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Parametric and semi-parametric estimation of the effect of firm attributes on efficiency: the electricity generating industry in India

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  • Madhu Khanna
  • Kusum Mundra
  • Aman Ullah

Abstract

A stochastic frontier cost function is estimated using panel data for the electricity generating industry in India. The impact of distributional and functional form assumptions on technical inefficiency and the sources of inefficiency are investigated by using maximum likelihood, GLS and semi-parametric-GLS approaches and by incorporating firm-specific inefficiency effects in the cost function itself. Average inefficiency in the electricity generating industry in India is found to be high by all three methods. The estimate predicted by the maximum-likelihood approach is, however, lower than that predicted by the other two methods. This could be due to the distributional assumptions made under the maximum likelihood method. Public ownership and low capacity utilization are found to be significant determinants of inefficiency in the electricity generating industry in India.

Suggested Citation

  • Madhu Khanna & Kusum Mundra & Aman Ullah, 1999. "Parametric and semi-parametric estimation of the effect of firm attributes on efficiency: the electricity generating industry in India," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 8(4), pages 419-430.
    • Handle: RePEc:taf:jitecd:v:8:y:1999:i:4:p:419-430
    DOI: 10.1080/09638199900000025
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    Citations

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    Cited by:

    1. Sugathan, Anish & Malghan, Deepak & Chandrashekar, S. & Sinha, Deepak K., 2019. "Downstream electric utility restructuring and upstream generation efficiency: Productivity dynamics of Indian coal and gas based electricity generators," Energy, Elsevier, vol. 178(C), pages 832-852.
    2. See, Kok Fong & Coelli, Tim, 2014. "Total factor productivity analysis of a single vertically integrated electricity utility in Malaysia using a Törnqvist index method," Utilities Policy, Elsevier, vol. 28(C), pages 62-72.
    3. Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
    4. Ghosh, Ranjan & Kathuria, Vinish, 2016. "The effect of regulatory governance on efficiency of thermal power generation in India: A stochastic frontier analysis," Energy Policy, Elsevier, vol. 89(C), pages 11-24.
    5. See, Kok Fong & Coelli, Tim, 2012. "An analysis of factors that influence the technical efficiency of Malaysian thermal power plants," Energy Economics, Elsevier, vol. 34(3), pages 677-685.
    6. Mohammad Ali Motafakker Azad & Mohsen Pourebadollahan Covich & Sakineh Sojoodi, 2015. "The Impact of Electricity Competitive Market Establishment on Technical Efficiency of Thermal Power Plants in Iran," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 1010-1015.
    7. Yu, Chin-Hsien & Zhao, Jinsong & Qin, Ping & Wang, Shinn-Shyr & Lee, Wen-Chieh, 2022. "Comparison of misallocation between the Chinese thermal power and hydropower electricity industries," Economic Modelling, Elsevier, vol. 116(C).
    8. Sushama Murty & Resham Nagpal, "undated". "Measuring output-based technical efficiency of Indian coal-based thermal power plants: A by-production approach," Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi Discussion Papers 18-07, Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi, India.
    9. Sebastian Cuadros & Yeny E. Rodríguez & Javier Contreras, 2023. "Determinants of the Efficiency of Electricity Generation in Latin America and Caribbean Countries Using a Cragg’s Regression Model," Energies, MDPI, vol. 16(23), pages 1-18, December.
    10. Kabir Malik & Maureen Cropper & Alexander Limonov & Anoop Singh, 2011. "Estimating the Impact of Restructuring on Electricity Generation Efficiency: The Case of the Indian Thermal Power Sector," NBER Working Papers 17383, National Bureau of Economic Research, Inc.

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