell W. Pittman, 1981. "Issue in Pollution Control: Interplant Cost Differences and Economies of Scale," Land Economics, University of Wisconsin Press, vol. 57(1), pages 1-17.
    35. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    36. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    37. R. Färe & S. Grosskopf & D. Margaritis, 2008. "U.S. productivity in agriculture and R&D," Journal of Productivity Analysis, Springer, vol. 30(1), pages 7-12, August.
    38. Kumar, Surender & Managi, Shunsuke, 2009. "Energy price-induced and exogenous technological change: Assessing the economic and environmental outcomes," Resource and Energy Economics, Elsevier, vol. 31(4), pages 334-353, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sarangi, Gopal K. & Pradhan, Abhilas Kumar & Taghizadeh-Hesary, Farhad, 2021. "Performance assessment of state-owned electricity distribution utilities in India," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 516-531.
    2. Abhinav Jindal & Rahul Nilakantan, 2022. "Regulatory independence and thermal power plant performance: evidence from India," Journal of Regulatory Economics, Springer, vol. 61(1), pages 32-47, February.
    3. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    4. Shen, Neng & Peng, Hui & Wang, Qunwei, 2021. "Spatial dependence, agglomeration externalities and the convergence of carbon productivity," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    5. Liu, Xiao & Hang, Ye & Wang, Qunwei & Chiu, Ching-Ren & Zhou, Dequn, 2022. "The role of energy consumption in global carbon intensity change: A meta-frontier-based production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 109(C).
    6. Wenhao Qi & Changxing Song & Meng Sun & Liguo Wang & Youcheng Han, 2022. "Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity," IJERPH, MDPI, vol. 19(3), pages 1-25, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    2. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
    3. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
    4. Abebayehu Girma Geffersa & Frank Wogbe Agbola & Amir Mahmood, 2022. "Modelling technical efficiency and technology gap in smallholder maize sector in Ethiopia: accounting for farm heterogeneity," Applied Economics, Taylor & Francis Journals, vol. 54(5), pages 506-521, January.
    5. Rakesh Kumar Jain & Surender Kumar, 2018. "Shadow price of CO2 emissions in Indian thermal power sector," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(4), pages 879-902, October.
    6. Zarkovic, Maja, 2020. "Cap-and-trade and produce at least cost? Investigating firm behaviour in the EU ETS," Working papers 2020/12, Faculty of Business and Economics - University of Basel.
    7. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    8. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    9. John N. Ng’ombe, 2017. "Technical efficiency of smallholder maize production in Zambia: a stochastic meta-frontier approach," Agrekon, Taylor & Francis Journals, vol. 56(4), pages 347-365, October.
    10. Yung-Hsiang Lu & Ku-Hsieh Chen & Jen-Chi Cheng & Chih-Chun Chen & Sian-Yuan Li, 2019. "Analysis of Environmental Productivity on Fossil Fuel Power Plants in the U.S," Sustainability, MDPI, vol. 11(24), pages 1-27, December.
    11. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    12. Lizhan Cao & Zhongying Qi & Junxia Ren, 2017. "China’s Industrial Total-Factor Energy Productivity Growth at Sub-Industry Level: A Two-Step Stochastic Metafrontier Malmquist Index Approach," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
    13. Yu-Ying Lin, Eugene & Chen, Ping-Yu & Chen, Chi-Chung, 2013. "Measuring green productivity of country: A generlized metafrontier Malmquist productivity index approach," Energy, Elsevier, vol. 55(C), pages 340-353.
    14. Du, Limin & Mao, Jie, 2015. "Estimating the environmental efficiency and marginal CO2 abatement cost of coal-fired power plants in China," Energy Policy, Elsevier, vol. 85(C), pages 347-356.
    15. Surender Kumar & Rakesh Kumar Jain, 2021. "Cost of CO2 emission mitigation and its decomposition: evidence from coal-fired thermal power sector in India," Empirical Economics, Springer, vol. 61(2), pages 693-717, August.
    16. Huang, Tai-Hsin & Chiang, Dien-Lin & Tsai, Chao-Min, 2015. "Applying the New Metafrontier Directional Distance Function to Compare Banking Efficiencies in Central and Eastern European Countries," Economic Modelling, Elsevier, vol. 44(C), pages 188-199.
    17. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    18. Yang, Jun & Cheng, Jixin & Zou, Ran & Geng, Zhifei, 2021. "Industrial SO2 technical efficiency, reduction potential and technology heterogeneities of China's prefecture-level cities: A multi-hierarchy meta-frontier parametric approach," Energy Economics, Elsevier, vol. 104(C).
    19. Zhang, Ning & Jiang, Xue-Feng, 2019. "The effect of environmental policy on Chinese firm's green productivity and shadow price: A metafrontier input distance function approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 129-136.
    20. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).

    More about this item

    Keywords

    Carbon-sensitive productivity; Luenberger Productivity Indicator; Stochastic meta-frontier; Indian thermal power plants;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:104-116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.